ACM Journal on Emerging Technologies in Computing Systems最新文献

Advances in quantum computing have urged the need for cryptographic algorithms that are low-power, low-energy, and secure against attacks that can be potentially enabled. For this post-quantum age, different solutions have been studied. Code-based cryptography is one feasible solution whose hardware architectures have become the focus of research in the NIST standardization process and has been advanced to the final round (to be concluded by 2022–2024). Nevertheless, although these constructions, e.g., McEliece and Niederreiter public key cryptography, have strong error correction properties, previous studies have proved the vulnerability of their hardware implementations against faults product of the environment and intentional faults, i.e., differential fault analysis. It is previously shown that depending on the codes used, i.e., classical or reduced (using either quasi-dyadic Goppa codes or quasi-cyclic alternant codes), flaws in error detection could be observed. In this work, efficient fault detection constructions are proposed for the first time to account for such shortcomings. Such schemes are based on regular parity, interleaved parity, and two different cyclic redundancy checks (CRC), i.e., CRC-2 and CRC-8. Without losing the generality, we experiment on the McEliece variant, noting that the presented schemes can be used for other code-based cryptosystems. We perform error detection capability assessments and implementations on field-programmable gate array Kintex-7 device xc7k70tfbv676-1 to verify the practicality of the presented approaches. To demonstrate the appropriateness for constrained embedded systems, the performance degradation and overheads of the presented schemes are assessed.

One of the essential elements of computing is the memory element. Flip-flops form an integral part of a System-on-Chip (SoC) and consume most of the area on the die. To meet the high-speed performance demands by the data-intensive applications such as artificial intelligence, cloud computing, and machine learning, we propose to integrate memory with the logic to get built-in memory Logic circuits that operate based on the crosstalk computing logic. These circuits are called Crosstalk Built-in Memory Logic (CBML) circuits, which exploit the detrimental interconnect crosstalk and astutely turn this unwanted effect into a computing principle with embedded memory. By virtue of our novel CBML circuit technique, the logic is computed, and the result is stored intrinsically within these complex circuits. The stored values will be retained irrespective of the change in input until the next logic evaluation cycle. This neoteric embedding of memory in logic provides high-speed operation with a reduced number of transistors. In this article, we have manifested the built-in memory feature of the complex CBML circuits using 16 nanometer (nm) PTM models in HSPICE. Benchmarking is performed by comparing with the equivalent static CMOS circuits to compare the number of transistors, power, and performance. It is observed that the number of transistors consumed by CBML 4-bit Full-Adder (the key element prevalent in Arithmetic circuits, e.g., ALU, Counters) is up to 46% less, and performance is improved by 27% over the equivalent CMOS circuits. This circuit serves as an example of a large-scale CBML circuit. Also, the performance improvement achieved by other circuits such as 3-input AND and the CARRY logic is up to 60% along with a 40% reduction in the number of transistors. CBML circuits have the potential to pave the way for special high-speed macros with specifically engineered structures.

We propose AccHashtag, the first framework for high-accuracy detection of fault-injection attacks on Deep Neural Networks (DNNs) with provable bounds on detection performance. Recent literature in fault-injection attacks shows the severe DNN accuracy degradation caused by bit flips. In this scenario, the attacker changes a few DNN weight bits during execution by injecting faults to the dynamic random-access memory (DRAM). To detect bit flips, AccHashtag extracts a unique signature from the benign DNN prior to deployment. The signature is used to validate the model’s integrity and verify the inference output on the fly. We propose a novel sensitivity analysis that identifies the most vulnerable DNN layers to the fault-injection attack. The DNN signature is constructed by encoding the weights in vulnerable layers using a low-collision hash function. During DNN inference, new hashes are extracted from the target layers and compared against the ground-truth signatures. AccHashtag incorporates a lightweight methodology that allows for real-time fault detection on embedded platforms. We devise a specialized compute core for AccHashtag on field-programmable gate arrays (FPGAs) to facilitate online hash generation in parallel to DNN execution. Extensive evaluations with the state-of-the-art bit-flip attack on various DNNs demonstrate the competitive advantage of AccHashtag in terms of both attack detection and execution overhead.

This article proposes an electrical analysis of a new defect mechanism, to be named as b-open defect, which may occur in nanometer technologies due to the use of the Self-Aligned Double Patterning (SADP) technique. In metal lines making use of the SADP technique, a single dust particle may cause the simultaneous occurrence of a bridge defect and an open defect. When the two defects impact the same gates, the electrical effects of the bridge and the open combine and exhibit a new specific electrical behavior; we call this new defect behavior a b-open. As a consequence, existing test generation methodologies may miss defect detection. The electrical behavior of the b-open defect is first analyzed graphically and then validated through extensive SPICE simulations. The test pattern conditions to detect the b-open defect are finally determined, and it is shown that the b-open defect requires specific test generation.

Cryptography hardware is vulnerable to side-channel (SC) attacks on power supply current flow and electromagnetic (EM) emission. This article proposes simulation-based power and EM side-channel leakage analysis (SCLA) techniques on a cryptographic integrated circuit (IC) chip in system level assembly. SCLA measures SC leakage metrics including T-score, SC leakage score, and the number of measurement traces to disclosure, leveraged by a secure system-on-chip design flow toward SC attack resiliency and SC leakage sign off. Power SCLA features the tracking of security sensitive registers within cryptographic logic paths and the automatic assignments of probe points on associated physical power nets. Power supply current traces are efficiently simulated for the large set of input payloads, with direct vector-based and vector-less random switching controls. EM SCLA evaluates magnetic fields created by every piece of metal wiring in metal stacks where power supply current of cryptographic processing flows. The EM emission and EM SCLA from the backside Si surface of an IC chip in flip-chip packaging are experimentally examined with a 0.13 μm test chip. The proposed simulation-based SCLA exhibits the SC leakage metrics of on-chip location and direction dependency as accurately as in the measurements.

Molecular Field-Coupling Nanocomputing (FCN) is one of the most promising technologies for overcoming Complementary Metal Oxide Semiconductor (CMOS) scaling issues. It encodes the information in the charge distribution of nanometric molecules and propagates it through local electrostatic intermolecular interaction. This technology promises very high speed at ambient temperatures with minimal power dissipation. The main research focus on molecular FCN is currently either on single-molecule low-level analysis or circuit design based on naïve assumptions. We aim to fill this gap, assessing the potential and feasibility of FCN. We present a bottom-up analysis and design framework that starts from the physical characterization of molecular and technological parameters and enables physical-aware FCN designs. The framework explicitly considers molecular physics, allowing the designer to tame the molecular interaction to ensure the computational capabilities of the final device. The framework permits studying possible physical effects that create cross-implications and correlations among physical and system-level layers considering possible behavior variability. We characterize and verify molecular propagation in increasingly structured layouts to design complex arithmetic circuits. The results highlight molecular FCN advantages, especially in area occupation, and provide valuable quantitative feedback to designers and technologists to support the assessment of molecular FCN and the realization of an eventual prototype.