Gelebte Mehrsprachigkeit am Sprachenzentrum Luxemburg: Mit studentischen Assistent:innen für Studierende. Peer-Tutorien von Studierenden für Studierende

in Fremdsprachen in Lehre und Forschung (FLF) Band 56 (in press), 56

The language centres at the universities in the Greater Region have adopted a French-German tandem module as part of a joint course that provides linguistic and cultural preparation for students ahead of ... [more ▼]

The language centres at the universities in the Greater Region have adopted a French-German tandem module as part of a joint course that provides linguistic and cultural preparation for students ahead of their upcoming mobility semester. But there are often not enough French-speaking students to complete the tandems. So as an alternative, our student assistants can now guide student pairs or trios through their tandem activities. Based on comments from students and the experience of tutors in group tandems, a practical handbook has been produced to help train tutors, while a contract between tandem partners further engages them as soon as the tandem is set up. [less ▲]

ProPILE: Probing Privacy Leakage in Large Language Models

in Advances in Neural Information Processing Systems 36 (NeurIPS 2023) (2023, December)

The rapid advancement and widespread use of large language models (LLMs) have raised significant concerns regarding the potential leakage of personally identifiable information (PII). These models are ... [more ▼]

The rapid advancement and widespread use of large language models (LLMs) have raised significant concerns regarding the potential leakage of personally identifiable information (PII). These models are often trained on vast quantities of web-collected data, which may inadvertently include sensitive personal data. This paper presents ProPILE, a novel probing tool designed to empower data subjects, or the owners of the PII, with awareness of potential PII leakage in LLM-based services. ProPILE lets data subjects formulate prompts based on their own PII to evaluate the level of privacy intrusion in LLMs. We demonstrate its application on the OPT-1.3B model trained on the publicly available Pile dataset. We show how hypothetical data subjects may assess the likelihood of their PII being included in the Pile dataset being revealed. ProPILE can also be leveraged by LLM service providers to effectively evaluate their own levels of PII leakage with more powerful prompts specifically tuned for their in-house models. This tool represents a pioneering step towards empowering the data subjects for their awareness and control over their own data on the web. [less ▲]

Multi-label Deepfake Classification

in IEEE Workshop on Multimedia Signal Processing (2023, September 27)

In this paper, we investigate the suitability of current multi-label classification approaches for deepfake detection. With the recent advances in generative modeling, new deepfake detection methods have ... [more ▼]

In this paper, we investigate the suitability of current multi-label classification approaches for deepfake detection. With the recent advances in generative modeling, new deepfake detection methods have been proposed. Nevertheless, they mostly formulate this topic as a binary classification problem, resulting in poor explainability capabilities. Indeed, a forged image might be induced by multi-step manipulations with different properties. For a better interpretability of the results, recognizing the nature of these stacked manipulations is highly relevant. For that reason, we propose to model deepfake detection as a multi-label classification task, where each label corresponds to a specific kind of manipulation. In this context, state-of-the-art multi-label image classification methods are considered. Extensive experiments are performed to assess the practical use case of deepfake detection. [less ▲]

The Integration of the Advertising Function in Marketing within the Philips Company, 1959-1975

in Proceedings of the 21st Biennial Conference on Historical Analysis & Research in Marketing (CHARM) (2023, June 26), Vol. 21. Esse quam videri. Marketing history for real.

Load Introduction Zone Connection in Composite Columns

in Young Engineers Colloquium Dresden 2023 (2023, May)

The Burden of Being a Bridge: Analysing Subjective Well-Being of Twitter Users During the COVID-19 Pandemic

(2023, March 17)

Children’s perspectives on their learning experiences during the pandemic

in Developmental and Adolescent Health (2023), 2(4),

The present paper is based on two online surveys of the mix-method projects COVID-Kids I and II which investigated children’s school experiences, emotional responses, and subjective well-being during the ... [more ▼]

The present paper is based on two online surveys of the mix-method projects COVID-Kids I and II which investigated children’s school experiences, emotional responses, and subjective well-being during the Covid-19 pandemic in 2020 and 2021. The data of the 2020 questionnaire stem from 1,773 children aged 6-16 from Luxembourg, Germany and Switzerland (Kirsch et al., 2021) and those of the second questionnaire from 502 children of the same age group in Luxembourg (Kirsch et al., 2022). The presentation will examine some of the participants’ challenges with home schooling as well as selected outcomes and conclude with a few implications. [less ▲]

Scalable Coercion-Resistant E-Voting under Weaker Trust Assumptions

in Proceedings of ACM SAC Conference (SAC'23) (2023)

Electronic voting (e-voting) is regularly used in many countries and organizations for legally binding elections. In order to conduct such elections securely, numerous e-voting systems have been proposed ... [more ▼]

Electronic voting (e-voting) is regularly used in many countries and organizations for legally binding elections. In order to conduct such elections securely, numerous e-voting systems have been proposed over the last few decades. Notably, some of these systems were designed to provide coercion-resistance. This property protects against potential adversaries trying to swing an election by coercing voters. Despite the multitude of existing coercion-resistant e-voting systems, to date, only few of them can handle large-scale Internet elections efficiently. One of these systems, VoteAgain (USENIX Security 2020), was originally claimed secure under similar trust assumptions to state-of-the-art e-voting systems without coercion-resistance. In this work, we review VoteAgain's security properties. We discover that, unlike originally claimed, VoteAgain is no more secure than a trivial voting system with a completely trusted election authority. In order to mitigate this issue, we propose a variant of VoteAgain which effectively mitigates trust on the election authorities and, at the same time, preserves VoteAgain's usability and efficiency. Altogether, our findings bring the state of science one step closer to the goal of scalable coercion-resistant e-voting being secure under reasonable trust assumptions. [less ▲]

CODEBERT-NT: code naturalness via CodeBERT

in 22nd IEEE International Conference on Software Quality, Reliability and Security (QRS'22) (2022, December 05)

Much of recent software-engineering research has investigated the naturalness of code, the fact that code, in small code snippets, is repetitive and can be predicted using statistical language models like ... [more ▼]

Much of recent software-engineering research has investigated the naturalness of code, the fact that code, in small code snippets, is repetitive and can be predicted using statistical language models like n-gram. Although powerful, training such models on large code corpus can be tedious, time consuming and sensitive to code patterns (and practices) encountered during training. Consequently, these models are often trained on a small corpus and thus only estimate the language naturalness relative to a specific style of programming or type of project. To overcome these issues, we investigate the use of pre-trained generative language models to infer code naturalness. Pre-trained models are often built on big data, are easy to use in an out-of-the-box way and include powerful learning associations mechanisms. Our key idea is to quantify code naturalness through its predictability, by using state-of-the-art generative pre-trained language models. Thus, we suggest to infer naturalness by masking (omitting) code tokens, one at a time, of code-sequences, and checking the models’ability to predict them. We explore three different predictability metrics; a) measuring the number of exact matches of the predictions, b) computing the embedding similarity between the original and predicted code, i.e., similarity at the vector space, and c) computing the confidence of the model when doing the token completion task regardless of the outcome. We implement this workflow, named CODEBERT-NT, and evaluate its capability to prioritize buggy lines over non-buggy ones when ranking code based on its naturalness. Our results, on 2,510 buggy versions of 40 projects from the SmartShark dataset, show that CODEBERT-NT outperforms both, random-uniform and complexity-based ranking techniques, and yields comparable results to the n-gram models. [less ▲]

Why do Competition Authorities need Artificial Intelligence?

in Yearbook of Antitrust and Regulatory Studies (2022, December), 15(26), 33-55

Recent technological developments are transforming the way antitrust is enforced as well as the way market players are infringing competition law. As a result, enforcers are starting to equip themselves ... [more ▼]

Recent technological developments are transforming the way antitrust is enforced as well as the way market players are infringing competition law. As a result, enforcers are starting to equip themselves with sophisticated digital investigation tools. This paper explores this interest in building an Artificial Intelligence (AI) arsenal for the fight against algorithmic infringements. What are the key factors motivating regulators to develop their own technological tools to enforce competition law? Building on interviews with a number of competition authorities, this paper finds that changes in digital markets, the need for enforcers to reverse- engineer companies’ algorithms in order to better understand their implications for competition law, the need to enhance efficiency and keep pace with the fast evolution of the digital economy, and, finally, the decrease in leniency applications, are all reasons for which competition authorities should strive for more innovative and alternative means to boost their ex officio investigations. [less ▲]

Secure and Distributed Assessment of Privacy-Preserving Releases of GWAS

in ACM/IFIP International Middleware Conference (2022, November)

Genome-wide association studies (GWAS) identify correlations between the genetic variants and an observable characteristic such as a disease. Previous works presented privacy-preserving distributed ... [more ▼]

Genome-wide association studies (GWAS) identify correlations between the genetic variants and an observable characteristic such as a disease. Previous works presented privacy-preserving distributed algorithms for a federation of genome data holders that spans multiple institutional and legislative domains to securely compute GWAS results. However, these algorithms have limited applicability, since they still require a centralized instance to decide whether GWAS results can be safely disclosed, which is in violation to privacy regulations, such as GDPR. In this work, we introduce GenDPR, a distributed middleware that leverages Trusted Execution Environments (TEEs) to securely determine a subset of the potential GWAS statistics that can be safely released. GenDPR achieves the same accuracy as centralized solutions, but requires transferring significantly less data because TEEs only exchange intermediary results but no genomes. Additionally, GenDPR can be configured to tolerate all-but-one honest-but-curious federation members colluding with the aim to expose genomes of correct members. [less ▲]

What Really Drives the Spread of COVID-19 Tweets: A Revisit from Perspective of Content

in 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA) (2022, October 13)

COVID-19 content spreads wildly on social media and produces significant effects in both causing social panic and assisting pandemic management. However, what really enhances the diffusion of pandemic ... [more ▼]

COVID-19 content spreads wildly on social media and produces significant effects in both causing social panic and assisting pandemic management. However, what really enhances the diffusion of pandemic-related content during COVID-19, particularly from the perspective of the content itself, remains unexplored. Using large-scale COVID-19 tweets posted on Twitter, this paper empirically examines the effects of the four key characteristics, namely emotions, topics, hashtags, and mentions, on information spread in the pandemic. The empirical results show that most negative emotions have positive effects on retweeting. Nevertheless, the positive effect of trust on retweeting is unexpectedly the strongest. And the positive effects of the political topics and mentioning politicians further indicate that people are sensitive to the politicization of information during the pandemic. The strongest anger intensity in the political topic also needs to be noticed. The results complement the extant understanding of information diffusion during COVID-19 and provide insights for the governments to understand the psychology and behavior of large population during disasters like global pandemics. [less ▲]

A Secure Authentication Protocol for Cholesteric Spherical Reflectors using Homomorphic Encryption

in Lecture Notes in Computer Science (2022, October 06), 13503

Sometimes fingerprint-like features are found in a material. The exciting discovery poses new challenges on how to use the features to build an object authentication protocol that could tell customers and ... [more ▼]

Sometimes fingerprint-like features are found in a material. The exciting discovery poses new challenges on how to use the features to build an object authentication protocol that could tell customers and retailers equipped with a mobile device whether a good is authentic or fake. We are exactly in this situation with Cholesteric Spherical Reflectors (CSRs), tiny spheres of liquid crystals with which we can tag or coat objects. They are being proposed as a potential game-changer material in anti-counterfeiting due to their unique optical properties. In addition to the problem of processing images and extracting the minutiæ embedded in a CSR, one major challenge is designing cryptographically secure authentication protocols. The authentication procedure has to handle unstable input data; it has to measure the distance between some reference data stored at enrollment and noisy input provided at authentication. We propose a cryptographic authentication protocol that solves the problem, and that is secure against semi-honest and malicious adversaries. We prove that our design ensures data privacy even if enrolled data are leaked and even if servers and provers are actively curious. We implement and benchmark the protocol in Python using the Microsoft SEAL library through its Python wrapper PySEAL. [less ▲]

OpenAirInterface as a platform for 5G-NTN Research and Experimentation

in IEEE Future Networks World Forum (2022, October)

Technical advancements and experimental works for the integration of 5G and Non-Terrestrial Networks (NTN) have gained significant traction over the past few years. NTN components have been officially ... [more ▼]

Technical advancements and experimental works for the integration of 5G and Non-Terrestrial Networks (NTN) have gained significant traction over the past few years. NTN components have been officially included in the 5G ecosystem by 3GPP in the latest Release-17. 5G-NTN research is ongoing and it is desirable to have a platform that facilitates quick prototyping of the proof-of-concept methods. OpenAirInterface(OAI) is an open-source experimental yet 3GPP standard-compliant Software Defined Radio (SDR) based protocol stack that has been widely known for implementing 4G/5G technologies. Due to its proven capabilities and flexibility, OAI is currently in the developmental process of integrating adaptations for the 5G-NTN. In this work, we discuss the peculiar features of OAI which are shaping it towards becoming a preferred tool for research and experimentation related to 5G-NTN. We provide details of completed/ongoing 5G-NTN projects leveraging OAI to achieve their objectives. In particular, we discuss 5G-GOA and 5G-LEO where critical adaptations in OAI are being done to support 5G-NTN usecases. Such adaptations enable direct-access between UE and gNB via transparent payload Geostationary (5G-GOA) and Nongeostationary satellites (5G-LEO). Both projects have closely followed 3GPP discussions over 5G-NTN and the adaptations are compliant with the currently frozen 3GPP Release-17. OAI adaptations from both projects will be merged into the main development branch of OAI. We also provide a future roadmap of OAI towards 5G-NTN development. We believe that the pioneering steps taken in the course of the aforementioned projects will establish OAI as a preferred tool for 5G-NTN research and experimentations. [less ▲]

Optimal industrial flexibility scheduling based on generic data format

in Energy Informatics (2022, September 07), 5

The energy transition into a modern power system requires energy flexibility. Demand Response (DR) is one promising option for providing this flexibility. With the highest share of final energy ... [more ▼]

The energy transition into a modern power system requires energy flexibility. Demand Response (DR) is one promising option for providing this flexibility. With the highest share of final energy consumption, the industry has the potential to offer DR and contribute to the energy transition by adjusting its energy demand. This paper proposes a mathematical optimization model that uses a generic data model for flexibility description. The optimization model supports industrial companies to select when (i.e., at which time), where (i.e., in which market), and how (i.e., the schedule) they should market their flexibility potential to optimize profit. We evaluate the optimization model under several synthetic use cases developed upon the learnings over several workshops and bilateral discussions with industrial partners from the paper and aluminum industry. The results of the optimization model evaluation suggest the model can fulfill its purpose under different use cases even with complex use cases such as various loads and storages. However, the optimization model computation time grows as the complexity of use cases grows. [less ▲]

Integrated Spacecraft Design: Demonstration of a prototype process and platform for satellite design application

in Proceedings of International Astronautical Congress (2022, September)

The Impact Of Distributed Data Preprocessing On Automotive Data Streams

in 2022 IEEE 96th Vehicular Technology Conference: (VTC2022-Fall) (2022, September)

Vehicles have transformed into sophisticated com- puting machines that not only serve the objective of transporta- tion from point A to point B but serve other objectives including improved experience ... [more ▼]

Vehicles have transformed into sophisticated com- puting machines that not only serve the objective of transporta- tion from point A to point B but serve other objectives including improved experience, safer journey, automated and more efficient and sustainable transportation. With such sophistication comes complex applications and enormous volumes of data generated from diverse types of vehicle sensors and components. Automotive data is not sedentary but moves from the edge (the vehicle) to the cloud (e.g., infrastructure of the vehicle manufacturers, national highway agencies, insurance companies, etc.). The exponential increase in data volume and variety generated in modern vehicles far exceeds the rate of infrastructure scaling and expansion. To mitigate this challenge, the computational and storage capacities of vehicle components can be leveraged to perform in-vehicle operations on the data to either prepare and transform (prepro- cess) the data or extract information from (process) the data. This paper focuses on distributing data preprocessing to the vehicle and highlights the benefits and impact of the distribution including on the consumption of resources (e.g., energy). [less ▲]

Privacy in Cross-border Digital Currency. A Transatlantic Approach

in Frankfurt Forum on US-European GeoEconomics (2022, September)

As a growing number of countries explore Central Bank Digital Currencies (CBDCs) for the domestic context, multi-country cross-border CBDCs pilots are also proliferating. Cross-border CBDCs could make ... [more ▼]

As a growing number of countries explore Central Bank Digital Currencies (CBDCs) for the domestic context, multi-country cross-border CBDCs pilots are also proliferating. Cross-border CBDCs could make cross-border payments faster, cheaper, and simpler. However, for any cross-border CBDC to unlock these benefits and be widely adopted, it must address key concerns, chief among them risks around privacy and transparency of data. This article illustrates how various technical design choices can affect the privacy and transparency of cross-border CBDCs. For instance, architectural choices about the structure of a cross-border CBDC and representational choices about how transactions are encoded in the underlying software can have far-reaching implications for privacy and transparency—both in a domestic context and for cross-border transactions. Many of the cross-border CBDC pilot studies to date have (understandably) adopted the technical designs provided by enterprise distributed ledger platforms. However, some of these designs make tradeoffs regarding privacy, efficiency, and/or security. Whether these tradeoffs are acceptable is a matter of policy, and requires coordination between different regulators and central banks. In view of these implications—and some of the corresponding tensions that arise—we argue that the US and the EU should work together alongside other partners to create the technological and regulatory environment to enable privacy-preserving cross-border CBDCs. The US and the EU should seize the emergence of CBDCs as an opportunity to finally establish a transatlantic privacy framework, and clarify its interplay with the prevention of money laundering and financing of terrorism (AML/CFT/CPF). More broadly, both should harness the clout of their combined financial systems to develop digital asset regulation and standards with a global reach and democratic values. These regulatory developments would not only streamline regulatory guidelines, but they could also directly impact and ease the technical development of a cross-border CBDC. [less ▲]

Data Protection and Consenting Communication Mechanisms: Current Proposals and Challenges

in IEEE eXplore (2022, June 06)

Data Protection and Consenting Communication Mechanisms (DPCCMs) have the potential of becoming one of the most fundamental means of protecting humans’ privacy and agency. However, they are yet to be ... [more ▼]

Data Protection and Consenting Communication Mechanisms (DPCCMs) have the potential of becoming one of the most fundamental means of protecting humans’ privacy and agency. However, they are yet to be improved, adopted and enforced. In this paper, based on the results of a technical document analysis and an expert study, we we identify some of the main technical factors that can be comparison factors between some of the main interdisciplinary challenges of a Human-centric, Accountable, Lawful, and Ethical practice of personal data processing on the Internet and discuss whether the current DPCCMs proposal can contribute towards their resolution. In particular, we discuss the two current open specifications, i.e. the Advanced Data Protection Control (ADPC) and the Global Privacy Control (GPC) based on the identified challenges. [less ▲]

Technical Assessment of Natural-Based and Advanced Technologies for the Removal of Micropollutants from Municipal Wastewater in a Real Scenario

in Proceedings of the 39th IAHR World Congress (Granada, 2022) (2022, June)

MEC-assisted Dynamic Geofencing for 5G-enabled UAV

in IEEE Wireless Communications and Networking Conference (2022, May 16)

5G-enabled UAV-based services have become popular for civilian applications. At the same time, certain no-fly zones will be highly dynamic, e.g. accident areas, large outdoor public events, VIP convoys ... [more ▼]

5G-enabled UAV-based services have become popular for civilian applications. At the same time, certain no-fly zones will be highly dynamic, e.g. accident areas, large outdoor public events, VIP convoys etc. An appropriate geofencing algorithm is required to avoid the no-fly zone in such scenarios. However, it is challenging to execute a high computing process such as a geofencing algorithm for a resource constraint UAV. This paper proposes an architecture and a geofencing algorithm for 5G-enabled UAV using Mobile Edge Computing (MEC). Also, the 5G-enabled UAV must fly within the coverage area during a mission. Hence, there must be an optimal trade-off between 5G coverage and distance to travel to design a new trajectory for a 5G-enabled UAV. To this end, we propose a cost minimization problem to generate a new trajectory while a no-fly zone exists. Specifically, we design a cost function considering 5G coverage and the velocity of the UAV. Then, we propose a geofencing algorithm running at the MEC by adopting the fast marching method (FMM) to generate a new trajectory for the UAV. Finally, a numerical example shows how the proposed geofencing algorithm generates an optimal trajectory for a UAV to avoid a dynamically created no-fly zone while on the mission. [less ▲]

Context, Prioritization, and Unexpectedness: Factors Influencing User Attitudes About Infographic and Comic Consent

in Web Conference Companion Volume (ACM) (2022, April 26)

Being asked to consent to data sharing is a ubiquitous experience in digital services - yet it is very rare to encounter a well designed consent experience. Considering the momentum and importance of a ... [more ▼]

Being asked to consent to data sharing is a ubiquitous experience in digital services - yet it is very rare to encounter a well designed consent experience. Considering the momentum and importance of a European data space where personal information freely and easily flows across organizations, sectors and Member States, solving the long-discussed thorny issue of "how to get consent right" cannot be postponed any further. In this paper, we describe the first findings from a study based on 24 semi-structured interviews investigating participants’ expectations and opinions toward consent in a data sharing scenario with a data trustee. We analyzed various dimensions of a consent form redesigned as a comic and an infographic, including language, information design, content and the writer-reader relationship. The results provide insights into the complexity of elements that should be considered when asking individuals to freely and mindfully disclose their data, especially sensitive information. [less ▲]

D-ViNE: Dynamic Virtual Network Embedding in Non-Terrestrial Networks

in IEEE Wireless Communications and Networking Conference (WCNC) (2022, April 10)

In this paper, we address the virtual network embedding (VNE) problem in non-terrestrial networks (NTNs) enabling dynamic changes in the virtual network function (VNF) deployment to maximize the service ... [more ▼]

In this paper, we address the virtual network embedding (VNE) problem in non-terrestrial networks (NTNs) enabling dynamic changes in the virtual network function (VNF) deployment to maximize the service acceptance rate and service revenue. NTNs such as satellite networks involve highly dynamic topology and limited resources in terms of rate and power. VNE in NTNs is a challenge because a static strategy under-performs when new service requests arrive or the network topology changes unexpectedly due to failures or other events. Existing solutions do not consider the power constraint of satellites and rate limitation of inter-satellite links (ISLs) which are essential parameters for dynamic adjustment of existing VNE strategy in NTNs. In this work, we propose a dynamic VNE algorithm that selects a suitable VNE strategy for new and existing services considering the time-varying network topology. The proposed scheme, D-ViNE, increases the service acceptance ratio by 8.51% compared to the benchmark scheme TS-MAPSCH. [less ▲]

Sanierung erhaltenswürdiger Gebäude in der Südeifel mit regionaltypischen Bruch-steinmauerwerk im Kontext der Innendämmung

in Bauphysiktage Kaiserslautern (2022, March 29), 5

Um eine Innendämmung, welche an Bestandsgebäuden oftmals aufgrund baurechtlicher Einschränkungen die einzige Möglichkeit zur thermischen Ertüchtigung der Fassade darstellt, entsprechend planen und ... [more ▼]

Um eine Innendämmung, welche an Bestandsgebäuden oftmals aufgrund baurechtlicher Einschränkungen die einzige Möglichkeit zur thermischen Ertüchtigung der Fassade darstellt, entsprechend planen und nachweisen zu können, sollten die bauphysikalischen Randbedingungen der Außenfassade sowie des darunterliegenden Bruchsteinmauerwerks messtechnisch erfasst und entsprechend gedeutet werden. Mit Hilfe korrekt abgeschätzter Ein-gangsparameter für notwendige, hygrothermische Berechnungen lassen sich spätere Bauschäden, welche die Folge eines fehlerhaften Sanierungskonzepts wären, weitestgehend ausschließen. Diese Studie befasst sich mit typischen Baustoffen für die „Südeifel“ (Sandstein, Schiefer und Kalkstein). An drei realen Wohngebäuden wurden entsprechende Messungen durchgeführt und deren Einfluss auf die Planung einer Innendämmmaßnahme untersucht. Die Ergebnisse wurden zusammengeführt und dienen als Grundlage für möglichst realitätsnahe, dynamische Simulationen. [less ▲]

Retrofitting of legacy machines in the context of Industrial Internet of Things (IIoT)

in Procedia Computer Science (2022, February 08), 200

In the context of Industry 4.0 (I 4.0), one of the most important aspects is data, followed by the capital required to deploy advanced technologies. However, most Small and Medium Enterprises (SMEs) are ... [more ▼]

In the context of Industry 4.0 (I 4.0), one of the most important aspects is data, followed by the capital required to deploy advanced technologies. However, most Small and Medium Enterprises (SMEs) are neither data ready nor have the capital to upgrade their existing machinery. In SMEs, most of the legacy machines do not have data gathering capabilities. In this scenario, the concept of retrofitting the existing machinery with sensors and building an Industrial Internet of Things (IIoT) is more beneficial than upgrading the equipment to newer machinery. The current research paper proposes a simple architecture on retrofitting a legacy machine with external sensors for data collection and feeding the cloud-based databases for analysis/monitoring purposes. The design and functional aspects of the architecture are then tested in a laboratory environment on a drilling machine with no embedded sensors. Data related to the speed of the drill head and the bore depth are collected using newly retrofitted sensors to validate the proposed architecture. [less ▲]

Highly Vectorized SIKE for AVX-512

in IACR Transactions on Cryptographic Hardware and Embedded Systems (TCHES) (2022, February), 2022(2), 41-68

It is generally accepted that a large-scale quantum computer would be capable to break any public-key cryptosystem used today, thereby posing a serious threat to the security of the Internet’s public-key ... [more ▼]

It is generally accepted that a large-scale quantum computer would be capable to break any public-key cryptosystem used today, thereby posing a serious threat to the security of the Internet’s public-key infrastructure. The US National Institute of Standards and Technology (NIST) addresses this threat with an open process for the standardization of quantum-safe key establishment and signature schemes, which is now in the final phase of the evaluation of candidates. SIKE (an abbreviation of Supersingular Isogeny Key Encapsulation) is one of the alternate candidates under evaluation and distinguishes itself from other candidates due to relatively short key lengths and relatively high computing costs. In this paper, we analyze how the latest generation of Intel’s Advanced Vector Extensions (AVX), in particular AVX-512IFMA, can be used to minimize the latency (resp. maximize the throughput) of the SIKE key encapsulation mechanism when executed on Ice LakeCPUs based on the Sunny Cove microarchitecture. We present various techniques to parallelize and speed up the base/extension field arithmetic, point arithmetic, and isogeny computations performed by SIKE. All these parallel processing techniques are combined in AVXSIKE, a highly optimized implementation of SIKE using Intel AVX-512IFMA instructions. Our experiments indicate that AVXSIKE instantiated with the SIKEp503 parameter set is approximately 1.5 times faster than the to-date best AVX-512IFMA-based SIKE software from the literature. When executed on an Intel Core i3-1005G1 CPU, AVXSIKE outperforms the x64 assembly implementation of SIKE contained in Microsoft’s SIDHv3.4 library by a factor of about 2.5 for key generation and decapsulation, while the encapsulation is even 3.2 times faster. [less ▲]

Yes, I do: Marrying blockchain applications with GDPR

in Proceedings of the 55th Hawaii International Conference on System Sciences (2022, January 04)

Due to blockchains’ intrinsic transparency and immutability, blockchain-based applications are challenged by privacy regulations, such as the EU General Data Protection Regulation. Hence, scaling ... [more ▼]

Due to blockchains’ intrinsic transparency and immutability, blockchain-based applications are challenged by privacy regulations, such as the EU General Data Protection Regulation. Hence, scaling blockchain use cases to production often fails to owe to a lack of compliance with legal constraints. As current research mainly focuses on specific use cases, we aim to offer comprehensive guidance regarding the development of blockchain solutions that comply with privacy regulations. Following the action design research method, we contribute a generic framework and design principles to the research domain. In this context, we also emphasize the need for distinguishing between applications based on blockchains’ data integrity and computational integrity guarantees. [less ▲]

Challenges of protecting confidentiality in social media data and their ethical import

in 2022 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) (2022)

This article discussed the challenges of pseudonymizing unstructured, noisy social media data for cybersecurity research purposes and presents an open- source package developed to pseudonymize personal ... [more ▼]

This article discussed the challenges of pseudonymizing unstructured, noisy social media data for cybersecurity research purposes and presents an open- source package developed to pseudonymize personal and confidential information (i.e., personal names, companies, and locations) contained in such data. Its goal is to facilitate compliance with EU data protection obligations and the upholding of research ethics principles like the respect for the autonomy, privacy and dignity of research participants, the social responsibility of researchers, and scientific integrity. We discuss the limitations of the pseudonymizer package, their ethical import, and the additional security measures that should be adopted to protect the confidentiality of the data. [less ▲]

Combinated Treatment of Wastewater Using Photo-Fenton and Granular Active Carbon Enhancing the Microcontaminants Removall

in Proceedings of the 39th IAHR World Congress (Granada, 2022) (2022)

Efficient and Transferable Adversarial Examples from Bayesian Neural Networks

in The 38th Conference on Uncertainty in Artificial Intelligence (2022)

An established way to improve the transferability of black-box evasion attacks is to craft the adversarial examples on an ensemble-based surrogate to increase diversity. We argue that transferability is ... [more ▼]

An established way to improve the transferability of black-box evasion attacks is to craft the adversarial examples on an ensemble-based surrogate to increase diversity. We argue that transferability is fundamentally related to uncertainty. Based on a state-of-the-art Bayesian Deep Learning technique, we propose a new method to efficiently build a surrogate by sampling approximately from the posterior distribution of neural network weights, which represents the belief about the value of each parameter. Our extensive experiments on ImageNet, CIFAR-10 and MNIST show that our approach improves the success rates of four state-of-the-art attacks significantly (up to 83.2 percentage points), in both intra-architecture and inter-architecture transferability. On ImageNet, our approach can reach 94% of success rate while reducing training computations from 11.6 to 2.4 exaflops, compared to an ensemble of independently trained DNNs. Our vanilla surrogate achieves 87.5% of the time higher transferability than three test-time techniques designed for this purpose. Our work demonstrates that the way to train a surrogate has been overlooked, although it is an important element of transfer-based attacks. We are, therefore, the first to review the effectiveness of several training methods in increasing transferability. We provide new directions to better understand the transferability phenomenon and offer a simple but strong baseline for future work. [less ▲]

Non-Admissibility in abstract argumentation

in Frontiers in Artificial Intelligence and Applications (2022), 353

In this paper, we give an overview of several recent proposals for non-Admissible non-naive semantics for abstract argumentation frameworks. We highlight the similarities and differences between weak ... [more ▼]

In this paper, we give an overview of several recent proposals for non-Admissible non-naive semantics for abstract argumentation frameworks. We highlight the similarities and differences between weak admissibility-based approaches and undecidedness-blocking approaches using examples and principles as well as a study of their computational complexity. We introduce a kind of strengthened undecidedness-blocking semantics combining some of the distinctive behaviours of weak admissibility-based semantics with the lower complexity of undecidedness-blocking approaches. We call it loop semantics, because in our new semantics, an argument can only be undecided if it is part of a loop of undecided arguments. Our paper shows how a principle-based approach and a complexity-based approach can be used in tandem to further develop the foundations of formal argumentation. [less ▲]

MULTI LABEL IMAGE CLASSIFICATION USING ADAPTIVE GRAPH CONVOLUTIONAL NETWORKS (ML-AGCN)

in IEEE International Conference on Image Processing (2022)

In this paper, a novel graph-based approach for multi-label image classification called Multi-Label Adaptive Graph Convolutional Network (ML-AGCN) is introduced. Graph-based methods have shown great ... [more ▼]

In this paper, a novel graph-based approach for multi-label image classification called Multi-Label Adaptive Graph Convolutional Network (ML-AGCN) is introduced. Graph-based methods have shown great potential in the field of multi-label classification. However, these approaches heuristically fix the graph topology for modeling label dependencies, which might be not optimal. To handle that, we propose to learn the topology in an end-to-end manner. Specifically, we incorporate an attention-based mechanism for estimating the pairwise importance between graph nodes and a similarity-based mechanism for conserving the feature similarity between different nodes. This offers a more flexible way for adaptively modeling the graph. Experimental results are reported on two well-known datasets, namely, MS-COCO and VG-500. Results show that ML-AGCN outperforms state-of-the-art methods while reducing the number of model parameters. [less ▲]

Value-based practical reasoning: Modal Logic + Argumentation

in Frontiers in Artificial Intelligence and Applications (2022), 353

Autonomous agents are supposed to be able to finish tasks or achieve goals that are assigned by their users through performing a sequence of actions. Since there might exist multiple plans that an agent ... [more ▼]

Autonomous agents are supposed to be able to finish tasks or achieve goals that are assigned by their users through performing a sequence of actions. Since there might exist multiple plans that an agent can follow and each plan might promote or demote different values along each action, the agent should be able to resolve the conflicts between them and evaluate which plan he should follow. In this paper, we develop a logic-based framework that combines modal logic and argumentation for value-based practical reasoning with plans. Modal logic is used as a technique to represent and verify whether a plan with its local properties of value promotion or demotion can be followed to achieve an agent's goal. We then propose an argumentation-based approach that allows an agent to reason about his plans in the form of supporting or objecting to a plan using the verification results. [less ▲]

Case-Based Reasoning via Comparing the Strength Order of Features

in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2022), 13283 LNAI

Case-based reasoning (CBR) is broadly speaking a method of giving a verdict/decision on a new case query by comparing it with verdicts/decisions of known similar cases. Similarity of cases is determined ... [more ▼]

Case-based reasoning (CBR) is broadly speaking a method of giving a verdict/decision on a new case query by comparing it with verdicts/decisions of known similar cases. Similarity of cases is determined either by best distance of the query case from the known cases and recently also using argumentation. The approach of this paper is not to rely on similarity or argumentation, but to use the entire set of known cases and their known verdicts to define the relative strength and importance of all the features involved in these cases. We then decide the verdict for the new case based on the strength of the features appearing in it. [less ▲]

What if data protection embraced foresight and speculative design?

in DRS2022: Bilbao (2022)

Due to rapid technological advancements and the growing “datafication” of our societies, individuals’ privacy constitutes an increasingly explored speculative space for regulators, researchers ... [more ▼]

Due to rapid technological advancements and the growing “datafication” of our societies, individuals’ privacy constitutes an increasingly explored speculative space for regulators, researchers, practitioners, designers and artists. This article reports two experiences at a national and an international data protection authority (i.e., the Commission Nationale de l'Informatique et des Libertés - CNIL - and the European Data Protection Supervisor - EDPS - respectively), where foresight methods and speculative design are employed in policy-making with the goal of anticipating technological trends, their implications for society and their impact on regulations, as well as the effects of existing and upcoming laws on emerging technologies. Such initiatives can enhance strategic proactive abilities, raise public awareness of privacy issues and engender a participatory approach to the design of policies. They can also inspire the research, education and practice of legal design. [less ▲]

Transforming IoT Data Preprocessing: A Holistic, Normalized and Distributed Approach

in The Fifth International Workshop on Data: Acquisition To Analysis (2022)

Data preprocessing is an integral part of Artificial Intelligence (AI) pipelines. It transforms raw data into input data that fulfill algorithmic criteria and improve prediction accuracy. As the adoption ... [more ▼]

Data preprocessing is an integral part of Artificial Intelligence (AI) pipelines. It transforms raw data into input data that fulfill algorithmic criteria and improve prediction accuracy. As the adoption of Internet of Things (IoT) gains more momentum, the data volume generated from the edge is exponentially increasing that far exceeds any expansion of infrastructure. Social responsibilities and regulations (e.g., GDPR) must also be adhered when handling IoT data. In addition, we are currently witnessing a shift towards distributing AI to the edge. The aforementioned reasons render the distribution of data preprocessing to the edge an urgent requirement. In this paper, we introduce a modern data preprocessing framework that consists of two main parts. Part1 is a design tool that reduces the complexity and costs of the data preprocessing phase for AI via generalization and normalization. The design tool is a standard template that maps specific techniques into abstract categories and highlights dependencies between them. In addition, it presents a holistic notion of data preprocessing that is not limited to data cleaning. The second part is an IoT tool that adopts the edge-cloud collaboration model to progressively improve the quality of the data. It includes a synchronization mechanism that ensures adaptation to changes in data characteristics and a coordination mechanism that ensures correct and complete execution of preprocessing plans between the cloud and the edge. The paper includes an empirical analysis of the framework using a developed prototype and an automotive use-case. Our results demonstrate reductions in resource consumption (e.g., energy, bandwidth) while maintaining the value and integrity of the data. [less ▲]

User Grouping for Non-Coherent DPSK Massive SIMO with Heterogeneous Propagation Conditions

in 2021 Global Congress on Electrical Engineering (GC-ElecEng) (2021, December)

Cookie Banners, What’s the Purpose? Analyzing Cookie Banner Text Through a Legal Lens

in Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security (CCS '21) (2021, November 15)

A cookie banner pops up when a user visits a website for the first time, requesting consent to the use of cookies and other trackers for a variety of purposes. Unlike prior work that has focused on ... [more ▼]

A cookie banner pops up when a user visits a website for the first time, requesting consent to the use of cookies and other trackers for a variety of purposes. Unlike prior work that has focused on evaluating the user interface (UI) design of cookie banners, this paper presents an in-depth analysis of what cookie banners say to users to get their consent. We took an interdisciplinary approach to determining what cookie banners should say. Following the legal requirements of the ePrivacy Directive (ePD) and the General Data Protection Regulation (GDPR), we manually annotated around 400 cookie banners presented on the most popular English-speaking websites visited by users residing in the EU. We focused on analyzing the purposes of cookie banners and how these purposes were expressed (e.g., any misleading or vague language, any use of jargon). We found that 89% of cookie banners violated applicable laws. In particular, 61% of banners violated the purpose specificity requirement by mentioning vague purposes, including “user experience enhancement”. Further, 30% of banners used positive framing, breaching the freely given and informed consent requirements. Based on these findings, we provide recommendations that regulators can find useful. We also describe future research directions. [less ▲]

Global land dampness characterization using reflectometry by students (GOLDCREST): mission and CubeSat design

in Proceedings of the 12th European CubeSat symposium (2021, November 15)

Longitudinal Relations Between Views on Aging and Perceived Stress: Evidence for Mutual Associations

in Innovation in Aging (2021, November), 5(Supplement_1), 287-287

We investigated the reciprocal longitudinal relation between perceived stress and three established domains of views on aging (VoA): (1) subjective age; (2) attitude toward own aging [ATOA]; and (3) aging ... [more ▼]

We investigated the reciprocal longitudinal relation between perceived stress and three established domains of views on aging (VoA): (1) subjective age; (2) attitude toward own aging [ATOA]; and (3) aging-related cognitions including social loss, physical decline, and continuous growth. We also examined the potentially moderating role of chronological age. Data of the German Ageing Survey, comprising two measurement occasions (2014 and 2017) and a sample of 4,588 individuals aged between 40 and 95 years, were analyzed. Controlling for socio-demographic and health-related indicators, cross-lagged models indicated mutual longitudinal relations between VoA and stress. Whether the pathway from stress to VoA or the opposite pathway was stronger varied depending on the VoA considered. With increasing age, most VoA domains were less strongly associated with subsequent perceived stress. Our findings suggest that less favorable VoA predict higher perceived subsequent stress, but they are also preceded and predicted by higher levels of perceived stress. [less ▲]

Exploring the Relationship Between Subjective Age and Worry for Older Adults in Times of a Pandemic

in Innovation in Aging (2021, November), 5(Supplement_1), 593-593

Given the role of age as a risk factor in the covid pandemic, we examined the longitudinal cross-lagged relationship between subjective age and Covid-related worry, and possible moderators of this ... [more ▼]

Given the role of age as a risk factor in the covid pandemic, we examined the longitudinal cross-lagged relationship between subjective age and Covid-related worry, and possible moderators of this relationship. Data were obtained at two-time points (June and October 2020) by a phone/online survey, from N = 611 older participants (Mage = 69.92 years). Participants felt on average 10 and 8.5 years younger than their chronological ages at the two-time points, respectively. Younger subjective age at T1 increased the level of worry at T2 irrespective of age, perceived control and subjective health. Higher worry increased subjective age at T2, but only for those with worse subjective health. Our results show that subjective age and Covid-related worry interact over time. This relation needs to be explored further in order to understand the relationship between subjective age and well-being especially, but not only in the pandemic context. [less ▲]

Leveraging Temporal Information for 3D Trajectory Estimation of Space Objects

in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops (2021, October)

Evaluation of TPMS Signal Propagation in a Heavy Commercial Vehicle Environement

in 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall) proceedings (2021, September 27)

Cholesteric Spherical Reflectors as Physical Unclonable Identifiers in Anti-counterfeiting

in Journal of the Association for Computing Machinery (2021, August 17), 16

GPU-Accelerated Mahalanobis-Average Hierarchical Clustering Analysis

in Lecture Notes in Computer Science (2021, August), 12820

Hierarchical clustering is a common tool for simplification, exploration, and analysis of datasets in many areas of research. For data originating in flow cytometry, a specific variant of agglomerative ... [more ▼]

Hierarchical clustering is a common tool for simplification, exploration, and analysis of datasets in many areas of research. For data originating in flow cytometry, a specific variant of agglomerative clustering based Mahalanobis-average linkage has been shown to produce results better than the common linkages. However, the high complexity of computing the distance limits the applicability of the algorithm to datasets obtained from current equipment. We propose an optimized, GPU-accelerated open-source implementation of the Mahalanobis-average hierarchical clustering that improves the algorithm performance by over two orders of magnitude, thus allowing it to scale to the large datasets. We provide a detailed analysis of the optimizations and collected experimental results that are also portable to other hierarchical clustering algorithms; and demonstrate the use on realistic high-dimensional datasets. [less ▲]

Unlinkable Updatable Hiding Databases and Privacy-Preserving Loyalty Programs

in Proceedings on Privacy Enhancing Technologies (2021, July), 2021(3), 95-121

Loyalty programs allow vendors to profile buyers based on their purchase histories, which can reveal privacy sensitive information. Existing privacy friendly loyalty programs force buyers to choose ... [more ▼]

Loyalty programs allow vendors to profile buyers based on their purchase histories, which can reveal privacy sensitive information. Existing privacy friendly loyalty programs force buyers to choose whether their purchases are linkable. Moreover, vendors receive more purchase data than required for the sake of profiling. We propose a privacy-preserving loyalty program where purchases are always unlinkable, yet a vendor can profile a buyer based on her purchase history, which remains hidden from the vendor. Our protocol is based on a new building block, an unlinkable updatable hiding database (HD), which we define and construct. HD allows the vendor to initialize and update databases stored by buyers that contain their purchase histories and their accumulated loyalty points. Updates are unlinkable and, at each update, the database is hidden from the vendor. Buyers can neither modify the database nor use old versions of it. Our construction for HD is practical for large databases. [less ▲]

Comparing effectiveness of paper based and Augmented Reality instructions for manual assembly and training tasks

in Proceedings of the 11th Conference on Learning Factories (2021, June 24)

Augmented Reality (AR) systems have seen a rapid adaptation in both training and in virtual assembly instructions. AR systems assist the operator by enhancing user perception of reality, reducing the ... [more ▼]

Augmented Reality (AR) systems have seen a rapid adaptation in both training and in virtual assembly instructions. AR systems assist the operator by enhancing user perception of reality, reducing the defects, and lead-time. However, there is a significant lack in the existing literature to compare AR systems and conventional work instructions. The aim of this research is to provide an empirical evidence of comparing task completion time, number of errors, workload index and system usability of AR and conventional paper-based work instructions. For this purpose, we designed an experiment where participants use paper based instructions and AR instructions to assemble a planetary gearbox. The task was assessed using NASA-TLX and System Usability Scale (SUS) tests, which allowed further analysis using descriptive statistics. Moreover, the qualitative interview at the end of the experiment gave more insights about participant’s overall experience. [less ▲]

Numerical study on the revised rules for minimum degree of shear connection in propped and unpropped steel-concrete composite beams

in Proceedings of ICMS (2021, June 16)

The work presents a numerical study that focuses on steel-concrete composite beams using ductile headed stud shear connectors. The objective is to check the suitability of the proposed revised EN 1994-1-1 ... [more ▼]

The work presents a numerical study that focuses on steel-concrete composite beams using ductile headed stud shear connectors. The objective is to check the suitability of the proposed revised EN 1994-1-1 rules for the minimum degree of shear connection. Therefore, a non-linear 3D finite element model of simply supported composite beams was developed and validated against the analytical values of the plastic bending design resistance. The parametric study consists of 10 configurations where the relative slip at slab-beam interface was carefully investigated at different degrees of shear connection and propping conditions. Specifically, the slip at the minimum degree of shear connection shall not exceed the limit of 6 mm defined as the characteristic slip of ductile connector according to EN 1994-1-1. The results showed that the revised rules for unpropped beams delivers conservative results whereas one case with propped conditions exhibit a maximum slip significantly higher than 6 mm. [less ▲]

Effective resistance of demountable shear connectors

in Proceedings of ICMS (2021, June 16)

Steel-concrete composite construction is structurally efficient but is impossible to dismount where the floor slab is permanently connected to the steel beams through traditional welded studs. This ... [more ▼]

Steel-concrete composite construction is structurally efficient but is impossible to dismount where the floor slab is permanently connected to the steel beams through traditional welded studs. This contradicts the reuse and reduce aspects of the circular economy concept which has recently been introduced to the construction industry. Within the RFCS REDUCE project, several solutions have been proposed. Demountability of the composite beams using the proposed new shear connectors has been successfully demonstrated by push-out tests and full-scale beam tests. Both experiments and numerical simulations showed that the composite beams can develop plasticity even the demountable shear connectors in solid concrete slabs failed in a brittle way. To extend the scope of Eurocode 4 and avoid uneconomic elastic design, effective shear resistance of the demountable shear connectors was defined by using a newly developed algorithm, for the calculation of the plastic moment capacity of composite sections with partial shear connection. [less ▲]

Observability based data-fusion cascading filtering for urban network flow estimation

in IEEE Xplore (2021, June)