Hardware trojan design on neural networks

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August undefined, 2024

WebMay 27, 2024 · IC design and production process is very complex, including several uncontrollable processes, such as design, manufacture, use, etc. Hardware Trojan can … WebOct 18, 2024 · These inserted Trojans are then detected using a machine-learning-based technique that employs a neural network. The designed neural network comprises 11 neurons and 2 neurons in the input layer and output layer respectively. The developed algorithm is then validated on benchmark circuits. The usage of neural networks for the …

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WebCurrently working as Physical Design Enginner in LTTS. • Completed certification in IC Design using cadence from Entuple and in Python from Coursera. • Worked on Pre-silicon verification of IC design against hardware trojans using Gate level Netlist, Deep learning with Generative Adversarial Network and Stacked Autoencoder Neural networks ... WebJun 14, 2024 · With the rising popularity of machine learning and the ever increasing demand for computational power, there is a growing need for hardware optimized … tom glaser uc davis

Hardware Trojan - GeeksforGeeks

WebNov 4, 2024 · As an extra circuit inserted into chip design, Hardware Trojan can achieve malicious functional changes, reliability reduction or secret information disclosure. ... Meanwhile, a large number of efficient algorithms and functions built by neural network are integrated . Since the system is a nonlinear system, the design is completed using a ... WebSep 26, 2024 · The existence of noise can weaken or even submerge the influence of hardware Trojan on the circuit, which makes the detection rate greatly reduced [1,2,3]. In this paper, a method of data de-noising preprocessing method based on wavelet transform is applied, and the hardware Trojan is tested by using neural network algorithm. WebMay 1, 2024 · As the effort required to train deep neural network models dramatically increased in recent years due to the high hardware requirement and time consumption, … tom glaser

Hardware Trojan Attacks on Neural Networks - arXiv

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WebOct 31, 2024 · The performance and concurrency testing of the deep neural network (DNN) model deployed in IoT devices are computed to validate the possibility of in-production implementation. By deploying the DNN model on two selected IoT gateways, we observed very promising results, with less than 30 kb/s increase in network bandwidth on … WebThis paper proposes a graph neural network-based Trojan detection framework to protect the RISC-V SoC platform written in SystemVerilog from intruding malicious logic. The study is under-construction and planned to be validated on the Ariane RISC-V CPU with several peripheral IPs in the experimental section. tom glasgowWebMay 1, 2024 · Hardware Trojan Design on Neural Networks. Abstract: Recent innovations and breakthroughs in deep neural networks have advanced or evolved many industries as well as human daily life. To facilitate the deployment of these models to edge devices, … tom glasgow komo

"WebThe use of hardware accelerators for convolutional neural networks (CNN) is on the rise due to the popularity of artificial intelligence in autonomous vehicles, industrial control … " - Hardware trojan design on neural networks

Hardware trojan design on neural networks

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WebMay 27, 2024 · IC design and production process is very complex, including several uncontrollable processes, such as design, manufacture, use, etc. Hardware Trojan can be inserted in these kinds of ... WebJan 13, 2024 · Convolutional Neural Network (CN N) among others [43], ... which mainly targets the malicious behaviour of Hardware Trojan insertion in the IC design process. First of all, during transferring ...

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WebJan 31, 2024 · TL;DR: GNN4TJ as discussed by the authors uses Graph Neural Network (GNN) to extract features from DFG, learn the circuit's behavior, and identify the presence of HT, in a fully automated pipeline. Abstract: The time to market pressure and resource constraints has pushed System-on-Chip (SoC) designers toward outsourcing the design … WebThis work introduces, for the ﬁrst time, hardware Trojan attacks in the scope of neural networks. To the best of our knowledge, the only other attack on a neural network in the hardware domain comes in the form of fault injection techniques on the parameters of a well-trained network [17]. Our attack deviates from this work, as we attempt to

WebJan 18, 2024 · Hardware Trojan detection using path delay fingerprint. In 2008 IEEE International workshop on hardware-oriented security and trust. IEEE, 51–57. Google … WebTitle: Training Neural Networks for Execution on Approximate Hardware Authors: Tianmu Li , Shurui Li , Puneet Gupta Subjects: Machine Learning (cs.LG) ; Hardware Architecture (cs.AR)

WebApr 28, 2016 · Master's degreeComputer Engineering3.82. 2016 - 2024. • Research: Hardware Security, hardware trojan detection and its … WebApr 10, 2024 · AI Software Engineer. Job in Orlando - Orange County - FL Florida - USA , 32885. Listing for: Intuitive Research and Technology. Full Time position. Listed on 2024 …

WebFeb 23, 2024 · Clements J, Lao Y (2024) Hardware trojan design on neural networks. In: 2024 IEEE international symposium on circuits and systems (ISCAS). IEEE, pp 1–5. …

WebHardware Trojan Detection using Graph Neural Networks. The globalization of the Integrated Circuit (IC) supply chain has moved most of the design, fabrication, and testing process from a single trusted entity to various untrusted third-party entities around the world. The risk of using untrusted third-Party Intellectual Property (3PIP) is the ... tom glassmanWebJohnLaw3742. Jun 1996 - Present26 years 11 months. New York City Metropolitan Area. • Create web sites (wireframes, design, digital imaging, copy writing, editing, photography, … tom glatz obitWebJul 1, 2024 · For instance, Trojan-net features derived from gate-level netlist are exploited by support vector machine [18] and multi-layer neural network [19]. Others apply gradient boosting [20 ... tom glatz obituaryWebJan 7, 2024 · This method focused on training a multi-layer neural network ML model, in IC design step itself and obtained 100% TPR. In ... Hardware trojan detection using deep … tom glaubWeband malicious presence of Trojan inside the design. Since hardware is a non-euclidean, structural type of data in nature, we use the graph data structure to represent the hardware design and generate the Data Flow Graph (DFG) for both RTL codes and gate-level netlists. We leverage Graph Neural Networks (GNN) to model the behavior of the circuit ... tom glassWebFeb 23, 2024 · Clements J, Lao Y (2024) Hardware trojan design on neural networks. In: 2024 IEEE international symposium on circuits and systems (ISCAS). IEEE, pp 1–5. Google Scholar Clements J, Lao Y (2024) Backdoor attacks on neural network operations. In: 2024 IEEE global conference on signal and information processing (GlobalSIP). tom glatzWebMay 26, 2024 · Hardware Trojan Detection using Graph Neural Networks. Abstract: The globalization of the Integrated Circuit (IC) supply chain has moved most of the design, fabrication, and testing process from a single trusted entity to various untrusted third party entities around the world. The risk of using untrusted third-Party Intellectual Property … tom glatzel