Tamper Detection in Digital Circuits

My primary area of research is tamper detection in digital hardware. The objective is to develop methods to detect and prevent active attempts to embed malicious functionality within digital circuits and investigate secure circuit design techniques that reduce or eliminate an attacker's ability to exploit this form of stealthy attack. The goal is to detect tampering near the end of the design cycle and not to rely on secure design facilities or tools, which in turn enables full access to the latest COTS design technologies including open source cores and cell libraries. In addition, we hope to develop techniques that do not rely on validation with respect to a clean circuit, which would eliminate the threat from insider attack. The potential impact of this research will be secure circuit design approaches and tampering detection methods that raise the bar for the attacker, making the level of security for hardware design commensurate with the state of the art in software protection. A long-term goal is to be able to quantify the security of particular design approaches and make security an optimization dimension along with speed, area and power.

Active Projects

FPGA Assurance- Tamper Detection- Chameleon Circuits

To create systems that automaticallt thwart attacks and exploitation attempts, Chameleon Circuits covertly alter the behavior of FPGA firmware in response to adversaries' asttempts to modify it. Alternate behaviors of covertly embedded Chameleon Circuits have a high degree of resistance to reverse engineering and low impact on the host. Sponsor: Lockheed Martin (Air Force Research Lab). Fea.b 2019-Jan. 2021.

Safeguards Against Hidden Effects and Anomalous Trojans in Hardware (SHEATH)

Sponsor: Assured Information Security (DARPA). Dates: TBD

Ultra-Lightweight Anomaly Detection for Embedded Systems

Embedded systems, such as Internet of Things devices, often lack effective mechanisms for security due to resource constraints. Many proposed security mechanisms, such as intrusion detection, are designed to acheive the highest detection performance without consideration for resource utilizatioa. We have been developing a novel ultra-lightweight anomaly detection approach for resource constrained systems. This approach uses very efficient low-level operations, such as bit-masking and counter increments, to acheive real-time operation with a very small hardware or software footprint. Performance results on embedded systems show that, despite being resource constrained, the approach offers very high attack detection accuracy with very low false positive rates in embedded applications. Furthermore, being amenable to hardware or software implementation adds flexibility in the point of deployment for supporting a wide-range of applications.