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Experimental analysis of a ring oscillator network for hardware trojan detection in a 90nm ASIC

Published: 05 November 2012 Publication History

Abstract

The modern integrated circuit (IC) manufacturing process has exposed chip designers to hardware Trojans which threaten circuits bound for critical applications. This paper details the implementation and analysis of a novel ring oscillator network technique for Trojan detection in an application specific integrated circuit (ASIC). The ring oscillator network serves as a power supply monitor by detecting fluctuations in characteristic frequencies due to malicious modifications (i.e. hardware Trojans) in the circuit under authentication. The ring oscillator network was implemented and fabricated in 40 IBM 90nm ASICs with controlled hardware Trojans. This work analyzes the impact of Trojans with varied partial activity, area, and location on the proposed ring oscillator structure and demonstrates that stealthy Trojans can be efficiently detected with this technique even while obfuscated by process variations, background noise, and environment noise.

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    cover image ACM Conferences
    ICCAD '12: Proceedings of the International Conference on Computer-Aided Design
    November 2012
    781 pages
    ISBN:9781450315739
    DOI:10.1145/2429384
    • General Chair:
    • Alan J. Hu
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 05 November 2012

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    Author Tags

    1. IC trust
    2. hardware Trojan detection
    3. on-chip measurement
    4. process variations

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    Overall Acceptance Rate 457 of 1,762 submissions, 26%

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    • (2024)Sensors for Remote Power Attacks: New Developments and Challenges2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC)10.1109/ASP-DAC58780.2024.10473890(333-340)Online publication date: 22-Jan-2024
    • (2023)Circuit Topology-Aware Vaccination-Based Hardware Trojan DetectionIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.323444042:9(2852-2862)Online publication date: Sep-2023
    • (2023)Unsupervised IC Security with Machine Learning for Trojan Detection2023 IEEE 66th International Midwest Symposium on Circuits and Systems (MWSCAS)10.1109/MWSCAS57524.2023.10406045(20-24)Online publication date: 6-Aug-2023
    • (2022)A Primer on Hardware Trojans including Platform Specific Attacks and Machine Learning for DetectionSoutheastCon 202210.1109/SoutheastCon48659.2022.9763966(479-486)Online publication date: 26-Mar-2022
    • (2022)A comprehensive survey of physical and logic testing techniques for Hardware Trojan detection and preventionJournal of Cryptographic Engineering10.1007/s13389-022-00295-w12:4(495-522)Online publication date: 16-Jul-2022
    • (2021)Side-channel Analysis for Hardware Trojan Detection using Machine Learning2021 IEEE International Test Conference India (ITC India)10.1109/ITCIndia52672.2021.9532888(1-6)Online publication date: 18-Jul-2021
    • (2021)Design of Hardware Trojans and its Impact on CPS Systems: A Comprehensive Survey2021 IEEE International Symposium on Circuits and Systems (ISCAS)10.1109/ISCAS51556.2021.9401254(1-5)Online publication date: May-2021
    • (2020)Survey of Hardware Trojan Threats and Detection2020 International Symposium on Electromagnetic Compatibility - EMC EUROPE10.1109/EMCEUROPE48519.2020.9245675(1-5)Online publication date: 23-Sep-2020
    • (2020)Detecting Hardware Trojans by Monitoring Powersupply Noise Based on Ring Oscillator Network in FPGA2020 3rd International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)10.1109/AEMCSE50948.2020.00095(410-413)Online publication date: Apr-2020
    • (2020)Ingress of Threshold Voltage-Triggered Hardware Trojan in the Modern FPGA Fabric–Detection Methodology and MitigationIEEE Access10.1109/ACCESS.2020.29732608(31371-31397)Online publication date: 2020
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