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Journal ArticleDOI

Real-Time SoC Security against Passive Threats Using Crypsis Behavior of Geckos

TL;DR: This work seeks refuge to the crypsis behavior exhibited by geckos in nature to generate a runtime security technique for SoC architectures, which can bypass runtime passive threats of a HTH.
Abstract: The rapid evolution of the embedded era has witnessed globalization for the design of SoC architectures in the semiconductor design industry. Though issues of cost and stringent marketing deadlines have been resolved in such a methodology, yet the root of hardware trust has been evicted. Malicious circuitry, a.k.a. Hardware Trojan Horse (HTH), is inserted by adversaries in the less trusted phases of design. A HTH remains dormant during testing but gets triggered at runtime to cause sudden active and passive attacks. In this work, we focus on the runtime passive threats based on the parameter delay. Nature-inspired algorithms offer an alternative to the conventional techniques for solving complex problems in the domain of computer science. However, most are optimization techniques and none is dedicated to security. We seek refuge to the crypsis behavior exhibited by geckos in nature to generate a runtime security technique for SoC architectures, which can bypass runtime passive threats of a HTH. An adaptive security intellectual property (IP) that works on the proposed security principles is designed. Embedded timing analysis is used for experimental validation. Low area and power overhead of our proposed security IP over standard benchmarks and practical crypto SoC architectures as obtained in experimental results supports its applicability for practical implementations.
References
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Proceedings ArticleDOI
06 Aug 2002
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Abstract: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications, including nonlinear function optimization and neural network training, are proposed. The relationships between particle swarm optimization and both artificial life and genetic algorithms are described.

35,104 citations

Journal ArticleDOI
01 Feb 1996
TL;DR: It is shown how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling, and the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
Abstract: An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.

11,224 citations


"Real-Time SoC Security against Pass..." refers background in this paper

  • ...ACO is based on the action of ants where finding optimal solutions is the objective in a space comprising all possible solutions [Dorigo et al. 1996]....

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Proceedings ArticleDOI
01 Dec 2009
TL;DR: A new meta-heuristic algorithm, called Cuckoo Search (CS), is formulated, based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Lévy flight behaviour ofSome birds and fruit flies, for solving optimization problems.
Abstract: In this paper, we intend to formulate a new meta-heuristic algorithm, called Cuckoo Search (CS), for solving optimization problems. This algorithm is based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Levy flight behaviour of some birds and fruit flies. We validate the proposed algorithm against test functions and then compare its performance with those of genetic algorithms and particle swarm optimization. Finally, we discuss the implication of the results and suggestion for further research.

5,521 citations


Additional excerpts

  • ...DOI: http://dx.doi.org/10.1145/3014166...

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01 Jan 2005

5,265 citations


"Real-Time SoC Security against Pass..." refers methods in this paper

  • ...Similarly, ABC algorithm is based on the foraging behaviour of honey bees, which is used to explore new regions in the search space [Karaboga 2005]....

    [...]

  • ...DOI: http://dx.doi.org/10.1145/3014166...

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Journal ArticleDOI
TL;DR: A classification of hardware Trojans and a survey of published techniques for Trojan detection are presented.
Abstract: Editor's note:Today's integrated circuits are vulnerable to hardware Trojans, which are malicious alterations to the circuit, either during design or fabrication. This article presents a classification of hardware Trojans and a survey of published techniques for Trojan detection.

1,227 citations