Hardware Trojan Detection and Mitigation in NoC using Key authentication and Obfuscation Techniques

P, Thejaswini; G, Vivekananda; H, Anu; Priya, R; S, Krishna Prasad B; Nischay, M

doi:10.24003/emitter.v10i2.716

Cited by 2 publications

(2 citation statements)

References 25 publications

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“…Thejaswini et al [10] present an HT detection and mitigation approach using obfuscation and key-based authentication. The authors aim to prevent illegal transactions between routers, protecting the NoC against packet misrouting and information leakage.…”

Section: Related Workmentioning

confidence: 99%

“…MCSoCs are susceptible to various attacks, such as hardware Trojans (HT), side channel attacks (SCA), denial of service (DoS), and spoofing [6]. Current security methods in MCSoCs include the implementation of firewalls [7], secure routing algorithms [8], encryption [9], authentication [10], anomaly detection [11], among others. These proposals focus on mitigating a single type of attack rather than seeking to create an integrated security framework.…”

Section: Introductionmentioning

confidence: 99%

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A Comprehensive Framework for Systemic Security Management in NoC-Based Many-Cores

Faccenda,

Comarú,

Caimi

et al. 2023

IEEE Access

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Many-core Systems-on-Chip (MCSoC) are increasingly used in various applications domains such as high-performance computing, embedded systems, and Internet of Things devices. As MCSoCs permeate various industries and applications, the potential consequences of security issues are becoming increasingly severe. Therefore, security is a fundamental design constraint, addressing vulnerabilities and protecting valuable data from threats. This requires the development of robust security mechanisms and countermeasures against potential threats. The reviewed works on security for MCSoCs addressed frameworks and mechanisms to treat different security threats. Despite these proposals, the integration of security mechanisms still needs to be improved, enabling a security manager to make decisions using monitoring data for mitigating threats more effectively. This integration is the primary goal of our work, aiming to create a comprehensive framework for security management. The framework adopts a Monitoring-Detection-Countermeasure loop. A distributed monitoring infrastructure detects suspicious behaviors, generating warnings to different system actors. These actors decide the warning severity, firing security countermeasures. Countermeasures may be local (e.g., discarding a packet) or taken at the system level (e.g., aborting a malicious application). The results use an MCSoC modeled at the RTL level, providing accuracy at the clock cycle (cc) level. Five different attack scenarios are evaluated, showing that the gap between attack detection and countermeasure takes less than one millisecond (15,000 cc at 100 MHz). The area overhead in the communication infrastructure corresponds to 48.8%. These results show that the framework can effectively manage the system's security while maintaining the performance of the applications.INDEX TERMS Countermeasures, Monitoring, NoC-based Many-cores, Security Framework.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Comprehensive Framework for Systemic Security Management in NoC-Based Many-Cores

Faccenda,

Comarú,

Caimi

et al. 2023

IEEE Access

View full text Add to dashboard Cite

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Improving Hardware Trojan Detection with Transformer-Based Power Analysis

Nasr,

shenawy,

Mohamed

et al. 2024

Preprint

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The prevalence of hardware trojans (HTs) poses a significant threat to the integrity and security of Integrated Circuits (ICs). Rule-based Hardware Trojan Detection (HTD) techniques are limited in their effectiveness and scalability. Many domains such as Natural Language Processing (NLP), and cybersecurity are experiencing a surge in automation with the aid of modern Generative Artificial Intelligence (GenAI) techniques such as Generative pre-trained transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), which are applied in Large Language Models (LLMs). In HTD, transformers have only recently started to receive traction. This paper proposes a novel non-destructive golden-chip free transformer-based HTD framework. The proposed framework is applied to Power Side-Channel (PSC) data. Modern generative AI techniques such as GPT, BERT, and transformers are exploited to solve the HTD problem. The proposed framework combines the power of transformer-based networks with time-series side-channel analysis to achieve efficient and accurate HTD. The side-channel data are processed by different transformer networks, including GPT, BERT, and full transformer models to classify the trojan into three main categories: Enabled, Disabled, and Triggered HTs. The proposed framework effectively analyses side-channel measurements, accurately detecting abnormal IC behaviours. The experimental results demonstrated promising and superior performance, achieving an accuracy of 87.74% in HT detection compared with existing frameworks.

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Hardware Trojan Detection and Mitigation in NoC using Key authentication and Obfuscation Techniques

Cited by 2 publications

References 25 publications

A Comprehensive Framework for Systemic Security Management in NoC-Based Many-Cores

A Comprehensive Framework for Systemic Security Management in NoC-Based Many-Cores

Improving Hardware Trojan Detection with Transformer-Based Power Analysis

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