The EPIC Lab’s research on secure and real‑time automotive network management advances the foundations of dependable, AI‑enabled automotive cyber‑physical systems. This work spans anomaly detection using temporal CNNs, LSTMs, and recurrent autoencoders; intrusion‑resilient architectures for embedded automotive platforms; and security‑aware scheduling frameworks for time‑critical in‑vehicle networks such as FlexRay and time‑triggered Ethernet. The lab also investigates emerging challenges in software‑defined vehicles, including secure control, certification‑ready architectures, and robust communication under uncertainty. Complementary contributions address jitter‑aware message scheduling, signal‑integrity monitoring, and powertrain control reliability, forming a comprehensive approach to ensuring predictable timing, resilience to cyber‑attacks, and safe operation in increasingly autonomous and connected vehicles. Collectively, this research establishes a cross‑layer foundation for next‑generation automotive systems that integrate real‑time guarantees with strong security and system‑level dependability.
Selected Publications
B. Ranjbar, K. Raveendiran, S. Pasricha, S. Chakraborty, C. Carbonelli, and A. Kumar, “Autonomous Systems Dependability in the era of AI: Design Challenges in Security, Reliability and Certification”, IEEE/ACM Design, Automation and Test in Europe (DATE) Conference, Verona, Italy, Mar 2026.
A. El-Fatyany, X. Wang, P. S. Duggirala, S. Chakraborty, S. Pasricha, A. K. Singh, “Emerging Architecture Design, Control, and Security Challenges in Software Defined Vehicles”, IEEE/ACM ESWEEK, Oct 2024.
V. Kukkala, S. Pasricha, “Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems“, Springer Nature Publishers, 2023.
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), Jan 2022. (Best Paper Award Candidate)
V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, “LATTE: LSTM Self-Attention based Anomaly Detection in Embedded Automotive Platforms”, ACM Transactions on Embedded Computing Systems (TECS), Volume 20, Issue 5s, Oct 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.
V. Kukkala, S. Pasricha, T. H. Bradley, “SEDAN: Security-Aware Design of Time-Critical Automotive Networks”, IEEE Transactions on Vehicular Technology (TVT), vol. 69, no. 8, Aug 2020
V. Kukkala, S. Pasricha, T. H. Bradley, “JAMS-SG: A Framework for Jitter-Aware Message Scheduling for Time-Triggered Automotive Networks”, ACM Transactions on Design Automation of Electronic Systems (TODAES), Vol. 24, Iss. 6, Nov 2019
V. K. Kukkala, S. Pasricha, T. Bradley, “JAMS: Jitter-Aware Message Scheduling for FlexRay Automotive Networks,” IEEE/ACM International Symposium on Networks-on-Chip (NOCS), Oct 2017.
V. K. Kukkala, T. Bradley, S. Pasricha, “Uncertainty Analysis and Propagation for an Auxiliary Power Module,” IEEE Transportation and Electrification Conference (TEC), 2017.
V. K. Kukkala, T. Bradley, S. Pasricha, “Priority-based Multi-level Monitoring of Signal Integrity in a Distributed Powertrain Control System,” 4th IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling, Jul 2015. (Invited)