A Pragmatic Methodology for Blind Hardware Trojan Insertion in Finalized Layouts

Author:

Hepp Alexander1,Perez Tiago2,Pagliarini Samuel2,Sigl Georg3

Affiliation:

1. Technical University of Munich, Munich, Germany

2. Tallinn University of Technology, Tallinn, Estonia

3. Technical University of Munich, Munich, Germany and Fraunhofer AISEC, Munich, Germany

Funder

European Union's Horizon 2020 research and innovation programme

European Social Fund

Publisher

ACM

Reference43 articles.

1. A case study in hardware Trojan design and implementation

2. Hardware Trojan Horses in Cryptographic IP Cores

3. Jonathan Cruz Pravin Gaikwad Abhishek Nair Prabuddha Chakraborty and Swarup Bhunia. 2022. Automatic Hardware Trojan Insertion using Machine Learning. (2022). https://arxiv.org/abs/2204.08580 arXiv: 2204.08580. Jonathan Cruz Pravin Gaikwad Abhishek Nair Prabuddha Chakraborty and Swarup Bhunia. 2022. Automatic Hardware Trojan Insertion using Machine Learning. (2022). https://arxiv.org/abs/2204.08580 arXiv: 2204.08580.

4. An automated configurable Trojan insertion framework for dynamic trust benchmarks

5. PyEDA: Data Structures and Algorithms for Electronic Design Automation

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