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Šišejković, Dominik, Leupers, Rainer, Ascheid, Gerd, Metzner, Simon.  2018.  A Unifying Logic Encryption Security Metric. Proceedings of the 18th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation. :179–186.
The globalization of the IC supply chain has brought forth the era of fabless companies. Due to security issues during design and fabrication processes, various security concerns have risen, ranging from IP piracy and reverse engineering to hardware Trojans. Logic encryption has emerged as a mitigation against these threats. However, no generic metrics for quantifying the security of logic encryption algorithms has been reported so far, making it impossible to formally compare different approaches. In this paper, we propose a unifying metric, capturing the key security aspects of logic encryption algorithms. The metric is evaluated on state-of-the-art algorithms and benchmarks.
Andraud, Martin, Hallawa, Ahmed, De Roose, Jaro, Cantatore, Eugenio, Ascheid, Gerd, Verhelst, Marian.  2018.  Evolving Hardware Instinctive Behaviors in Resource-scarce Agent Swarms Exploring Hard-to-reach Environments. Proceedings of the Genetic and Evolutionary Computation Conference Companion. :1497–1504.
This work introduces a novel adaptation framework to energy-efficiently adapt small-sized circuits operating under scarce resources in dynamic environments, as autonomous swarm of sensory agents. This framework makes it possible to optimally configure the circuit based on three key mechanisms: (a) an off-line optimization phase relying on R2 indicator based Evolutionary Multi-objective Optimization Algorithm (EMOA), (b) an on-line phase based on hardware instincts and (c) the possibility to include the environment in the optimization loop. Specifically, the evolutionary algorithm is able to simultaneously determine an optimal combination of static settings and dynamic instinct for the hardware, considering highly dynamic environments. The instinct is then run on-line with minimal on-chip resources so that the circuit efficiently react to environmental changes. This framework is demonstrated on an ultrasonic communication system between energy-scarce wireless nodes. The proposed approach is environment-adaptive and enables power savings up to 45% for the same performance on the considered case studies.