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Trojan

About: Trojan is a research topic. Over the lifetime, 2028 publications have been published within this topic receiving 33209 citations.


Papers
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Patent
24 May 2011
TL;DR: In this article, an antivirus in the client computer detects a computer network data stream generated by a Trojan program communicating with an associated malicious server computer by receiving a relevance pattern in a client computer.
Abstract: Computer network data streams generated by a Trojan program and its variants are detected by receiving a relevance pattern in a client computer. An antivirus in the client computer detects a computer network data stream from the Trojan program communicating with an associated malicious server computer. The antivirus checks the computer network data stream for network characteristics of the Trojan program and one or more of its variants indicated in the relevance pattern. The network characteristics may include the order that HTTP headers and/or commands appear in network communications from the Trojan program and its variants.

25 citations

Journal ArticleDOI
TL;DR: A clock-tree-concerned technique to detect the HTs on FPGA and a Trojan identifying approach which extracts the mathematical feature of obtained EM traces, i.e., 2-D principal component analysis (2DPCA) in this paper, and automatically isolates the Trojan-infected FPGAs from theTrojan-free ones by using a BP neural network.
Abstract: Nowadays, field programmable gate array (FPGA) has been widely used in Internet of Things (IoT) since it can provide flexible and scalable solutions to various IoT requirements. Meanwhile, hardware Trojan (HT), which may lead to undesired chip function or leak sensitive information, has become a great challenge for FPGA security. Therefore, distinguishing the Trojan-infected FPGAs is quite crucial for reinforcing the security of IoT. To achieve this goal, we propose a clock-tree-concerned technique to detect the HTs on FPGA. First, we present an experimental framework which helps us to collect the electromagnetic (EM) radiation emitted by FPGA clock tree. Then, we propose a Trojan identifying approach which extracts the mathematical feature of obtained EM traces, i.e., 2-D principal component analysis (2DPCA) in this paper, and automatically isolates the Trojan-infected FPGAs from the Trojan-free ones by using a BP neural network. Finally, we perform extensive experiments to evaluate the effectiveness of our method. The results reveal that our approach is valid in detecting HTs on FPGA. Specifically, for the trust-hub benchmarks, we can find out the FPGA with always on Trojans (100% detection rate) while identifying the triggered Trojans with high probability (by up to 92%). In addition, we give a thorough discussion on how the experimental setup, such as probe step size, scanning area, and chip ambient temperature, affects the Trojan detection rate.

25 citations

Journal ArticleDOI
TL;DR: In this manuscript, a hardware trojan is created and emulated on a consumer FPGA board, and a state-of-the-art methodology to accurately detect the trojan in both dormant and active states using off- the-shelf hardware is used.
Abstract: As a result of the globalisation of the semiconductor design and fabrication processes, integrated circuits are becoming increasingly vulnerable to malicious attacks. The most concerning threats are hardware trojans. A hardware trojan is a malicious inclusion or alteration to the existing design of an integrated circuit, with the possible effects ranging from leakage of sensitive information to the complete destruction of the integrated circuit itself. While the majority of existing detection schemes focus on test-time, they all require expensive methodologies to detect hardware trojans. Off-the-shelf approaches have often been overlooked due to limited hardware resources and detection accuracy. With the advances in technologies and the democratisation of open-source hardware, however, these tools enable the detection of hardware trojans at reduced costs during or after production. In this manuscript, a hardware trojan is created and emulated on a consumer FPGA board. The experiments to detect the trojan in a dormant and active state are made using off-the-shelf technologies taking advantage of different techniques such as Power Analysis Reports, Side Channel Analysis and Thermal Measurements. Furthermore, multiple attempts to detect the trojan are demonstrated and benchmarked. Our simulations result in a state-of-the-art methodology to accurately detect the trojan in both dormant and active states using off-the-shelf hardware.

25 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023136
2022282
2021111
2020139
2019144
2018168