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.

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.

Shrinking transistor sizes are jeopardizing the reliability of runtime reconfigurable Field Programmable Gate Arrays (FPGAs), making them increasingly sensitive to aging effects such as Negative Bias Temperature Instability (NBTI). This paper introduces a reliability-aware floorplanner which is tailored to multi-context, coarse-grained, runtime reconfigurable architectures (CGRRAs) and seeks to extend their Mean Time to Failure (MTTF) by balancing the usage of processing elements (PEs). The proposed method is based on a Mixed Integer Linear Programming (MILP) formulation, the solution to which produces appropriately-balanced mappings of workload to PEs on the reconfigurable fabric, thereby mitigating aging-induced lifetime degradation. Results demonstrate that, as compared to the default reliability-unaware floorplanning solutions, the proposed method achieves an average MTTF increase of 2.5× without introducing any performance degradation.

A recently proposed TRAnsistor-level Programmable (TRAP) fabric can enable seamless on-die integration of high-density reconfigurable logic with custom ICs. However, state-of-the-art CAD tools are developed for either ASICs or FPGAs and do not support the new architecture. To this end, we present CASPER − a novel CAD framework for implementing designs on the TRAP fabric. CASPER begins with characterizing an ASIC-esque cell library in order to leverage the industry-leading logic synthesis tools for TRAP. We then systematically remodel the TimberWolf and the Versatile Place and Route (VPR) tools to facilitate TRAP-specific design placement and routing, respectively. In addition, we develop a robust programming bitstream generation tool for TRAP. Lastly, we fabricate a 65nm prototype TRAP chip and implement ten ISCAS-85/MCNC benchmark circuits on it. Our evaluation results validate the proposed CAD framework and provide a comparative overhead analysis between TRAP and FPGA.

A recently introduced TRAnsistor-level Programmable fabric (TRAP) has demonstrated great promise towards seamless unification of high-density reconfigurable logic with Application-Specific Integrated Circuits (ASICs). However, practical deployment of TRAP relies on the development of a comprehensive mechanism for detecting manufacturing defects. Unfortunately, the state-of-the-art test schemes are developed either for ASICs or for Field-Programmable Gate Arrays (FPGAs) and do not support this new transistor-level architecture. To address this limitation, we present a novel application-agnostic test methodology specifically tailored to the TRAP fabric. We first introduce a multi-phase, cascadable scheme to efficiently test the programmable transistors in TRAP’s Logic Elements (LEs). Then, we define the required test patterns for verifying the correct functionality of the built-in D flip-flop, full-adder, and multiplexer of each LE. Next, we present a systematic approach for testing the interconnect network. Lastly, we discuss the limitations in testing the memory cells used for storing the TRAP programming bits and we propose design modifications for improving test coverage.

Widespread adoption of the fabless business model and utilization of third-party foundries have increased the exposure of sensitive designs to security threats such as intellectual property (IP) theft and integrated circuit (IC) counterfeiting. As a result, concerted interest in various design obfuscation schemes for deterring reverse engineering and/or unauthorized reproduction and usage of ICs has surfaced. To this end, in this paper we present a novel mechanism for structurally obfuscating sensitive parts of a design through post-fabrication TRAnsistor-level Programming (TRAP). We introduce a transistor-level programmable fabric and we discuss its unique advantages towards design obfuscation, as well as a customized CAD framework for seamlessly integrating this fabric in an ASIC design flow. We theoretically analyze the complexity of attacking TRAP-obfuscated designs through both brute-force and intelligent SAT-based attacks and we present a silicon implementation of a platform for experimenting with TRAP. Effectiveness of the proposed method is evaluated through selective obfuscation of various modules of a modern microprocessor design. Results corroborate that, as compared to an FPGA implementation, TRAP-based obfuscation offers superior resistance against both brute-force and oracle-guided SAT attacks, while incurring an order of magnitude less area, power and delay overhead.

The protection of Intellectual Property (IP) has emerged as one of the most serious areas of concern in the semiconductor industry. To address this issue, we present a method and architecture to map selective portions of a design, given as a behavioral description for High-Level Synthesis (HLS) to a high-security embedded Field-Programmable Gate Array (eFPGA). In this manner, only the end-user has access to the full functionality of the chip. Using six benchmark circuits, we show that our approach is effective. In all cases, the Time-To-Break (TTB) is so long (at least 8 million hours) that for all practical purposes the designs are secure while incurring area overheads of around 5%. Further, latencies were only slightly increased, while the computation times are under one minute.

The paradigm shift from planar (two dimensional (2D)) to vertical (three-dimensional (3D)) models has placed the NAND flash technology on the verge of a design evolution that can handle the demands of next-generation storage applications. However, it also introduces challenges that may obstruct the realization of such 3D NAND flash. Specifically, we observed that the fast threshold drift (fast-drift) in a charge-trap flash-based 3D NAND cell can make it lose a critical fraction of the stored charge relatively soon after programming and generate errors. In this work, we first present an elastic read reference ( V Ref ) scheme (ERR) for reducing such errors in ReveNAND—our fast-drift aware 3D NAND design. To address the inherent limitation of the adaptive V Ref , we introduce a new intra-block page organization (hitch-hike) that can enable stronger error correction for the error-prone pages. In addition, we propose a novel reinforcement-learning-based smart data refill scheme (iRefill) to counter the impact of fast-drift with minimum performance and hardware overhead. Finally, we present the first analytic model to characterize fast-drift and evaluate its system-level impact. Our results show that, compared to conventional 3D NAND design, our ReveNAND can reduce fast-drift errors by 87%, on average, and can lower the ECC latency and energy overheads by 13× and 10×, respectively.

Accurate characterization of real device samples is essential for understanding the true potential of the emerging non-volatile memories (NVMs) and identifying their optimal placement in the memory hierarchy. Even though, NVM devices are now available from different manufacturers, lack of an appropriate NVM controller and evaluation platform in the public domain is the main challenge in extracting empirical data from these real devices. In this paper, we present Open-NVM, an open-sourced, highly configurable FPGA based evaluation/characterization platform for various NVM technologies. Through our OpenNVM, this work reveals important low-level NVM characteristics, including i) static and dynamic latency disparity, ii) error rate variation, iii) power consumption behavior, vi) interrelationship between frequency and NVM operational current. In addition, we also examine state-of-the-art write-once-memory (WOM) codes on a real NVM device and study diverse system-level performance impacts based on our findings. All FPGA source code and detailed information of our hardware design is ready to be open-sourced and downloaded for free.