International Association
for Cryptologic Research

Physical security is an important aspect of devices for which an adversary can manipulate the physical execution environment. Recently, more and more attention has been directed towards a security model that combines the capabilities of passive and active physical attacks, i.e., an adversary that performs fault-injection and side-channel analysis at the same time. Implementing countermeasures against such a powerful adversary is not only costly but also requires the skillful combination of masking and redundancy to counteract all reciprocal effects.In this work, we propose a new methodology to generate combined-secure circuits. We show how to transform Threshold Implementation (TI)-like constructions to resist any adversary with the capability to tamper with internal gates and probe internal wires. For the resulting protection scheme, we can prove the combined security in a well-established theoretical security model.Since the transformation preserves the advantages of TI-like structures, the resulting circuits prove to be more efficient in the number of required bits of randomness (up to 100%), the latency in clock cycles (up to 40%), and even the area for pipelined designs (up to 40%) than the state of the art for an adversary restricted to manipulating a single gate and probing a single wire.

In our highly digitalized world, an adversary is not constrained to purely digital attacks but can monitor or influence the physical execution environment of a target computing device. Such side-channel or fault-injection analysis poses a significant threat to otherwise secure cryptographic implementations. Hence, it is important to consider additional adversarial capabilities when analyzing the security of cryptographic implementations besides the default black-box model. For side-channel analysis, this is done by providing the adversary with knowledge of some internal values, while for fault-injection analysis the capabilities of the adversaries include manipulation of some internal values. In this work, we extend probabilistic security models for physical attacks, by introducing a general random probing model and a general random fault model to capture arbitrary leakage and fault distributions, as well as the combination of these models. Our aim is to enable a more accurate modeling of low-level physical effects. We then analyze important properties, such as the impact of adversarial knowledge on faults and compositions, and provide tool-based formal verification methods that allow the security assessment of design components. These methods are introduced as extension of previous tools VERICA and IronMask which are implemented, evaluated and compared.

Active fault injection is a credible threat to real-world digital systems computing on sensitive data. Arguing about security in the presence of faults is non-trivial, and state-of-the-art criteria are overly conservative and lack the ability of fine-grained comparison. However, comparing two alternative implementations for their security is required to find a satisfying compromise between security and performance. In addition, the comparison of alternative fault scenarios can help optimize the implementation of effective countermeasures. In this work, we use quantitative information flow analysis to establish a vulnerability metric for hardware circuits under fault injection that measures the severity of an attack in terms of information leakage. Potential use cases range from comparing implementations with respect to their vulnerability to specific fault scenarios to optimizing countermeasures. We automate the computation of our metric by integrating it into a state-of-the-art evaluation tool for physical attacks and provide new insights into the security under an active fault attacker.

Physical characteristics of electronic devices, leaking secret and sensitive information to an adversary with physical access, pose a long-known threat to cryptographic hardware implementations. Among a variety of proposed countermeasures against such Side-Channel Analysis attacks, masking has emerged as a promising, but often costly, candidate. Furthermore, the manual realization of masked implementations has proven error-prone and often introduces flaws, possibly resulting in insecure circuits. In the context of automatic masking, a new line of research emerged, aiming to replace each physical gate with a secure gadget that fulfills well-defined properties, guaranteeing security when interconnected to a large circuit. Unfortunately, those gadgets introduce a significant amount of additional overhead into the design, in terms of area, latency, and randomness requirements.In this work, we present a novel approach to reduce the demands for randomness in such gadget-composed circuits by reusing randomness across gadgets while maintaining security in the probing adversary model. To this end, we embedded the corresponding optimization passes into an Electronic Design Automation toolchain, able to construct, optimize, and implement masked circuits, starting from an unprotected design. As such, our security-aware optimization offers an additional building block for existing or new Electronic Design Automation frameworks, where security is considered a first-class design constraint.

Physical attacks, including passive Side-Channel Analysis and active Fault Injection Analysis, are considered among the most powerful threats against physical cryptographic implementations. These attacks are well known and research provides many specialized countermeasures to protect cryptographic implementations against them. Still, only a limited number of combined countermeasures, i.e., countermeasures that protect implementations against multiple attacks simultaneously, were proposed in the past. Due to increasing complexity and reciprocal effects, design of efficient and reliable combined countermeasures requires longstanding expertise in hardware design and security. With the help of formal security specifications and adversary models, automated verification can streamline development cycles, increase quality, and facilitate development of robust cryptographic implementations.In this work, we revise and refine formal security notions for combined protection mechanisms and specifically embed them in the context of hardware implementations. Based on this, we present the first automated verification framework that can verify physical security properties of hardware circuits with respect to combined physical attacks. To this end, we conduct several case studies to demonstrate the capabilities and advantages of our framework, analyzing secure building blocks (gadgets), S-boxes build from Toffoli gates, and the ParTI scheme. For the first time, we reveal security flaws in analyzed structures due to reciprocal effects, highlighting the importance of continuously integrating security verification into modern design and development cycles.