Focused ion beam (FIB) has emerged as one of the most prevalent integrated circuit (IC) editing techniques in the past decade, greatly assisting post-silicon debugging and failure analysis. However, the confidentiality of security assets on electronic devices is gravely threatened by FIB-based probing attacks because of the FIB’s fine-grained milling and deposition capabilities on silicon die. Although numerous solutions, such as active shields and analog sensors have been proposed, they either incur prohibitively high overhead or suffer from low reliability, failing to provide protection against such threats in a feasible manner. In this article, we propose a FIB-aware framework, iPROBE, as a set of computer-aided design (CAD) utilities to quantify the threats of FIB attacks on the target layout from both front-side and back-side at the pre-silicon stage. The subsequent shield nets/layer place-and-route are completely automated by iPROBE to minimize the quantified FIB vulnerability metric, so-called exposed area (EA), allowing users to achieve the optimal security level at a cost of minimal performance degradation, extra design efforts, and time consumption. Our experimental results show that the EA of security-critical nets, i.e., vulnerable regions inside the physical layout, to front-side and back-side probing attacks can be fully eliminated at low FIB aspect ratios with only 3% timing and area overhead. Moreover, we validate the results through the FIB experiments on a fabricated test chip covering both baseline and iPROBE-protected AES implementations at 65nm technology node, further demonstrating the effectiveness of iPROBE.

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.