Trojan Detection using IC Fingerprinting

By Dakshi Agrawal, S. Baktir, Deniz Karakoyunlu, Pankaj Rohatgi, Berk Sunar. IEEE Symposium on Security and Privacy, 2007

813 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/0402e10c33b53a91b4ea55db4e6307ab0bd09130

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Citations in the corpus

Detecting malicious inclusions in secure hardware: Challenges and solutions (2008, background): “A third approach that can potentially solve these problems involves the measurement and analysis of the chip’s side-channel signals [4][5][6].”
Hardware Trojan detection using path delay fingerprint (2008, methodology): “[1] is a significant milestone in the Trojan detection field.”
FANCI: identification of stealthy malicious logic using boolean functional analysis (2013, background): “There has also been prior work in related areas of hardware supply-chain security, including the detection of physical backdoors added during fabrication [13, 14, 15, 16] and detecting actively running backdoors [17, 18].”
Hardware Trojan Attacks: Threat Analysis and Countermeasures (2014, methodology): “The IC fingerprinting technique [4] uses signal processing techniques such as the Karhunen–Loeve”
MERO: A Statistical Approach for Hardware Trojan Detection (2009, methodology): “A minimal set of patterns that is highly likely to cause activity in a Trojan is attractive in power or current signature based side-channel approach to detect hardware Trojan [1, 9, 11].”
A Survey of Hardware Trojan Taxonomy and Detection (2010, background): “Agrawal et al.(13) Transient power Counter: 16-bit”
On design vulnerability analysis and trust benchmarks development (2013, positive): “Using these methodologies, we have developed a large number of trust benchmarks that are available for use by the public, as well as researchers and practitioners in the field.”
A Primer on Hardware Security: Models, Methods, and Metrics (2014, methodology): “This work was supported in part by the U.S. Office of Naval Research (ONR) under Grant R17460 and the National Science Foundation (NSF) under Grants to Rice University (CNS-1059416) and NYU (CNS-1059328 and CCF-1319841), NYU/NYU-AD Center for Research in Information Security Studies and Privacy…”
Hardware Trojan: Threats and emerging solutions (2009, background): “6(b)) in the design to capture and compare with the data latched by registers in the original circuit paths.”
Overcoming an Untrusted Computing Base: Detecting and Removing Malicious Hardware Automatically (2010, methodology): “[3] propose signal processing techniques to detect additional circuits through power side-channel power analysis.”
At-speed delay characterization for IC authentication and Trojan Horse detection (2008, background): “For example, Agrawal et al. proposed a side-channel-based approach that extracts non-functional circuit information, including path delays, power consumption, and electromagnetic emanation profiles, that constitutes a “fingerprint” for every individual IC [1].”
Counterfeit Integrated Circuits: A Rising Threat in the Global Semiconductor Supply Chain (2014, methodology): “In [57], advanced signal processing techniques based on Karhunen–Loève expansion are used to find a signal subspace from which the process noise is absent in order to identify Trojans that are well hidden within the variations of the signals generated by the process noise.”
Designing and Implementing Malicious Hardware (2008, background): “IBM developed a “trojan circuit” to steal encryption keys [3].”