RTNA: Securing SOC architectures from confidentiality attacks at runtime using ART1 neural networks

Abstract: The remarkable success of machine learning (ML) in a variety of research domains has inspired academic and industrial communities to explore its potential to address hardware Trojan (HT) attacks. While numerous works have been published over the past decade, few survey papers, to the best of our knowledge, have systematically reviewed the achievements and analyzed the remaining challenges in this area. To fill this gap, this article surveys ML-based approaches against HT attacks available in the literature. In particular, we first provide a classification of all possible HT attacks and then review recent developments from four perspectives, i.e., HT detection, design-for-security (DFS), bus security, and secure architecture. Based on the review, we further discuss the lessons learned in and challenges arising from previous studies. Despite current work focusing more on chip-layer HT problems, it is notable that novel HT threats are constantly emerging and have evolved beyond chips and to the component, device, and even behavior layers, therein compromising the security and trustworthiness of the overall hardware ecosystem. Therefore, we divide the HT threats into four layers and propose a hardware Trojan defense (HTD) reference model from the perspective of the overall hardware ecosystem, therein categorizing the security threats and requirements in each layer to provide a guideline for future research in this direction.

Abstract: A major issue of present age system on chip (SoC) designing is meeting of stringent time to market deadlines along with the reduction of various challenges faced during design. A significant strategy adopted in tackling such a problem is to procure different components or IPs (intellectual properties) of the SoC from different third party IP vendors (3PIPs). Such a technique targets independent working of the SoC components and removes the threat of the occurrence of malicious circuitry or Hardware Trojan Horse (HTH) having a distributed architecture. However, trustworthiness of the 3PIP vendors is a concern and possibility exists in the implantation of a HTH in the individual IPs procured from them. In this work, we analyze the effects of such Trojans, which may induce sudden unintentional delays at runtime, affecting the basic security principles of the SoC. We propose a self aware approach which works on the observe-decide-act (ODA) paradigm to counteract the scenario. Existing literature on hardware security generally focus on detection of anomaly, but is silent on organizing low level security mechanisms in such a manner that the high level objective of secure task completion is facilitated at run time. Our proposed methodology not only overcomes this limitation but also ensures security without tampering the IP designs. Experimental analysis is performed using AES crypto SoC architecture. Low overhead in area and power of the security elements as obtained in experimentation supports its applicability for practical SoC applications.

Abstract: Virtual instrumentation is a powerful tool that has been largely left unexplored in the domain of hardware security. It facilitates creation of automated tests to detect the presence of Trojans in a circuit thereby reducing the chance of human errors and the time required for testing. The presence of a stealthy Trojan in large VLSI circuits could lead to leakage of confidential information even in high-security applications such as defense equipment. Here, we propose the usage of virtual instrumentation to detect the presence of a delay-based Trojan in a circuit. Our results confirm that VI-based systems provide a cheap, self-sufficient, easy-to-use interface, and flexible scheme which can be easily modified to accommodate any VLSI circuit. This can also be used in other detection techniques without the need for use of complex systems.

Abstract: The rapid evolution of the embedded era has witnessed globalization for the design of SoC architectures in the semiconductor design industry. Though issues of cost and stringent marketing deadlines have been resolved in such a methodology, yet the root of hardware trust has been evicted. Malicious circuitry, a.k.a. Hardware Trojan Horse (HTH), is inserted by adversaries in the less trusted phases of design. A HTH remains dormant during testing but gets triggered at runtime to cause sudden active and passive attacks. In this work, we focus on the runtime passive threats based on the parameter delay. Nature-inspired algorithms offer an alternative to the conventional techniques for solving complex problems in the domain of computer science. However, most are optimization techniques and none is dedicated to security. We seek refuge to the crypsis behavior exhibited by geckos in nature to generate a runtime security technique for SoC architectures, which can bypass runtime passive threats of a HTH. An adaptive security intellectual property (IP) that works on the proposed security principles is designed. Embedded timing analysis is used for experimental validation. Low area and power overhead of our proposed security IP over standard benchmarks and practical crypto SoC architectures as obtained in experimental results supports its applicability for practical implementations.

Abstract: The semiconductor design industry of the embedded era has embraced the globalization strategy for system on chip (SoC) design. This involves incorporation of various SoC components or intellectual properties (IPs), procured from various third-party IP (3PIP) vendors. However, trust of an SoC is challenged when a supplied IP is counterfeit or implanted with a Hardware Trojan Horse. Both roots of untrust may result in sudden performance degradation at runtime. None of the existing hardware security approaches organize the behavior of the IPs at the low level, to ensure timely completion of SoC operations. However, real-time SoC operations are always associated with a deadline, and a deadline miss due to sudden performance degradation of any of the IPs may jeopardize mission-critical applications. We seek refuge to the stigmergic behavior exhibited in insect colonies to propose a decentralized self-aware security approach. The self-aware security modules attached with each IP works based on the Observe-Decide-Act paradigm and not only detects vulnerability but also organizes behavior of the IPs dynamically at runtime so that the high-level objective of task completion before a deadline is ensured. Experimental validation and low overhead of our proposed security modules over various benchmark IPs and crypto SoCs depict the prospects of our proposed mechanism.

Abstract: : Partial Contents: Attention and Expectation in Self-Organizing Learning and Recognition Systems; The Stability-Plasticity Dilemma and Adaptive Resonance Theory; Competitive Learning Models; Self-Stabilized Learning by an ART Architecture in an Arbitrary Input Environment; Attentional Priming and Prediction: Matching by the 2/3 Rule; Automatic Control of Hypothesis Testing by Attentional-Orienting Interactions; Learning to Recognize an Analog World; Invariant Visual Pattern Recognition; The Three R's: Recognition, Reinforcement, and Recall; Self-Stabilization of Speech Perception and Production Codes: New Light on Motor Theory; and Psychophysiological and Neurophysiological Predictions of ART.

Abstract: The adaptive resonance theory (ART) suggests a solution to the stability-plasticity dilemma facing designers of learning systems, namely how to design a learning system that will remain plastic, or adaptive, in response to significant events and yet remain stable in response to irrelevant events. ART architectures are discussed that are neural networks that self-organize stable recognition codes in real time in response to arbitrary sequences of input patterns. Within such an ART architecture, the process of adaptive pattern recognition is a special case of the more general cognitive process of hypothesis discovery, testing, search, classification, and learning. This property opens up the possibility of applying ART systems to more general problems of adaptively processing large abstract information sources and databases. The main computational properties of these ART architectures are outlined and contrasted with those of alternative learning and recognition systems. >

Abstract: Editor's note:Today's integrated circuits are vulnerable to hardware Trojans, which are malicious alterations to the circuit, either during design or fabrication. This article presents a classification of hardware Trojans and a survey of published techniques for Trojan detection.

Abstract: This book includes the following chapters : Introduction; Mathematics of Cryptography; Traditional Symmetric-Key Ciphers; Mathematics of Cryptography; Introduction to Modern Symmetric-Key Ciphers; Data Encryption Standard (DES); Advanced Encryption Standard (AES); Encipherment Using Modern Symmetric-Key Ciphers; Mathematics of Cryptography; Asymmetric-Key Cryptography; Message Integrity and Message Authentication; Cryptographic Hash Functions; Digital Signature; Entity Authentication; Key Management; Security at the Application Layer: PGP and S/MIME; Security at the Transport Layer: SSL and TLS; and Security at the Network Layer: IPSec.

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