UN-SPLIT: Attacking Split Manufacturing Using Link Prediction in Graph Neural Networks

Lilas Alrahis; Likhitha Mankali; Satwik Patnaik; Abhrajit Sengupta; Johann Knechtel; Ozgur Sinanoglu

doi:10.1007/978-3-031-51583-5_12

UN-SPLIT: Attacking Split Manufacturing Using Link Prediction in Graph Neural Networks

Lilas Alrahis, Likhitha Mankali, Satwik Patnaik, Abhrajit Sengupta, Johann Knechtel, Ozgur Sinanoglu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We explore a new angle for attacking split manufacturing aside from relying only on physical design hints. By learning on the structure, composition, and the front-end-of-line (FEOL) interconnectivity of gates in a given design (or design library/dataset), along with key hints from physical design, we obtain a model that can predict the missing back-end-of-line (BEOL) connections. We formulate this as a link-prediction problem and solve it using a graph neural network (GNN). Furthermore, we utilize post-processing techniques that analyze the GNN predictions and apply common domain knowledge to further enhance the accuracy of our attack methodology.

Original language	English (US)
Title of host publication	Security, Privacy, and Applied Cryptography Engineering - 13th International Conference, SPACE 2023, Proceedings
Editors	Francesco Regazzoni, Bodhisatwa Mazumdar, Sri Parameswaran
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	197-213
Number of pages	17
ISBN (Print)	9783031515828
DOIs	https://doi.org/10.1007/978-3-031-51583-5_12
State	Published - 2024
Event	13th International Conference on Security, Privacy, and Applied Cryptographic Engineering, SPACE 2023 - Roorkee, India Duration: Dec 14 2023 → Dec 17 2023

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14412 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th International Conference on Security, Privacy, and Applied Cryptographic Engineering, SPACE 2023
Country/Territory	India
City	Roorkee
Period	12/14/23 → 12/17/23

Keywords

Graph neural networks
Hardware security
Link prediction
Machine learning
Split manufacturing

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-031-51583-5_12

Cite this

Alrahis, L., Mankali, L., Patnaik, S., Sengupta, A., Knechtel, J., & Sinanoglu, O. (2024). UN-SPLIT: Attacking Split Manufacturing Using Link Prediction in Graph Neural Networks. In F. Regazzoni, B. Mazumdar, & S. Parameswaran (Eds.), Security, Privacy, and Applied Cryptography Engineering - 13th International Conference, SPACE 2023, Proceedings (pp. 197-213). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14412 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-51583-5_12

UN-SPLIT: Attacking Split Manufacturing Using Link Prediction in Graph Neural Networks. / Alrahis, Lilas; Mankali, Likhitha; Patnaik, Satwik et al.
Security, Privacy, and Applied Cryptography Engineering - 13th International Conference, SPACE 2023, Proceedings. ed. / Francesco Regazzoni; Bodhisatwa Mazumdar; Sri Parameswaran. Springer Science and Business Media Deutschland GmbH, 2024. p. 197-213 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14412 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Alrahis, L, Mankali, L, Patnaik, S, Sengupta, A, Knechtel, J & Sinanoglu, O 2024, UN-SPLIT: Attacking Split Manufacturing Using Link Prediction in Graph Neural Networks. in F Regazzoni, B Mazumdar & S Parameswaran (eds), Security, Privacy, and Applied Cryptography Engineering - 13th International Conference, SPACE 2023, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14412 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 197-213, 13th International Conference on Security, Privacy, and Applied Cryptographic Engineering, SPACE 2023, Roorkee, India, 12/14/23. https://doi.org/10.1007/978-3-031-51583-5_12

Alrahis L, Mankali L, Patnaik S, Sengupta A, Knechtel J, Sinanoglu O. UN-SPLIT: Attacking Split Manufacturing Using Link Prediction in Graph Neural Networks. In Regazzoni F, Mazumdar B, Parameswaran S, editors, Security, Privacy, and Applied Cryptography Engineering - 13th International Conference, SPACE 2023, Proceedings. Springer Science and Business Media Deutschland GmbH. 2024. p. 197-213. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-51583-5_12

Alrahis, Lilas ; Mankali, Likhitha ; Patnaik, Satwik et al. / UN-SPLIT : Attacking Split Manufacturing Using Link Prediction in Graph Neural Networks. Security, Privacy, and Applied Cryptography Engineering - 13th International Conference, SPACE 2023, Proceedings. editor / Francesco Regazzoni ; Bodhisatwa Mazumdar ; Sri Parameswaran. Springer Science and Business Media Deutschland GmbH, 2024. pp. 197-213 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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UN-SPLIT: Attacking Split Manufacturing Using Link Prediction in Graph Neural Networks

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