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See detailReducing Efficiency of Connectivity-Splitting Attack on Newscast via Limited Gossip
Muszynski, Jakub UL; Varrette, Sébastien UL; Bouvry, Pascal UL

in Proc. of the 19th European Event on Bio-Inspired Computation, EvoCOMNET 2016 (2016, March)

Newscast is aPeer-to-Peer, nature-inspired gossip-based data exchange protocol used for information dissemination and membership management in large-scale, agent-based distributed systems. The model ... [more ▼]

Newscast is aPeer-to-Peer, nature-inspired gossip-based data exchange protocol used for information dissemination and membership management in large-scale, agent-based distributed systems. The model follows a probabilistic scheme able to keep a self-organised, small-world equilibrium featuring a complex, spatially structured and dynamically changing environment. Newscast gained popularity since the early 2000s thanks to its inherent resilience to node volatility as the protocol exhibits strong self-healing properties. However, the original design proved to be surprisingly fragile in a byzantine environment subjected to cheating faults. Indeed, a set of recent studies emphasized the hard-wired vulnerabilities of the protocol, leading to an efficient implementation of a malicious client, where a few naive cheaters are able to break the network connectivity in a very short time. Extending these previous works, we propose in this paper a modification of the seminal protocol with embedded counter-measures, improving the resilience of the scheme against malicious acts without significantly affecting the original Newscast’s proper- ties nor its inherent performance. Concrete experiments were performed to support these claims, using a framework implementing all the solutions discussed in this work. [less ▲]

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See detailDistributed Cellular Evolutionary Algorithms in a Byzantine Environment
Muszynski, Jakub UL; Varrette, Sébastien UL; Dorronsorro, Bernabé et al

in Proc. of the 18th Intl. Workshop on Nature Inspired Distributed Computing (NIDISC 2015), part of the 29th IEEE/ACM Intl. Parallel and Distributed Processing Symposium (IPDPS 2015) (2015, May)

Distributed parallel computing platforms contribute for a large part to some of the most powerful computers. Such architec- tures are typically based on accelerators (General Purpose com- puting on ... [more ▼]

Distributed parallel computing platforms contribute for a large part to some of the most powerful computers. Such architec- tures are typically based on accelerators (General Purpose com- puting on Graphics Processing Units, Many Integrated Cores e.g Xeon Phi co-processors) and/or a large number of interconnected computing nodes. Obviously, they raise new challenges, typically in terms of scalability, robustness, adaptability and security. At the advent of the quest for Ultrascale Computing Systems, this paper addresses the issue of fault tolerance toward Byzantine failures overs such platforms. Indeed, the inherent unpredictable nature of these errors render their detection, not speaking of their correction, hard or even impossible to perform at large-scale. At this level, Algorithm-Based Fault Tolerance (ABFT) techniques where the fault tolerance scheme is tailored to the algorithm performed, seems the most promising approaches to deal with such failures. In this context, Evolutionary Algorithms (EAs), especially panmictic global parallel EAs, exhibit a remarkable resilience against byzantine failures modeled as cheating faults as demonstrated either empirically or theoretically in previous studies [1], [2]. In this paper, we extend this analysis to the case of distributed EAs based on the cellular model leading to distributed Cellular Evolutionary Algorithms (dCEAs). Our empirical study over a set or reference optimization problem confirm the ABFT nature of dCEAs. To our knowledge, this is the first study of dCEAs under the perspective of cheating issues and crash faults in a domain of distributed computations, thus opening new insights and perspectives for the design of competitive ultra-scale system based on evolutionary programming models. [less ▲]

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See detailCheating-Tolerance of Parallel and Distributed Evolutionary Algorithms in Desktop Grids and Volunteer Computing Systems
Muszynski, Jakub UL

Doctoral thesis (2015)

This thesis analyses the fault-tolerant nature of Evolutionary Algorithms (EAs) executed in a distributed environment which is subjected to malicious acts. Such actions are a common problem in Desktop ... [more ▼]

This thesis analyses the fault-tolerant nature of Evolutionary Algorithms (EAs) executed in a distributed environment which is subjected to malicious acts. Such actions are a common problem in Desktop Grids and Volunteer Computing Systems (DGVCS’s) utilising idle resources shared by volunteers. Due to the vast computational and storage capabilities provided at a low cost, many large-scale research projects are carried out using such set-ups. However, this advantage is obtained at the expense of a challenging, error prone, heteroge neous and volatile environment of execution. In the volunteer-based systems, such as BOINC, the incentives offered to the contributors attract also malicious users, commonly called cheaters. A cheater typically seeks to obtain the rewards with little or no contribution at all. Additionally, this group may also include "crackers" or "black hat hackers" - users motivated by nothing more than a pure satisfaction from violating computer security. In this study we use and formalise cheating faults - a model for the behaviours described above, which are a subtype of byzantine (arbitrary) faults. They are mainly characterised by the alteration of outputs produced by some or all tasks forming a distributed execution. The approach differs from the arbitrary faults in its implementation, as usually they are introduced intentionally and from within the boundaries of a system. The innate fault resilience of EAs has been previously observed in the literature. However, this PhD manuscript offers the first, formal analysis of the impact of cheating faults in this area of optimisation techniques. In particular, the following contributions are proposed: - An in-depth formal analysis of the cheating-tolerance of parallel Evolutionary Algorithms (EAs), including proofs of convergence or non-convergence towards valid solutions in the presence of malicious acts. A step-wise approach is used, focusing firstly on the most simple variant of an EA that is still of theoretical and practical interest, i.e. a (1 + 1) EA. Then the results are extended to regular (population-based) EAs. The analysis shows that the selection mechanism is crucial to achieve convergence of EAs executed in malicious environments. - The extension of the study to cheating-resilience of spatially-structured Evolutionary Algorithms (EAs) and gossip protocols. More precisely, we analyse Evolvable Agent Model (EvAg) relying on Newscast protocol to define neighbourhoods in the evolution and the communication layers. There, we provide the necessary conditions for convergence of the algorithm in a hostile environment and we show that the evolutionary process may be affected only by tampering with the connectivity between the computing resources. After that, we design an effective connectivity-splitting attack which is able to defeat the protocol using very few naive cheaters. Finally, we provide a set of countermeasures which ultimately lead to a more robust solution. These results have been published in several international, peer-reviewed venues and well recognized international journals. By the variety of problems addressed by EAs, this study will hopefully promote their usage in the future developments around distributed computing platforms such as Desktop Grids and Volunteer Computing Systems or Cloud systems where the resources cannot be fully trusted. [less ▲]

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See detailResilience within Ultrascale Computing System: Challenges and Opportunities from Nesus Project
Bouvry, Pascal UL; Mayer, R.; Muszynski, Jakub UL et al

in Supercomputing Frontiers and Innovations (2015), 2(2), 46--63

Ultrascale computing is a new computing paradigm that comes naturally from the necessity of computing systems that should be able to handle massive data in possibly very large scale distributed systems ... [more ▼]

Ultrascale computing is a new computing paradigm that comes naturally from the necessity of computing systems that should be able to handle massive data in possibly very large scale distributed systems, enabling new forms of applications that can serve a very large amount of users and in a timely manner that we have never experienced before. However, besides the benefits, ultrascale computing systems do not come without challenges. One of the challenges is the resilience of ultrascale computing systems. Although resilience is already an established field in system science and many methodologies and approaches are available to deal with it, the unprecedented scales of computing, of the massive data to be managed, new network technologies, and drastically new forms of massive scale applications bring new challenges that need to be addressed. This paper reviews the challenges and approaches of resilience in ultrascale computing systems from multiple perspectives involving and addressing the resilience aspects of hardware-software co-design for ultrascale systems, resilience against (security) attacks, new approaches and methodologies to resilience in ultrascale systems, applications and case studies. [less ▲]

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See detailExploiting the Hard-wired Vulnerabilities of Newscast via Connectivity-splitting Attack
Muszynski, Jakub UL; Varrette, Sébastien UL; Jimenez Laredo, Juan Luis UL et al

in Proc. of the IEEE Intl. Conf. on Network and System Security (NSS 2014) (2014, October)

Newscast is a model for information dissemination and mem- bership management in large-scale, agent-based distributed systems. It deploys a simple, peer-to-peer data exchange protocol. The Newscast pro ... [more ▼]

Newscast is a model for information dissemination and mem- bership management in large-scale, agent-based distributed systems. It deploys a simple, peer-to-peer data exchange protocol. The Newscast pro- tocol forms an overlay network and keeps it connected by means of an epidemic algorithm, thus featuring a complex, spatially structured, and dynamically changing environment. It has recently become very popu- lar due to its inherent resilience to node volatility as it exhibits strong self-healing properties. In this paper, we analyze the robustness of the Newscast model when executed in a distributed environment subjected to malicious acts. More precisely, we evaluate the resilience of Newscast against cheating faults and demonstrate that even a few naive cheaters are able to defeat the protocol by breaking the network connectivity. Concrete experiments are performed using a framework that implements both the protocol and the cheating model considered in this work. [less ▲]

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See detailAnalysis of the Data Flow in the Newscast Protocol for Possible Vulnerabilities
Muszynski, Jakub UL; Varrette, Sébastien UL; Laredo, J. L. Jiménez et al

in Proc. of Intl. Conf. on Cryptography and Security System (CSS'14) (2014, September)

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See detailExpected Running Time of Parallel Evolutionary Algorithms on Unimodal Pseudo-Boolean Functions over Small-World Networks
Muszynski, Jakub UL; Varrette, Sébastien UL; Bouvry, Pascal UL

in Proc. of the IEEE Congress on Evolutionary Computation (CEC'2013) (2013)

This paper proposes a theoretical and experimental analysis of the expected running time for an elitist parallel Evolutionary Algorithm (pEA) based on an island model executed over small-world networks ... [more ▼]

This paper proposes a theoretical and experimental analysis of the expected running time for an elitist parallel Evolutionary Algorithm (pEA) based on an island model executed over small-world networks. Our study assumes the resolution of optimization problems based on unimodal pseudo-boolean funtions. In particular, for such function with d values, we improve the previous asymptotic upper bound for the expected parallel running time from O(d√n) to O(d log n). This study is a first step towards the analysis of influence of more complex network topologies (like random graphs created by P2P networks) on the runtime of pEAs. A concrete implementation of the analysed algorithm have been performed on top of the ParadisEO framework and run on the HPC platform of the University of Luxembourg (UL). Our experiments confirm the expected speed- up demonstrated in this article and prove the benefit that pEA can gain from a small-world network topology. [less ▲]

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See detailHash function generation by means of Gene Expression Programming
Varrette, Sébastien UL; Muszynski, Jakub UL; Bouvry, Pascal UL

in Intl. Conf. on Cryptography and Security System (CSS’12) (2012, September), XII(3), 37-53

Cryptographic hash functions are fundamental primitives in modern cryptography and have many security applications (data integrity checking, cryptographic protocols, digital signatures, pseudo random ... [more ▼]

Cryptographic hash functions are fundamental primitives in modern cryptography and have many security applications (data integrity checking, cryptographic protocols, digital signatures, pseudo random number generators etc.). At the same time novel hash functions are designed (for instance in the framework of the SHA-3 contest organized by the National Institute of Standards and Technology (NIST)), the cryptanalysts exhibit a set of statistical metrics (propagation criterion, frequency analysis etc.) able to assert the quality of new proposals. Also, rules to design "good" hash functions are now known and are followed in every reasonable proposal of a new hash scheme. This article investigates the ways to build on this experiment and those metrics to generate automatically compression functions by means of Evolutionary Algorithms (EAs). Such functions are at the heart of the construction of iterative hash schemes and it is therefore crucial for them to hold good properties. Actually, the idea to use nature-inspired heuristics for the design of such cryptographic primitives is not new: this approach has been successfully applied in several previous works, typically using the Genetic Programming (GP) heuristic [1]. Here, we exploit a hybrid meta-heuristic for the evolutionary process called Gene Expression Programming (GEP) [2] that appeared far more e?cient computationally speaking compared to the GP paradigm used in the previous papers. In this context, the GEPHashSearch framework is presented. As it is still a work in progress, this article focuses on the design aspects of this framework (individuals de?nitions, ?tness objectives etc.) rather than on complete implementation details and validation results. Note that we propose to tackle the generation of compression functions as a multi-objective optimization problem in order to identify the Pareto front i.e. the set of non-dominated functions over the four ?tness criteria considered. If this goal is not yet reached, the ?rst experimental results in a mono-objective context are promising and open the perspective of fruitful contributions to the cryptographic community [less ▲]

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See detailConvergence Analysis of Evolutionary Algorithms in the Presence of Crash-Faults and Cheaters
Muszynski, Jakub UL; Varrette, Sébastien UL; Bouvry, Pascal UL et al

in Computers & Mathematics with Applications (2012), 64(12), 3805-3819

This paper analyzes the fault-tolerance nature of Evolutionary Algorithms (EAs) when executed in a distributed environment subjected to malicious acts. More precisely, the inherent resilience of EAs ... [more ▼]

This paper analyzes the fault-tolerance nature of Evolutionary Algorithms (EAs) when executed in a distributed environment subjected to malicious acts. More precisely, the inherent resilience of EAs against two types of failures is considered: (1) crash faults, typically due to resource volatility which lead to data loss and part of the computation loss; (2) cheating faults, a far more complex kind of fault that can be modeled as the alteration of output values produced by some or all tasks of the program being executed. This last type of failure is due to the presence of cheaters on the computing platform. Most often in Global Computing (GC) systems such as BOINC, cheaters are attracted by the various incentives provided to stimulate the volunteers to share their computing resources: cheaters typically seek to obtain rewards with little or no contribution to the system. In this paper, the Algorithm-Based Fault Tolerance (ABFT) aspects of EAs against the above types of faults is characterized. Whereas the inherent resilience of EAs has been previously observed in the literature, for the first time, a formal analysis of the impact of the considered faults over the executed EA including a proof of convergence is proposed in this article. By the variety of problems addressed by EAs, this study will hopefully promote their usage in the future developments around distributed computing platform such as Desktop Grids and Volunteer Computing Systems or Cloud systems where the resources cannot be fully trusted. [less ▲]

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See detailCheating impact on distributed Evolutionary Algorithms over BOINC computations.
Varrette, Sébastien UL; Muszynski, Jakub UL; Bouvry, Pascal UL

in n Proc. of the 19th Intl. conference on Security and Intelligent Information Systems (SIIS 2011) (2011)

Detailed reference viewed: 51 (2 UL)