RTNA: Securing SOC architectures from confidentiality attacks at runtime using ART1 neural networks
26 Jun 2015-pp 1-6
TL;DR: An intelligent architecture, Runtime Trust Neural Architecture (RTNA) based on Adaptive Resonance Theory (ART 1) neural network, which when incorporated with the SOC architecture can prevent it at runtime from being compromised confidentially.
Abstract: With the entry into the embedded domain, security of SOC architectures has become an arena of importance. However, complexity and cost factors have forced us to outsource the VLSI design phases across the globe. Such sites may not be trusted and threat lies in the introduction of malicious intrusions at any stage of the design flow. Such malicious intrusions, also known as Hardware Trojan Horses (HTH) remain dormant during the testing phase but get triggered at runtime and threaten the integrity and confidentiality of the chip. In this paper, we focus on threat to confidentiality. HTH threatens the confidentiality of such chips by leaking the secret information at runtime. We propose an intelligent architecture, Runtime Trust Neural Architecture (RTNA) based on Adaptive Resonance Theory (ART 1) neural network, which when incorporated with the SOC architecture can prevent it at runtime from being compromised confidentially. Low area and low power overhead of our proposed RTNA on practical crypto SOC architectures as obtained in the experimental results confirm its practical implementation. Hardware implementation of trust generation at runtime, use of unsupervised learning and use of an intelligent architecture are the novelties of this work.
Citations
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01 Jan 2021
TL;DR: In this paper, the authors proposed a method to detect power dissipation attacks that may affect the green computing factor of a system or may drain the power budget of the system and cause early expiry of the computer system.
Abstract: Ensuring security for computer systems is of paramount importance. Analyzing various forms of attacks and defining strategies to prevent them is essential to generate trust among users. In general, to make a system reliable, system designers need to satisfy the basic three requirements, i.e. ensure confidentiality or prevent unauthorized observing of data or information, ensure integrity or prevent unauthorized change of data and ensure availability or facilitate authorized access to information or data at any instant of time and generate proper results within time. These three are commonly known as the CIA requirements [BT18]. However, with time, new attacks have arose like power dissipation attacks that may affect the green computing factor of a system or may drain the power budget of the system and cause early expiry of the system [Guh20, GMSC20]. Hence, it is the responsibility of system designers to analyze new and potential forms of threats that may arise with time and develop security strategies to mitigate them.
01 Jan 2021
TL;DR: In this paper, the authors present passive threats that do not cause direct damage by jeopardizing operations and generating erroneous results or causing stoppage of operations or even does not delay real-time operations to cause a deadline miss.
Abstract: Passive is the threat when system confidentiality is at stake. Such threats do not cause direct damage by jeopardizing operations and generating erroneous results or causing stoppage of operations or even does not delay real time operations to cause a deadline miss. Hence, such threats are passive in nature. This involves leakage of secret information to adversaries [LJM13, GSC17a, GSC15]. For example, the secret key that is associated with cryptographic operations by a genuine user may be leaked to an adversary.
06 Sep 2022
References
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TL;DR: A classification of hardware Trojans and a survey of published techniques for Trojan detection are presented.
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.
1,227 citations
TL;DR: 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, which opens up the possibility of applying ART systems to more general problems of adaptively processing large abstract information sources and databases.
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. >
1,217 citations
"RTNA: Securing SOC architectures fr..." refers background in this paper
...ART [25], [26] is a neural network which facilitates autonomous learning in a complex environment....
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...AES [25] is a 128 bit block non- Feistel cipher....
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...DES [25] is a 64 bit block cipher consisting of 16 Feistel rounds along with a key generation module and two permutation modules....
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...Adaptive Resonance Theory (ART1) neural networks [25], [26] exhibit unsupervised learning in an unknown environment....
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01 Dec 1987
TL;DR: In this article, the stability-plasticity dilemma and Adaptive Resonance Theory are discussed in the context of self-organizing learning and recognition systems, and the three R's: Recognition, Reinforcement, and Recall.
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.
1,196 citations
Book•
01 Jan 2015
TL;DR: This book includes the following chapters: Introduction to Modern Symmetric-Key Ciphers, Mathematics of Cryptography, and Message Integrity and Message Authentication, and Security at the Network Layer: IPSec.
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.
854 citations
15 Jul 2014
TL;DR: The threat of hardware Trojan attacks is analyzed; attack models, types, and scenarios are presented; different forms of protection approaches are discussed; and emerging attack modes, defenses, and future research pathways are described.
Abstract: Security of a computer system has been traditionally related to the security of the software or the information being processed. The underlying hardware used for information processing has been considered trusted. The emergence of hardware Trojan attacks violates this root of trust. These attacks, in the form of malicious modifications of electronic hardware at different stages of its life cycle, pose major security concerns in the electronics industry. An adversary can mount such an attack with an objective to cause operational failure or to leak secret information from inside a chip-e.g., the key in a cryptographic chip, during field operation. Global economic trend that encourages increased reliance on untrusted entities in the hardware design and fabrication process is rapidly enhancing the vulnerability to such attacks. In this paper, we analyze the threat of hardware Trojan attacks; present attack models, types, and scenarios; discuss different forms of protection approaches, both proactive and reactive; and describe emerging attack modes, defenses, and future research pathways.
588 citations