Visible to the public Swarm Intelligence Security 2015

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Swarm Intelligence Security


Swarm Intelligence is a concept using the metaphor of insect colonies to describe decentralized, self-organized systems. The method is often used in artificial intelligence, and there are about a dozen variants ranging from ant colony optimization to stochastic diffusion. For cybersecurity, these systems have significant value both offensively and defensively. For the Science of Security, swarm intelligence relates to composability and compositionality. The research cited here includes focus on drones, botnets and malware, intrusion detection, cryptanalysis, and security risk analysis. The works cited below were published in 2015.  

Jongho Won, Seung-Hyun Seo, Elisa Bertino; “A Secure Communication Protocol for Drones and Smart Objects,” ASIA CCS '15, Proceedings of the 10th ACM Symposium on Information, Computer and Communications Security, April 2015, Pages 249–260. doi:10.1145/2714576.2714616
Abstract: In many envisioned drone-based applications, drones will communicate with many different smart objects, such as sensors and embedded devices. Securing such communications requires an effective and efficient encryption key establishment protocol. However, the design of such a protocol must take into account constrained resources of smart objects and the mobility of drones. In this paper, a secure communication protocol between drones and smart objects is presented. To support the required security functions, such as authenticated key agreement, non-repudiation, and user revocation, we propose an efficient Certificateless Signcryption Tag Key Encapsulation Mechanism (eCLSC-TKEM). eCLSC-TKEM reduces the time required to establish a shared key between a drone and a smart object by minimizing the computational overhead at the smart object. Also, our protocol improves drone’s efficiency by utilizing dual channels which allows many smart objects to concurrently execute eCLSC-TKEM. We evaluate our protocol on commercially available devices, namely AR.Drone2.0 and TelosB, by using a parking management testbed. Our experimental results show that our protocol is much more efficient than other protocols.
Keywords: certificateless signcryption, drone communications (ID#: 15-7041)


Sam Palmer, Denise Gorse, Ema Muk-Pavic; “Neural Networks and Particle Swarm Optimization for Function Approximation in Tri-SWACH Hull Design,” EANN '15, Proceedings of the 16th International Conference on Engineering Applications of Neural Networks (INNS), September 2015, Article No. 8. doi:10.1145/2797143.2797168
Abstract: Tri-SWACH is a novel multihull ship design that is well suited to a wide range of industrial, commercial, and military applications, but which because of its novelty has few experimental studies on which to base further development work. Using a new form of particle swarm optimization that incorporates a strong element of stochastic search, Breeding PSO, it is shown it is possible to use multilayer nets to predict resistance functions for Tri-SWACH hullforms, including one function, the Residual Resistance Coefficient, which was found intractable with previously explored neural network training methods.
Keywords: Particle swarm optimization, Tri-SWACH, function approximation, hullform design, multihull resistance (ID#: 15-7042)


George Eleftherakis, Milos Kostic, Konstantinos Rousis, Anca Vasilescu; “Stigmergy Inspired Approach to Enable Agent Communication in Emergency Scenarios,” BCI '15, Proceedings of the 7th Balkan Conference on Informatics Conference, September 2015, Article No. 22.  doi:10.1145/2801081.2801119
Abstract: Coordination is one of the main challenges in emergency management. Recent disasters demonstrated that there is a need for communication mechanisms which do not rely on centralized systems and infrastructure. This paper investigates alternative communication models in emergency scenarios and provides an implementation that enables communication between different actors (machine and human) through the environment. First, it analyses the dynamics of emergency scenarios with special focus on coordination and communication challenges. Multi-agent systems are a promising solution for this type of situations and in this work are used in a theoretical framework for developing a bio-inspired communication model. Following this approach, a proof of concept solution has been implemented, named the Alternative Communication Framework. This framework utilises a wide range of alternative media in order to facilitate an indirect, stigmergic, communication. Finally, the real life applicability of this model is evaluated with the use of a realistic scenario which was designed in order to demonstrate the core concepts involved in this work.
Keywords: decentralized intelligence, emergence, emergency scenarios, multi-agent systems, stigmergy (ID#: 15-7043)


Yu Liu, Wei-Neng Chen, Xiao-min Hu, Jun Zhang; “An Ant Colony Optimizing Algorithm Based on Scheduling Preference for Maximizing Working Time of WSN,” GECCO '15, Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, July 2015, Pages 41–48. doi:10.1145/2739480.2754671
Abstract: With the proliferation of wireless sensor networks (WSN), the issues about how to schedule all the sensors in order to maximize the system’s working time have been in the spotlight. Inspired by the promising performance of ant colony optimization (ACO) in solving combinational optimization problem, we attempt to apply it in prolonging the life time of WSN. In this paper, we propose an improved version of ACO algorithm to get solutions about selecting exact sensors to accomplish the covering task in a reasonable way to preserve more energy to maintain longer active time. The methodology is based on maximizing the disjoint subsets of sensors, in other words, in every time interval, choosing which sensor to sustain active state must be rational in certain extent. With the aid of pheromone and heuristic information, a better solution can be constructed in which pheromone denotes the previous scheduling experience, while heuristic information reflects the desirable device assignment. Orderly sensor selection is designed to construct an advisable subset for coverage task. The proposed method has been successfully applied in solving limited energy assignment problem no matter in homogenous or heterogeneous WSNs. Simulation experiments have shown it has a good performance in addressing relevant issues.
Keywords: ant colony optimization algorithm, maximize working time, schedule, wireless sensors network (WSM) (ID#: 15-7044)


J. Amudhavel, S. Kumarakrishnan, H. Gomathy, A. Jayabharathi, M. Malarvizhi, K. Prem Kumar; “An Scalable Bandwidth Reduction and Optimization in Smart Phone Ad hoc Network (SPAN) Using Krill Herd Algorithm,” ICARCSET '15, Proceedings of the 2015 International Conference on Advanced Research in Computer Science Engineering & Technology (ICARCSET 2015), March 2015, Article No. 26. doi:10.1145/2743065.2743091
Abstract: In this paper a Krill Herd Algorithm is applied in Smart Phone Ad Hoc Network to solve the challenges present in SPAN. The main problem faced in Smart Phone Ad Hoc Network is Synchronization, Bandwidth, Power conservation. Smart Phone Ad hoc Networks [24] (SPANs) influence the existing hardware (primarily Bluetooth and Wi-Fi) in commercially available smart phones to create peer-to-peer networks without depend on cellular carrier networks, wireless access points, or traditional network infrastructure. It differs from traditional hub and spoke networks in that they support multi-hop relays. The issues in smart phone ad hoc network is resolved using biologically-inspired algorithm namely krill herd for solving optimization tasks. The best solution will be given by intensification process by krill herd algorithm. By using intensification process bandwidth in smart phone ad hoc network gets reduced. Power consumption is also a major issue in smart phone which affects the efficiency. By using intensification process the less power is consumed. Thus the increased bandwidth and power consumption in smart phone ad hoc network get reduced.
Keywords: Krill herd, issues in smart phone ad hoc network, optimization of smart phone (ID#: 15-7045)


D. Jude Hemanth, J. Anitha, Valentina Emilia Balas; “Performance Improved Hybrid Intelligent System for Medical Image Classification,” BCI '15, Proceedings of the 7th Balkan Conference on Informatics Conference, September 2015, Article No. 8. doi:10.1145/2801081.2801095
Abstract: Kohonen neural networks are one of the commonly used Artificial Neural Network (ANN) for medical imaging applications. In spite of the numerous advantages, there are some demerits associated with Kohonen neural network which are mostly unexplored. Being an unsupervised neural network, they are mostly dependent on iterations which ultimately affect the accuracy of the overall system. Any iteration dependent ANN may have to face local minima problems also. In this work, this specific problem is solved by proposing a hybrid swarm intelligence-Kohonen approach. The inclusion of Particle Swarm Optimization (PSO) in the training algorithm of Kohonen network provides a convergence condition which eliminates the iteration-dependent nature of Kohonen network. The proposed methodology is tested on Magnetic Resonance (MR) brain tumor image classification. A comparative analysis with the conventional Kohonen network shows the superior nature of the proposed technique in terms of the performance measures.
Keywords: Image segmentation and Classification Accuracy, Kohonen Neural network, Particle Swarm Optimization (ID#: 15-7046)


Matthias Galster; “Software Reference Architectures: Related Architectural Concepts and Challenges,” CobRA '15, Proceedings of the 1st International Workshop on Exploring Component-based Techniques for Constructing Reference Architectures, May 2015, Pages 5–8. doi:10.1145/2755567.2755570
Abstract: Software reference architectures provide guidance when designing systems for particular application or technology domains. In this paper we contribute a better understanding of developing and using reference architectures: First, we relate the concept of software reference architecture to other architectural concepts to help engineers better understand the relationships between software development artifacts. Second, we discuss several high-level (and mostly non-technical) challenges related to the design and use of software reference architectures. These challenges can be used a) to formulate research problems for future work, and b) to define software product and development scenarios in which reference architectures may be difficult to apply. Finally, we explore application domains that may benefit from established reference architectures, including concrete challenges related to reference architectures in these domains.
Keywords: architectural concepts, challenges, frameworks, software reference architecture (ID#: 15-7047)


Ahmad-Reza Sadeghi, Christian Wachsmann, Michael Waidner; “Security and Privacy Challenges in Industrial Internet of Things,” DAC '15, Proceedings of the 52nd Annual Design Automation Conference, June 2015, Article No. 54. doi:10.1145/2744769.2747942
Abstract: Today, embedded, mobile, and cyberphysical systems are ubiquitous and used in many applications, from industrial control systems, modern vehicles, to critical infrastructure. Current trends and initiatives, such as “Industrie 4.0” and Internet of Things (IoT), promise innovative business models and novel user experiences through strong connectivity and effective use of next generation of embedded devices. These systems generate, process, and exchange vast amounts of security-critical and privacy-sensitive data, which makes them attractive targets of attacks. Cyberattacks on IoT systems are very critical since they may cause physical damage and even threaten human lives. The complexity of these systems and the potential impact of cyberattacks bring upon new threats.  This paper gives an introduction to Industrial IoT systems, the related security and privacy challenges, and an outlook on possible solutions towards a holistic security framework for Industrial IoT systems.
Keywords: (not provided) (ID#: 15-7048)


Jia-bin Wang, Wei-Neng Chen, Jun Zhang, Ying Lin; “A Dimension-Decreasing Particle Swarm Optimization Method for Portfolio Optimization,” GECCO Companion '15, Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, July 2015, Pages 1515–1516. doi:10.1145/2739482.2764652
Abstract: Portfolio optimization problems are challenging as they contain different kinds of constrains and their complexity becomes very high when the number of assets grows. In this paper, we develop a dimension-decreasing particle swarm optimization (DDPSO) for solving multi-constrained portfolio optimization problems. DDPSO improves the efficiency of PSO for solving portfolio optimization problems with a lot of asset and it can easily handle the cardinality constraint in portfolio optimization. To improve search diversity, the dimension-decreasing method is coupled with the comprehensive learning particle swarm optimization (CLPSO) algorithm. The proposed method is tested on benchmark problems from the OR library. Experimental results show that the proposed algorithm performs well.
Keywords: cardinality constraint, dimension-decreasing, particle swarm optimization, portfolio optimization (ID#: 15-7049)


William F. Bond, Ahmed Awad E.A.; “Touch-based Static Authentication Using a Virtual Grid,” IH&MMSec '15,
Proceedings of the 3rd ACM Workshop on Information Hiding and Multimedia Security
, June 2015,
Pages 129–134. doi:10.1145/2756601.2756602
Abstract: Keystroke dynamics is a subfield of computer security in which the cadence of the typist’s keystrokes are used to determine authenticity. The static variety of keystroke dynamics uses typing patterns observed during the typing of a password or passphrase. This paper presents a technique for static authentication on mobile tablet devices using neural networks for analysis of keystroke metrics. Metrics used in the analysis of typing are monographs, digraphs, and trigraphs. Monographs as we define them consist of the time between the press and release of a single key, coupled with the discretized x–y location of the keystroke on the tablet. A digraph is the duration between the presses of two consecutively pressed keys, and a trigraph is the duration between the press of a key and the press of a key two keys later. Our technique combines the analysis of monographs, digraphs, and trigraphs to produce a confidence measure. Our best equal error rate for distinguishing users from impostors is 9.3% for text typing, and 9.0% for a custom experiment setup that is discussed in detail in the paper.
Keywords: Bayesian fusion, back-propagation neural networks, digraphs, discretization, keystroke dynamics, mobile authentication, monographs, receiver operating characteristic curve, static authentication, trigraphs (ID#: 15-7050)


Marlena R. Fraune, Steven Sherrin, Selma Sabanović, Eliot R. Smith; “Rabble of Robots Effects: Number and Type of Robots Modulates Attitudes, Emotions, and Stereotypes,” HRI '15, Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction, March 2015, Pages 109–116. doi:10.1145/2696454.2696483
Abstract: Robots are expected to become present in society in increasing numbers, yet few studies in human-robot interaction (HRI) go beyond one-to-one interaction to examine how emotions, attitudes, and stereotypes expressed toward groups of robots differ from those expressed toward individuals. Research from social psychology indicates that people interact differently with individuals than with groups. We therefore hypothesize that group effects might similarly occur when people face multiple robots. Further, group effects might vary for robots of different types. In this exploratory study, we used videos to expose participants in a between-subjects experiment to robots varying in Number (Single or Group) and Type (anthropomorphic, zoomorphic, or mechanomorphic). We then measured participants’ general attitudes, emotions, and stereotypes toward robots with a combination of measures from HRI (e.g., Godspeed Questionnaire, NARS) and social psychology (e.g., Big Five, Social Threat, Emotions). Results suggest that Number and Type of observed robots had an interaction effect on responses toward robots in general, leading to more positive responses for groups for some robot types, but more negative responses for others.
Keywords: attitudes, emotion, group effects, human-robot interaction, inter-group interactions, robot type, stereotypes (ID#: 15-7051)


Ayumi Sugiyama, Toshiharu Sugawara; “Meta-Strategy for Cooperative Tasks with Learning of Environments in Multi-Agent Continuous Tasks,” SAC '15, Proceedings of the 30th Annual ACM Symposium on Applied Computing, April 2015,
Pages 494–500. doi:10.1145/2695664.2695878
Abstract: With the development of robot technology, we can expect self-propelled robots working in large areas where cooperative and coordinated behaviors by multiple (hardware and software) robots are necessary. However, it is not trivial for agents, which are control programs running on robots, to determine the actions for their cooperative behaviors, because such strategies depend on the characteristics of the environment and the capabilities of individual agents. Therefore, using the example of continuous cleaning tasks by multiple agents, we propose a method of meta-strategy that decide the appropriate planning strategies for cooperation and coordination through with the learning of the performance of individual strategies and the environmental data in a multi-agent systems context, but without complex reasoning for deep coordination due to the limited CPU capability and battery capacity. We experimentally evaluated our method by comparing it with a conventional method that assumes that agents have knowledge on where agents visit frequently (since they are easy to become dirty). We found that agents with the proposed method could operate as effectively as and, in complex areas, outperformed those with the conventional method. Finally, we describe that the reasons for such a counterintuitive phenomenon is induced from splitting up in working by autonomous agents based on the local observations. We also discuss the limitation of the current method.
Keywords: continuous cleaning, cooperation, coordination, division of labor, multi-agent systems (ID#: 15-7052)


Afshin Shahriari, Hamid Parvin, Alireza Monajati; “Exploring Weights of Hierarchical and Equivalency Relationship in General Persian Texts,” EANN '15, Proceedings of the 16th International Conference on Engineering Applications of Neural Networks (INNS), September 2015, Article No. 7. doi:10.1145/2797143.2797167
Abstract: A thesaurus is a reference work that lists words grouped together according to similarity of meaning (containing synonyms and sometimes antonyms), in contrast to a dictionary, which contains definitions and pronunciations. Three kinds of relationships used in a thesaurus includes: (1) equivalency, (2) hierarchy, and finally (2) association. This paper proposes a novel method to develop a classification task in general Persian context while it employs a thesaurus. Two kinds of word relationships are employed in our used thesaurus: (1) equivalency, and (2) hierarchy. Each of these kinds has a weight that can be tuned. The paper explores all possible weights for the proper ones. After that a feature selection mechanism is also employed. A host of machine learning algorithms are employed as the classifier over the frequency based features. Experimental results indicate the usage of the best weights for these relationships; can lead to a good result.
Keywords: Equivalency, General Persian Text, Hierarchy (ID#: 15-7053)


Jean Michel Rouly, Huzefa Rangwala, Aditya Johri; “What Are We Teaching?: Automated Evaluation of CS Curricula Content Using Topic Modeling,” ICER '15, Proceedings of the Eleventh Annual International Conference on International Computing Education Research, July 2015, Pages 189–197. doi:10.1145/2787622.2787723
Abstract: Identifying the concepts covered in a university course based on a high level description is a necessary step in the evaluation of a university’s program of study. To this end, data describing university courses is readily available on the Internet in vast quantities. However, understanding natural language course descriptions requires manual inspection and, often, implicit knowledge of the subject area. Additionally, a holistic approach to curricular evaluation involves analysis of the prerequisite structure within a department, specifically the conceptual overlap between courses in a prerequisite chain. In this work we apply existing topic modeling techniques to sets of course descriptions extracted from publicly available university course catalogs. The inferred topic models correspond to concepts taught in the described courses. The inference process is unsupervised and generates topics without the need for manual inspection. We present an application framework for data ingestion and processing, along with a user-facing web-based application for inferred topic presentation. The software provides tools to view the inferred topics for a university’s courses, quickly compare departments by their topic composition, and visually analyze conceptual overlap in departmental prerequisite structures. The tool is available online at
Keywords: course descriptions, prerequisite chain, topic modeling, web visualization (ID#: 15-7054)


Xiao-Fang Liu, Zhi-Hui Zhan, Jun Zhang; “Dichotomy Guided Based Parameter Adaptation for Differential Evolution,” GECCO '15, Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, July 2015,
Pages 289–296. doi:10.1145/2739480.2754646
Abstract: Differential evolution (DE) is an efficient and powerful population-based stochastic evolutionary algorithm, which evolves according to the differential between individuals. The success of DE in obtaining the optima of a specific problem depends greatly on the choice of mutation strategies and control parameter values. Good parameters lead the individuals towards optima successfully. The increasing of the success rate (the ratio of entering the next generation successfully) of population can speed up the searching. Adaptive DE incorporates success-history or population-state based parameter adaptation. However, sometimes poor parameters may improve individual with small probability and are regarded as successful parameters. The poor parameters may mislead the parameter control. So, in this paper, we propose a novel approach to distinguish between good and poor parameters in successful parameters. In order to speed up the convergence of algorithm and find more “good” parameters, we propose a dichotomy adaptive DE (DADE), in which the successful parameters are divided into two parts and only the part with higher success rate is used for parameter adaptation control. Simulation results show that DADE is competitive to other classic or adaptive DE algorithms on a set of benchmark problem and IEEE CEC 2014 test suite.
Keywords: adaptive parameter control, dichotomy-guided, differential evolution, evolutionary optimization (ID#: 15-7055)


Aleksandr Farseev, Liqiang Nie, Mohammad Akbari, Tat-Seng Chua; “Harvesting Multiple Sources for User Profile Learning: a Big Data Study,” ICMR '15, Proceedings of the 5th ACM International Conference on Multimedia Retrieval, June 2015,
Pages 235–242. doi:10.1145/2671188.2749381
Abstract: User profile learning, such as mobility and demographic profile learning, is of great importance to various applications. Meanwhile, the rapid growth of multiple social platforms makes it possible to perform a comprehensive user profile learning from different views. However, the research efforts on user profile learning from multiple data sources are still relatively sparse, and there is no large-scale dataset released towards user profile learning. In our study, we contribute such benchmark and perform an initial study on user mobility and demographic profile learning. First, we constructed and released a large-scale multi-source multi-modal dataset from three geographical areas. We then applied our proposed ensemble model on this dataset to learn user profile. Based on our experimental results, we observed that multiple data sources mutually complement each other and their appropriate fusion boosts the user profiling performance.
Keywords: demographic profile, mobility profile, multiple source integration, user profile learning (ID#: 15-7056)


J. Amudhavel, D. Rajaguru, S. Sampath Kumar, Sonali H. Lakhani, T. Vengattaraman, K. Prem Kumar; “A Chaotic Krill Herd Optimization Approach in VANET for Congestion Free Effective Multi Hop Communication,” ICARCSET '15, Proceedings of the 2015 International Conference on Advanced Research in Computer Science Engineering & Technology (ICARCSET 2015), March 2015, Article No. 27. doi:10.1145/2743065.2743092
Abstract: VANET, which stands for Vehicular Ad-Hoc Network has many applications in Urban areas where congestion has become a drastic problem. VANET is a network where vehicles act as nodes. The Krill Herd algorithm recently designed by Gandomi and Alavi is one of the best optimization techniques. Even though Krill Herd algorithm satisfies many optimization problems, it lacks the three issues, namely local optima avoidance, high convergence speed and the absence of congestion. So in this paper, Chaotic theory is introduced into the krill herd algorithm to solve the three issues, thus forming the Chaotic Krill Herd algorithm (CKH). The Chaotic Krill Herd algorithm introduces three chaotic maps, namely Circle, Sine and Sinusoidal to provide chaotic behaviors and also enables the Krill herd algorithm to have a group of krills with chaotic induced movements. With the help of these three chaotic maps, Congestion can also be reduced to a greater extent.
Keywords: Congestion, Convergence speed, Krill Herd Algorithm, Local optima, Route Discovery, VANET (ID#: 15-7057)


Yixiao Lin, Sayan Mitra; “StarL: Towards a Unified Framework for Programming, Simulating and Verifying Distributed Robotic Systems,” LCTES '15, Proceedings of the 16th ACM SIGPLAN/SIGBED Conference on Languages, Compilers and Tools for Embedded Systems 2015, June 2015, Article No. 9. doi:10.1145/2670529.2754966
Abstract: We developed StarL as a framework for programming, simulating, and verifying distributed systems that interacts with physical processes. StarL framework has (a) a collection of distributed primitives for coordination, such as mutual exclusion, registration and geocast that can be used to build sophisticated applications, (b) theory libraries for verifying StarL applications in the PVS theorem prover, and (c) an execution environment that can be used to deploy the applications on hardware or to execute them in a discrete event simulator. The primitives have (i) abstract, nondeterministic specifications in terms of invariants, and assume-guarantee style progress properties, (ii) implementations in Java/Android that always satisfy the invariants and attempt progress using best effort strategies. The PVS theories specify the invariant and progress properties of the primitives, and have to be appropriately instantiated and composed with the application’s state machine to prove properties about the application. We have built two execution environments: one for deploying applications on Android/iRobot Create platform and a second one for simulating large instantiations of the applications in a discrete even simulator. The capabilities are illustrated with a StarL application for vehicle to vehicle coordination in an automatic intersection that uses primitives for point-to-point motion, mutual exclusion, and registration.
Keywords: Programming models, distributed systems, mechanical theorem proving (ID#: 15-7058)


Thomas Holleczek, Dang The Anh, Shanyang Yin, Yunye Jin, Spiros Antonatos, Han Leong Goh, Samantha Low, Amy Shi-Nash; “Traffic Measurement and Route Recommendation System for Mass Rapid Transit (MRT),” KDD '15, Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2015,
Pages 1859–1868. doi:10.1145/2783258.2788590
Abstract: Understanding how people use public transport is important for the operation and future planning of the underlying transport networks. We have therefore developed and deployed a traffic measurement system for a key player in the transportation industry to gain insights into crowd behavior for planning purposes. The system has been in operation for several months and reports, at hourly intervals, (1) the crowdedness of subway stations, (2) the flows of people inside interchange stations, and (3) the expected travel time for each possible route in the subway network of Singapore. The core of our system is an efficient algorithm which detects individual subway trips from anonymized real-time data generated by the location based system of Singtel, the country's largest telecommunications company. To assess the accuracy of our system, we engaged an independent market research company to conduct a field study--a manual count of the number of passengers boarding and disembarking at a selected station on three separate days. A strong correlation between the calculations of our algorithm and the manual counts was found. One of our key findings is that travelers do not always choose the route with the shortest travel time in the subway network of Singapore. We have therefore also been developing a mobile app which allows users to plan their trips based on the average travel time between stations.
Keywords: call detail records (cdrs), cellular networks, monitoring system, public transport (ID#: 15-7059)


Anirban Sengupta, Saumya Bhadauria; “Untrusted Third Party Digital IP Cores: Power-Delay Trade-off Driven Exploration of Hardware Trojan Secured Datapath During High Level Synthesis,” GLSVLSI '15, Proceedings of the 25th edition on Great Lakes Symposium on VLSI, May 2015, Pages 167–172. doi:10.1145/2742060.2742061
Abstract: An evolutionary algorithm (EA) driven novel design space exploration (DSE) of an optimized hardware Trojan secured datapath based on user power-delay constraint during high level synthesis (HLS) is presented. The focus on hardware Trojan secured datapath generation during HLS has been very little with absolutely zero effort so far in design space exploration of a user multi-objective (MO) constraint optimized hardware Trojan secured datapath. This problem mandates attention as producing a Trojan secured datapath is not inconsequential. Merely the detection process of Trojan is not as straightforward as concurrent error detection (CED) of transient faults as it involves the concept of multiple third party intellectual property (3PIP) vendors to facilitate detection, let aside the exploration process of a user optimized Trojan secured datapath based on MO constraints. The proposed DSE for hardware Trojan detection includes novel problem encoding technique that enables exploration of efficient distinct vendor allocation as well as enables exploration of an optimized Trojan secured datapath structure. The exploration backbone for the proposed approach is bacterial foraging optimization algorithm (BFOA) which is known for its adaptive feature (tumbling/swimming) and simplified model. Results of comparison with recent approach indicated an average improvement in quality of results (QoR) of >14.1%
Keywords: 3PIP, BFOA, delay, DSE, hardware trojan, HLS, power (ID#: 15-7060)


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