Fault attack hardware Trojan detection method based on ring oscillator
暂无分享,去创建一个
Ning Wu | Fang Zhou | Fen Ge | Muhammad Rehan Yahya | Jinbao Zhang | Qiangjia Bi | Ning Wu | Qiangjia Bi | Fang Zhou | Fen Ge | Jinbao Zhang | M. R. Yahya
[1] Wei He,et al. Multiple Fault Attack on PRESENT with a Hardware Trojan Implementation in FPGA , 2015, 2015 International Workshop on Secure Internet of Things (SIoT).
[2] Mark Mohammad Tehranipoor,et al. New design strategy for improving hardware Trojan detection and reducing Trojan activation time , 2009, 2009 IEEE International Workshop on Hardware-Oriented Security and Trust.
[3] Paris Kitsos,et al. On the effects of ring oscillator length and hardware Trojan size on an FPGA-based implementation of AES , 2017, Microprocess. Microsystems.
[4] Christos A. Papachristou,et al. MERO: A Statistical Approach for Hardware Trojan Detection , 2009, CHES.
[5] Berk Sunar,et al. Trojan Detection using IC Fingerprinting , 2007, 2007 IEEE Symposium on Security and Privacy (SP '07).
[6] Bruno Rouzeyre,et al. On the limitations of logic testing for detecting Hardware Trojans Horses , 2015, 2015 10th International Conference on Design & Technology of Integrated Systems in Nanoscale Era (DTIS).
[7] Yongqiang Lyu,et al. A Survey of Hardware Trojan Detection, Diagnosis and Prevention , 2015, 2015 14th International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics).
[8] Chong Hee Kim,et al. Differential Fault Analysis against AES-192 and AES-256 with Minimal Faults , 2010, 2010 Workshop on Fault Diagnosis and Tolerance in Cryptography.
[9] Debdeep Mukhopadhyay,et al. One Plus One is More than Two: A Practical Combination of Power and Fault Analysis Attacks on PRESENT and PRESENT-Like Block Ciphers , 2017, 2017 Workshop on Fault Diagnosis and Tolerance in Cryptography (FDTC).
[10] Nozomu Togawa,et al. A Hardware-Trojan Classification Method Using Machine Learning at Gate-Level Netlists Based on Trojan Features , 2017, IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences.
[11] Mahmoud Al-Qutayri,et al. A fault attack countermeasure for ECC processor using One-Hot RSD encoding , 2014, 2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS).
[12] Roshni Shende,et al. A side channel based power analysis technique for hardware trojan detection using statistical learning approach , 2016, 2016 Thirteenth International Conference on Wireless and Optical Communications Networks (WOCN).
[13] Xin Xie,et al. Hardware Trojans classification based on controllability and observability in gate-level netlist , 2017, IEICE Electron. Express.
[14] Qi Cui,et al. Hardware Trojan Detection Based on Cluster Analysis of Mahalanobis Distance , 2016, 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC).
[15] Tongsheng Xia,et al. Sensitivity analysis of ring oscillator based hardware Trojan detection , 2017, 2017 IEEE 17th International Conference on Communication Technology (ICCT).
[16] Richard J. Lipton,et al. On the Importance of Checking Cryptographic Protocols for Faults (Extended Abstract) , 1997, EUROCRYPT.
[17] Debdeep Mukhopadhyay,et al. Differential Fault Analysis of the Advanced Encryption Standard Using a Single Fault , 2011, WISTP.
[18] Mark Mohammad Tehranipoor,et al. RON: An on-chip ring oscillator network for hardware Trojan detection , 2011, 2011 Design, Automation & Test in Europe.
[19] Jianye Wang,et al. Temperature-variation-based hardware Trojan detection through ring oscillator , 2016 .
[20] Osman Hasan,et al. Power profiling of microcontroller's instruction set for runtime hardware Trojans detection without golden circuit models , 2017, Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017.
[21] Bruno Rouzeyre,et al. Protection Against Hardware Trojans With Logic Testing: Proposed Solutions and Challenges Ahead , 2018, IEEE Design & Test.
[22] Andreas Mauthe,et al. Power Consumption Profiling Using Energy Time-Frequency Distributions in Smart Grids , 2015, IEEE Communications Letters.
[23] Irith Pomeranz,et al. A measure of quality for n-detection test sets , 2004, IEEE Transactions on Computers.
[24] Wei He,et al. Supervised and unsupervised machine learning for side-channel based Trojan detection , 2016, 2016 IEEE 27th International Conference on Application-specific Systems, Architectures and Processors (ASAP).