Detection of Hardware Trojans in SystemC HLS Designs via Coverage-guided Fuzzing

被引:0
|
作者
Le, Hoang M. [1 ]
Grosse, Daniel [1 ,2 ]
Bruns, Niklas [2 ]
Drechsler, Rolf [1 ,2 ]
机构
[1] Univ Bremen, Inst Comp Sci, D-28359 Bremen, Germany
[2] DFKI GmbH, Cyber Phys Syst, D-28359 Bremen, Germany
来源
2019 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE) | 2019年
关键词
D O I
10.23919/date.2019.8714927
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
High-level Synthesis (HLS) is being increasingly adopted as a mean to raise design productivity. HLS designs, which can be automatically translated into RTL, are typically written in SystemC at a more abstract level. Hardware Trojan attacks and countermeasures, while well-known and well-researched for RTL and below, have been only recently considered for HLS. The paper makes a contribution to this emerging research area by proposing a novel detection approach for Hardware Trojans in SystemC HLS designs. The proposed approach is based on coverage-guided fuzzing, a new promising idea from software (security) testing research. The efficiency of the approach in identifying stealthy behavior is demonstrated on a set of open-source benchmarks.
引用
收藏
页码:602 / 605
页数:4
相关论文
共 50 条
  • [1] SPINALFUZZ: Coverage-Guided Fuzzing for SpinalHDL Designs
    Ruep, Katharina
    Grosse, Daniel
    2022 IEEE EUROPEAN TEST SYMPOSIUM (ETS 2022), 2022,
  • [2] Enhancing Coverage-Guided Fuzzing via Phantom Program
    Wu, Mingyuan
    Chen, Kunqiu
    Luo, Qi
    Xiang, Jiahong
    Qi, Ji
    Chen, Junjie
    Cui, Heming
    Zhang, Yuqun
    PROCEEDINGS OF THE 31ST ACM JOINT MEETING EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING, ESEC/FSE 2023, 2023, : 1037 - 1049
  • [3] REFuzz: A Remedy for Saturation in Coverage-Guided Fuzzing
    Lyu, Qian
    Zhang, Dalin
    Da, Rihan
    Zhang, Hailong
    ELECTRONICS, 2021, 10 (16)
  • [4] Coverage-guided Fuzzing for Feedforward Neural Networks
    Xie, Xiaofei
    Chen, Hongxu
    Li, Yi
    Ma, Lei
    Liu, Yang
    Zhao, Jianjun
    34TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE 2019), 2019, : 1162 - 1165
  • [5] RIFF: Reduced Instruction Footprint for Coverage-Guided Fuzzing
    Wang, Mingzhe
    Liang, Jie
    Zhou, Chijin
    Jiang, Yu
    Wang, Rui
    Sun, Chengnian
    Sun, Jiaguang
    PROCEEDINGS OF THE 2021 USENIX ANNUAL TECHNICAL CONFERENCE, 2021, : 147 - 159
  • [6] FOX: Coverage-guided Fuzzing as Online Stochastic Control
    She, Dongdong
    Storek, Adam
    Xie, Yuchong
    Kweon, Seoyoung
    Srivastava, Prashast
    Jana, Suman
    2024 IEEE/ACM INTERNATIONAL WORKSHOP ON SEARCH-BASED AND FUZZ TESTING, SBFT 2024, 2024, : 57 - 58
  • [7] TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing
    Odena, Augustus
    Olsson, Catherine
    Andersen, David G.
    Goodfellow, Ian
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 97, 2019, 97
  • [8] Coverage-guided fuzzing for deep reinforcement learning systems
    Wan, Xiaohui
    Li, Tiancheng
    Lin, Weibin
    Cai, Yi
    Zheng, Zheng
    JOURNAL OF SYSTEMS AND SOFTWARE, 2024, 210
  • [9] Tardis: Coverage-Guided Embedded Operating System Fuzzing
    Shen, Yuheng
    Xu, Yiru
    Sun, Hao
    Liu, Jianzhong
    Xu, Zichen
    Cui, Aiguo
    Shi, Heyuan
    Jiang, Yu
    IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2022, 41 (11) : 4563 - 4574
  • [10] RumFuzz: Coverage-guided Greybox Fuzzing with Reasonable Use of Memory
    Xu, Jiangyun
    Wang, Jinbo
    Ma, Yunyun
    Li, Lu
    Jia, Chang
    2024 IEEE 24TH INTERNATIONAL CONFERENCE ON SOFTWARE QUALITY, RELIABILITY AND SECURITY, QRS, 2024, : 526 - 535