Securing integrated circuits against counterfeiting through logic locking presents the fundamental challenge of protecting a locking key from physical, Boolean satisfiability (SAT)-based, and structural threats. Prior research has mainly focused on enhancing logic locking to thwart SAT-based and structural attacks but overlooked the necessity of robust physical security. Our work introduces a novel approach: a logic locking scheme utilizing the nonvolatile properties of nanomagnet logic (NML) to provide comprehensive protection. Polymorphic NML minority gates along with conventional locking techniques fortify the locking key against SAT-based and structural threats, while a protective shield, inducing strain in the nanomagnets, offers physical security via a self-destruct mechanism. Although the NML system improves physical security and preserves security against SAT-based and structural attacks, it suffers from drawbacks related to limited reliability and speed, which result in a notable security overhead cost. Consequently, we propose a hybrid CMOS/NML logic locking approach in which NML islands are integrated into a predominantly CMOS-based system. This hybrid solution continues to deliver security against physical, SAT-based, and the known structural attacks while minimizing the associated overhead. We evaluate the security of such hybrid systems against conventional and physically enhanced SAT attacks. The hybrid logic systems are found to retain the security against conventional SAT-based attacks. We further find that these hybrid logic systems are also robust to physically enhanced SAT attacks in which the attacker has access to all internal electrical signals. These hybrid logic systems are thus shown to provide security against all known physical attacks as well as SAT-based attacks, with minimal efficiency tradeoffs resulting from the use of emerging technologies.

Naïve Bayesian inference enables classification or prediction of an event given observations of potentially contradictory evidences, and is particularly intriguing in power-limited contexts where a neural network would be inappropriate. It has been demonstrated that Müller C-Elements (CEs), when applied within the stochastic computing paradigm, natively calculate Bayes’ theorem, which can be used to perform naïve Bayesian inference, enabling energy-efficient data fusion. However, this concept has never previously been demonstrated experimentally. We therefore report the first fabricated stochastic Bayesian inference engine implemented with CEs. Our measurements of four distinct CE structures experimentally demonstrate tradeoffs among accuracy, efficiency, robustness, and speed. Our chip achieves better power-delay product (PDP) than other proposed stochastic Bayesian engines with CEs, and is the first such chip to be fabricated.

The successful logic locking of integrated circuits requires that the system be secure against both algorithmic and physical attacks. In order to provide resilience against imaging techniques that can detect electrical behavior, we recently proposed an approach for physically and algorithmically secure logic locking with strain-protected nanomagnet logic (NML). While this NML system exhibits physical and algorithmic security, the fabrication imprecision, noise-related errors, and slow speed of NML incur a significant security overhead cost. In this paper, we therefore propose a hybrid CMOS/NML logic locking solution in which NML islands provide security within a system primarily composed of CMOS, thereby providing physical and algorithmic security with minimal overhead. In addition to describing this proposed system, we also develop a framework for device/system co-design techniques that consider trade-offs regarding the efficiency and security.

Prevention of integrated circuit counterfeiting through logic locking faces the fundamental challenge of securing an obfuscation key against both physical and algorithmic threats. Previous work has focused on strengthening the logic encryption to protect the key against algorithmic attacks, but failed to provide adequate physical security. In this work, we propose a logic locking scheme that leverages the non-volatility of the nanomagnet logic (NML) family to achieve both physical and algorithmic security. Polymorphic NML minority gates protect the obfuscation key against algorithmic attacks, while a strain-inducing shield surrounding the nanomagnets provides physical security via a self-destruction mechanism.

The development of beyond-CMOS technologies with alternative basis logic functions necessitates the introduction of novel design automation techniques. In particular, recently proposed computing systems based on memristors and bilayer avalanche spin-diodes both provide asymmetric functions as basis logic gates - the implication and inverted-input AND, respectively. This article therefore proposes a method by which Karnaugh maps can be directly applied to systems with asymmetric basis logic functions. A set of identities is defined for these memristor and spintronic logic functions, enabling the formal demonstration of the Karnaugh map method and an explanation of the proposed technique. This method thus, enables the direct minimization of spintronic and memristive logic circuits without translation to conventional Boolean algebra, facilitating the further development of these novel computing paradigms. Preliminary analyses demonstrate that this Karnaugh map minimization approach can provide a 28 percent reduction in step count as compared to previous manual optimization.