Sooryaa Vignesh Thiruloga
M.S. FinalDec 14, 2021, 9:30 am - 11:00 am
ENGR C101 B & Zoom
Anomaly Detection with Machine Learning for Automotive Cyber-Physical Systems
Abstract: Modern vehicles can be thought of as complex distributed embedded systems that run a variety of automotive applications with real-time constraints. Recent advances in the automotive industry towards greater autonomy are driving vehicles to be increasingly connected with various external systems (e.g., roadside beacons, other vehicles), which makes emerging vehicles highly vulnerable to cyber-attacks. Additionally, the increased complexity of automotive applications and the in-vehicle networks results in poor attack visibility, which makes detecting such attacks particularly challenging in automotive systems. In this thesis, we present two novel machine learning-based Intrusion detection techniques for in-vehicle network anomaly detection
Adviser: Sudeep Pasricha
Co-Adviser: N/A
Non-ECE Member: Indrakshi Ray
Member 3: Ryan Kim
Addional Members: N/A
Co-Adviser: N/A
Non-ECE Member: Indrakshi Ray
Member 3: Ryan Kim
Addional Members: N/A
Publications:
JOURNAL PUBLICATIONS:
• V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, “Roadmap for Cybersecurity in Autonomous Vehicles”, IEEE Consumer Electronics Magazine (CEM) (under review), 2021.
• V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, “LATTE: LSTM Self-Attention based Anomaly Detection in Embedded Automotive Platforms”, IEEE/ACM International Conference on Hardware Software Codesign and System Synthesis (CODES+ISSS) (ESWEEK), 2021.
• V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, “INDRA: Intrusion Detection using Recurrent Autoencoders in Automotive Embedded Systems”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, (TCAD), 39(11), Nov 2020.
CONFERENCE PUBLICATIONS:
• S. V. Thiruloga, V. K. Kukkala, and S. Pasricha, “TENET: Temporal CNN with Attention for Anomaly Detection in Automotive Cyber-Physical Systems”, IEEE/ACM Asia & South Pacific Design Automation Conference (ASPDAC) (to appear), 2022.
BOOK CHAPTER:
• V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, “AI for Cybersecurity in Distributed Automotive IoT Systems”, Electronic Design for AI, IoT and Hardware Security (to appear), Springer, 2022.
JOURNAL PUBLICATIONS:
• V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, “Roadmap for Cybersecurity in Autonomous Vehicles”, IEEE Consumer Electronics Magazine (CEM) (under review), 2021.
• V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, “LATTE: LSTM Self-Attention based Anomaly Detection in Embedded Automotive Platforms”, IEEE/ACM International Conference on Hardware Software Codesign and System Synthesis (CODES+ISSS) (ESWEEK), 2021.
• V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, “INDRA: Intrusion Detection using Recurrent Autoencoders in Automotive Embedded Systems”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, (TCAD), 39(11), Nov 2020.
CONFERENCE PUBLICATIONS:
• S. V. Thiruloga, V. K. Kukkala, and S. Pasricha, “TENET: Temporal CNN with Attention for Anomaly Detection in Automotive Cyber-Physical Systems”, IEEE/ACM Asia & South Pacific Design Automation Conference (ASPDAC) (to appear), 2022.
BOOK CHAPTER:
• V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, “AI for Cybersecurity in Distributed Automotive IoT Systems”, Electronic Design for AI, IoT and Hardware Security (to appear), Springer, 2022.
Program of Study:
ECE 580B9
ECE 561
ECE 455
ECE 699
ECE 554
CS 445
ECE 581C1
GRAD 575
ECE 580B9
ECE 561
ECE 455
ECE 699
ECE 554
CS 445
ECE 581C1
GRAD 575