Recent advances in hardware security have led to the development of FANCI (Functional Analysis for Nearly-Unused Circuit Identification), an analysis algorithm that identifies stealthy, malicious circuits within hardware designs that can perform backdoor operations to compromise security. Evaluations of such methods using benchmarks and academically known attacks are not always equivalent to the dynamic attack scenarios that can arise in the real world. For this reason, we apply a red team/blue team approach to stress-test the abilities of the FANCI prototype.

Hardware design today bears similarities to software design. Often vendors buy and integrate code acquired from third-party organizations into their designs, especially in embedded/system-on-chip designs. Currently, there is no way to determine if third-party designs have built-in backdoors that can compromise security after deployment.

The proliferation of computers in any domain is followed by the proliferation of malware in that domain. Systems, including the latest mobile platforms, are laden with viruses, rootkits, spyware, adware and other classes of malware. Despite the existence of anti-virus software, malware threats persist and are growing as there exist a myriad of ways to subvert anti-virus (AV) software. In fact, attackers today exploit bugs in the AV software to break into systems.

There have been many attacks that exploit side-effects of program execution to expose secret information and many proposed countermeasures to protect against these attacks. However there is currently no systematic, holistic methodology for understanding information leakage. As a result, it is not well known how design decisions affect information leakage or the vulnerability of systems to side-channel attacks. In this paper, we propose a metric for measuring information leakage called the Side-channel Vulnerability Factor (SVF). SVF is based on our observation that all side-channel attacks ranging from physical to microarchitectural to software rely on recognizing leaked execution patterns. SVF quantifies patterns in attackers' observations and measures their correlation to the victim's actual execution patterns and in doing so captures systems' vulnerability to side-channel attacks. In a detailed case study of on-chip memory systems, SVF measurements help expose unexpected vulnerabilities in whole-system designs and shows how designers can make performance-security trade-offs. Thus, SVF provides a quantitative approach to secure computer architecture.

Hardware components can contain hidden backdoors, which can be enabled with catastrophic effects or for ill-gotten profit. These backdoors can be inserted by a malicious insider on the design team or a third-party IP provider. In this paper, we propose techniques that allow us to build trustworthy hardware systems from components designed by untrusted designers or procured from untrusted third-party IP providers. We present the first solution for disabling digital, design-level hardware backdoors. The principle is that rather than try to discover the malicious logic in the design -- an extremely hard problem -- we make the backdoor design problem itself intractable to the attacker. The key idea is to scramble inputs that are supplied to the hardware units at runtime, making it infeasible for malicious components to acquire the information they need to perform malicious actions. We show that the proposed techniques cover the attack space of deterministic, digital HDL backdoors, provide probabilistic security guarantees, and can be applied to a wide variety of hardware components. Our evaluation with the SPEC 2006 benchmarks shows negligible performance loss (less than 1% on average) and that our techniques can be integrated into contemporary microprocessor designs.

Most security mechanisms proposed to date unquestioningly place trust in microprocessor hardware. This trust, however, is misplaced and dangerous because microprocessors are vulnerable to insider attacks that can catastrophically compromise security, integrity and privacy of computer systems. In this paper, we describe several methods to strengthen the fundamental assumption about trust in microprocessors. By employing practical, lightweight attack detectors within a microprocessor, we show that it is possible to protect against malicious logic embedded in microprocessor hardware. We propose and evaluate two area-efficient hardware methods - TrustNet and DataWatch - that detect attacks on microprocessor hardware by knowledgeable, malicious insiders. Our mechanisms leverage the fact that multiple components within a microprocessor (e.g., fetch, decode pipeline stage etc.) must necessarily coordinate and communicate to execute even simple instructions, and that any attack on a microprocessor must cause erroneous communications between micro architectural subcomponents used to build a processor. A key aspect of our solution is that TrustNet and DataWatch are themselves highly resilient to corruption. We demonstrate that under realistic assumptions, our solutions can protect pipelines and on-chip cache hierarchies at negligible area cost and with no performance impact. Combining TrustNet and DataWatch with prior work on fault detection has the potential to provide complete coverage against a large class of microprocessor attacks.