Visible to the public Biblio

Filters: Author is Karimi, Naghmeh  [Clear All Filters]
2020-07-30
Shey, James, Karimi, Naghmeh, Robucci, Ryan, Patel, Chintan.  2018.  Design-Based Fingerprinting Using Side-Channel Power Analysis for Protection Against IC Piracy. 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI). :614—619.

Intellectual property (IP) and integrated circuit (IC) piracy are of increasing concern to IP/IC providers because of the globalization of IC design flow and supply chains. Such globalization is driven by the cost associated with the design, fabrication, and testing of integrated circuits and allows avenues for piracy. To protect the designs against IC piracy, we propose a fingerprinting scheme based on side-channel power analysis and machine learning methods. The proposed method distinguishes the ICs which realize a modified netlist, yet same functionality. Our method doesn't imply any hardware overhead. We specifically focus on the ability to detect minimal design variations, as quantified by the number of logic gates changed. Accuracy of the proposed scheme is greater than 96 percent, and typically 99 percent in detecting one or more gate-level netlist changes. Additionally, the effect of temperature has been investigated as part of this work. Results depict 95.4 percent accuracy in detecting the exact number of gate changes when data and classifier use the same temperature, while training with different temperatures results in 33.6 percent accuracy. This shows the effectiveness of building temperature-dependent classifiers from simulations at known operating temperatures.

2020-03-12
Salmani, Hassan, Hoque, Tamzidul, Bhunia, Swarup, Yasin, Muhammad, Rajendran, Jeyavijayan JV, Karimi, Naghmeh.  2019.  Special Session: Countering IP Security Threats in Supply Chain. 2019 IEEE 37th VLSI Test Symposium (VTS). :1–9.

The continuing decrease in feature size of integrated circuits, and the increase of the complexity and cost of design and fabrication has led to outsourcing the design and fabrication of integrated circuits to third parties across the globe, and in turn has introduced several security vulnerabilities. The adversaries in the supply chain can pirate integrated circuits, overproduce these circuits, perform reverse engineering, and/or insert hardware Trojans in these circuits. Developing countermeasures against such security threats is highly crucial. Accordingly, this paper first develops a learning-based trust verification framework to detect hardware Trojans. To tackle Trojan insertion, IP piracy and overproduction, logic locking schemes and in particular stripped functionality logic locking is discussed and its resiliency against the state-of-the-art attacks is investigated.