Research 

Hardware Security and Reliability 

The research direction on hardware security and reliability aims at developing effective and affordable countermeasures against physical attacks on integrated circuits (ICs), such as reverse engineering, side-channel analysis, and fault injections. This involves creating accurate threat models and vulnerability assessments in the pre-silicon phase, as well as designing multilayer protection mechanisms. Emphasis is placed on leveraging machine learning to enhance security measures and developing innovative sensor technologies for real-time detection of attacks. The goal is to integrate these solutions into existing manufacturing processes to safeguard critical systems and sensitive data. 

Functional Safety of Automotive Vehicles

The research direction on the functional safety of automotive vehicles involves developing robust safety frameworks to ensure autonomous vehicles' reliable and secure operation. This includes integrating advanced sensor technologies, artificial intelligence, and rigorous validation methodologies to create fail-safe mechanisms that mitigate potential risks. The aim is to establish comprehensive safety frameworks that comply with stringent safety standards, fostering public trust in autonomous vehicle technology. Collaboration with industry and cross-disciplinary expertise will drive innovations in fault assessment tools and fault-tolerant algorithms, enhancing overall vehicle safety and reliability. 

The detailed research statement can be found here. 

Relevant Publications

1. Farheen, Tasnuva, Sourav Roy, Andrew Cannon, Jia Di, Shahin Tajik, and Domenic Forte. "Amnesiac Memory: A Self-Destructive Polymorphic Mechanism Against Cold Boot Data Remanence Attack ." In GLSVLSI. ACM, 2024. 

2. Farheen, Tasnuva, Sourav Roy, Jia Di, Shahin Tajik, and Domenic Forte. "Calibratable Polymorphic Temperature Sensor for Detecting Fault Injection and Side-channel Attacks. " In IEEE International Symposium on Hardware Oriented Security and Trust (HOST). IEEE, 2024. 

3. Cannon, Andrew, Tasnuva Farheen, Sourav Roy, Shahin Tajik, and Domenic Forte. "Protection against physical attacks through self-destructive polymorphic latch. " In 2023 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), pp. 1-9. IEEE, 2023. 

4. Holzhausen, Ryan, Tasnuva Farheen, Morgan Thomas, Nima Maghari, and Domenic Forte. "Laser Fault Injection Vulnerability Assessment and Mitigation with Case Study on PG-TVD Logic Cells. " In 2023 IEEE International Test Conference (ITC), pp. 330-339. IEEE, 2023. 

5. Farheen, Tasnuva, Shahin Tajik, and Domenic Forte. "Spred: Spatially distributed laser fault injection resilient design. " In 2023 24th International Symposium on Quality Electronic Design (ISQED), pp. 1-8. IEEE, 2023. 

6. Farheen, Tasnuva, Sourav Roy, Shahin Tajik, and Domenic Forte. "A twofold clock and voltage-based detection method for laser logic state imaging attack. " IEEE Transactions on Very Large Scale Integration (TVLSI) Systems 31, no. 1 (2022): 65-78. 

7. Roy, Sourav, Tasnuva Farheen, Shahin Tajik, and Domenic Forte. "Self-timed sensors for detecting static optical side channel attacks ." In 2022 23rd International Symposium on Quality Electronic Design (ISQED), pp. 1-6. IEEE, 2022. 

8. Farheen, Tasnuva, Ulbert Botero, Nitin Varshney, Damon L. Woodard, Mark Tehranipoor, Domenic Forte, and Haoting Shen. "Proof of reverse engineering barrier: sem image analysis on covert gates ." In ISTFA 2021, pp. 179-189. ASM International, 2021.