Biblio
Filters: Author is Yin, Yanzhao [Clear All Filters]
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2019. A New Information Extractor for Profiled DPA and Implementation of High Order Masking Circuit. 2019 IEEE 13th International Conference on Anti-counterfeiting, Security, and Identification (ASID). :258–262.
Profiled DPA is a new method combined with machine learning method in side channel attack which is put forward by Whitnall in CHES 2015.[1]The most important part lies in effectiveness of extracting information. This paper introduces a new rule Explained Local Variance (ELV) to extract information in profiled stage for profiled DPA. It attracts information effectively and shields noise to get better accuracy than the original rule. The ELV enables an attacker to use less power traces to get the same result as before. It also leads to 94.6% space reduction and 29.2% time reduction for calculation. For security circuit implementation, a high order masking scheme in modelsim is implemented. A new exchange network is put forward. 96.9% hardware resource is saved due to the usage of this network.
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2019. Hardware Trojan Detection Combine with Machine Learning: an SVM-based Detection Approach. 2019 IEEE 13th International Conference on Anti-counterfeiting, Security, and Identification (ASID). :202–206.
With the application of integrated circuits (ICs) appears in all aspects of life, whether an IC is security and reliable has caused increasing worry which is of significant necessity. An attacker can achieve the malicious purpose by adding or removing some modules, so called hardware Trojans (HTs). In this paper, we use side-channel analysis (SCA) and support vector machine (SVM) classifier to determine whether there is a Trojan in the circuit. We use SAKURA-G circuit board with Xilinx SPARTAN-6 to complete our experiment. Results show that the Trojan detection rate is up to 93% and the classification accuracy is up to 91.8475%.