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Jason Teo Kian Jin

dblp:179/0858 · also J. K. J. Teo · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Electronic design automation · 100%
Network and information security
1 paper
Hardware security and side channels · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Hardware security and side channels › hardware trojan
hardware trojan detection
0.212016
Cost-efficient Acceleration of Hardware Trojan Detection Through Fan-Out Cone Analysis and Weighted Random Pattern Technique · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2016
Electronic design automation › hardware verification and test › hardware verification
hardware trojan detection
0.212016
Cost-efficient Acceleration of Hardware Trojan Detection Through Fan-Out Cone Analysis and Weighted Random Pattern Technique · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2016
Electronic design automation
hardware verification and test
0.212016
Cost-efficient Acceleration of Hardware Trojan Detection Through Fan-Out Cone Analysis and Weighted Random Pattern Technique · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2016

Methods — techniques the papers use, named apart from their topics

weighted random pattern · 0.5fan-out cone analysis · 0.5MUX-based test points · 0.5
YearPublicationVenuePosition
2016 Cost-efficient Acceleration of Hardware Trojan Detection Through Fan-Out Cone Analysis and Weighted Random Pattern Technique
abstract
Fabless semiconductor industry and government agencies have raised serious concerns about tampering with inserting hardware Trojans (HTs) in an integrated circuit supply chain in recent years. In this paper, a low hardware overhead acceleration method of the detection of HTs based on the insertion of 2-to-1 MUXs as test points is proposed. In the proposed method, the fact that one logical gate has a significant impact on the transition probability of the logical gates in its logical fan-out cone is utilized to optimize the number of the inserted MUXs. The nets which have smaller transition probability than the user-specified threshold and minimal logical depth from the primary inputs are selected as the candidate nets. As for each candidate net, only its input net with smallest signal probability is required to be inserted the MUXs-based test points. The procedure repeats until the minimal transition probability of the entire circuit is not smaller than the threshold value. In order to further optimize the number of required insertions and reduce the overhead, the weighted random pattern technique is also applied. Experiment results on ISCAS'89 benchmark circuits show that our proposed method can achieve remarkable improvement of transition probability with on average 9.50% power, 2.37% delay, and 10.26% area penalty.
Wei Zhang 0012, Thambipillai Srikanthan, Jason Teo Kian Jin, Vivek Chaturvedi, Tao Luo 0014
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.4