Since finite state machines (FSMs) regulate the control flow in circuits, a computing system’s security might be breached by attacking the FSM. Physical attacks are especially worrisome because they can bypass software countermeasures. For example, an attacker can gain illegal access to the sensitive states of an FSM through fault injection, leading to privilege escalation and/or information leakage. Laser fault injection (LFI) provides one of the most effective attack vectors by enabling adversaries to precisely overturn single flip-flops states. Although conventional error correction/detection methodologies have been employed to improve FSM resiliency, their substantial overhead makes them unattractive to circuit designers. In our prior work, a novel decision diagram-based FSM encoding scheme called PATRON was proposed to resist LFI according to attack parameters, e.g., number of simultaneous faults. Although PATRON bested traditional encodings keeping overhead minimum, it provided numerous candidates for FSM designs requiring exhaustive and manual effort to select one optimum candidate. In this article, we automatically select an optimum candidate by enhancing PATRON using linear programming (LP). First, we exploit the proportionality between dynamic power dissipation and switching activity in digital CMOS circuits. Thus, our LP objective minimizes the number of FSM bit switches per transition, for comparatively lower switching activity and hence total power consumption. Second, additional LP constraints along with incorporating the original PATRON rules, systematically enforce bidirectionality to at least two state elements per FSM transition. This bestows protection against different types of fault injection, which we capture with a new unidirectional metric. Enhanced PATRON (EP) achieves superior security at lower power consumption in average compared to PATRON, error-coding, and traditional FSM encoding on five popular benchmarks.

Finite state machines (FSMs) control the behavior of sequential circuits, including access to privileged states and sensitive information. Laser-based fault injection (LFI) is a precise method where an adversary breaks the chip security by altering the values of individual flip-flops (FFs) with a laser beam. To understand LFI, different laser models, e.g., bit flip, bit set, and bit reset, have been developed. Existing countermeasures can improve FSM resiliency, but either generate multiple LFI resilient encodings applicable only to certain models, or are too conservative, thus incurring significant overhead. In this paper, we introduce the transition-based encoding CAD framework (TAMED), which offers greater flexibility by precisely generating a single optimized FSM encoding that is resilient to multiple LFI models. Predicated on linear programming, TAMED introduces Transitional Vulnerability Metrics that can quantify susceptibility of FSMs based on the bit flip model and the set-reset models. TAMED is demonstrated on 5 benchmarks and outperforms other FSM encoding schemes in terms of security and overhead.

Since Finite State Machines (FSMs) regulate the overall operations in majority of the digital systems, the security of an entire system can be jeopardized if the FSM is vulnerable to physical attacks. By injecting faults into an FSM, an attacker can attain unauthorized access to sensitive states, resulting in information leakage and privilege escalation. One of the powerful fault injection techniques is laser-based fault injection (LFI), which enables an adversary to alter states of individual flip-flops. While standard error correction/detection techniques have been used to protect the FSMs from such fault attacks, their significant overhead makes them unattractive to designers. To keep the overhead minimal, we propose a novel FSM encoding scheme based on decision diagrams that utilizes don't-care states of the FSM. We demonstrate that PATRON outperforms conventional encoding schemes in terms of both security and scalability for popular benchmarks. Finally, we introduce a vulnerability metric to aid the security analysis, which precisely manifests the susceptibility of FSM designs.