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Wei-Che Cheng

dblp:162/5732 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0005-2986-5678ORCID · corroborated

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021

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
Memory systems · 100%
Network and information security
1 paper
Hardware security and side channels · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Hardware security and side channels
hardware trojan
0.912025
Hardware Trojan Design With Low Overhead and High Destructiveness for STT-MRAM-Based CIMs · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2025
Memory systems › processing-in-memory
computing-in-memory
0.912025
Hardware Trojan Design With Low Overhead and High Destructiveness for STT-MRAM-Based CIMs · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2025
Memory systems
non-volatile memory
0.912025
Hardware Trojan Design With Low Overhead and High Destructiveness for STT-MRAM-Based CIMs · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2025
Memory systems › non-volatile memory › magnetic random access memory
STT-MRAM
0.912025
Hardware Trojan Design With Low Overhead and High Destructiveness for STT-MRAM-Based CIMs · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2025
YearPublicationVenuePosition
2025 Hardware Trojan Design With Low Overhead and High Destructiveness for STT-MRAM-Based CIMs
abstract
To overcome the von Neumann bottleneck, computing-in-memories (CIMs) have emerged as a design trend. On the other hand, with the globalization of the semiconductor supply chain, hardware Trojans have become a significant security concern. While there have been some studies on hardware Trojan designs for embedded memories in the past, there is no literature addressing hardware Trojan designs for CIMs. In this article, we propose a hardware Trojan design for spin transfer torque magnetoresistive random access memory (STT-MRAM)-based CIMs that can disrupt computing-mode operations. Our trigger circuit can evade detection during post-manufacturing memory testing, and our payload circuit can disrupt over 99% of CIM operations. Experimental results also demonstrate that compared to the original peripheral circuits of STT-MRAM-based CIMs, the area overhead and power overhead (at the TT process corner) caused by our inserted hardware Trojan are only 1.023% and 0.123%, respectively. Therefore, our hardware Trojan can easily hide within the peripheral circuits.
Wei-Che Cheng, Shih-Hsu Huang, Jin-Fu Li 0001
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.1
2015 Application of a two-stage fuzzy neural network to a prostate cancer prognosis system
R. J. Kuo 0001, Man-Hsin Huang, Wei-Che Cheng, Chih-Chieh Lin, Yung-Hung Wu
Artif. Intell. Medicine3