Lilas Alrahis

694 total citations
32 papers, 408 citations indexed

About

Lilas Alrahis is a scholar working on Hardware and Architecture, Electrical and Electronic Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Lilas Alrahis has authored 32 papers receiving a total of 408 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Hardware and Architecture, 25 papers in Electrical and Electronic Engineering and 13 papers in Cellular and Molecular Neuroscience. Recurrent topics in Lilas Alrahis's work include Physical Unclonable Functions (PUFs) and Hardware Security (24 papers), Integrated Circuits and Semiconductor Failure Analysis (16 papers) and Neuroscience and Neural Engineering (13 papers). Lilas Alrahis is often cited by papers focused on Physical Unclonable Functions (PUFs) and Hardware Security (24 papers), Integrated Circuits and Semiconductor Failure Analysis (16 papers) and Neuroscience and Neural Engineering (13 papers). Lilas Alrahis collaborates with scholars based in United States, United Arab Emirates and Germany. Lilas Alrahis's co-authors include Ozgur Sinanoglu, Satwik Patnaik, Muhammad Shafique, Johann Knechtel, Hani Saleh, Mahmoud Al‐Qutayri, Baker Mohammad, Muhammad Yasin, Muhammad Abdullah Hanif and Abhrajit Sengupta and has published in prestigious journals such as IEEE Access, IEEE Transactions on Computers and IEEE Transactions on Information Forensics and Security.

In The Last Decade

Lilas Alrahis

28 papers receiving 405 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lilas Alrahis United States 12 317 291 134 107 45 32 408
Bicky Shakya United States 9 426 1.3× 354 1.2× 116 0.9× 155 1.4× 67 1.5× 18 484
Samuel Pagliarini Estonia 11 259 0.8× 306 1.1× 156 1.2× 51 0.5× 21 0.5× 58 459
Farhad Merchant Germany 10 188 0.6× 180 0.6× 82 0.6× 58 0.5× 38 0.8× 48 314
Georg T. Becker Germany 11 351 1.1× 282 1.0× 123 0.9× 135 1.3× 72 1.6× 19 407
Phuong Ha Nguyen India 9 477 1.5× 408 1.4× 102 0.8× 202 1.9× 55 1.2× 23 526
Yang Xie United States 9 408 1.3× 385 1.3× 158 1.2× 158 1.5× 49 1.1× 17 478
Yijun Cui China 13 376 1.2× 341 1.2× 49 0.4× 142 1.3× 46 1.0× 53 419
Amin Rezaei United States 15 327 1.0× 290 1.0× 136 1.0× 95 0.9× 57 1.3× 42 452
Jiaji He China 11 315 1.0× 239 0.8× 154 1.1× 100 0.9× 66 1.5× 50 408
Yangdi Lyu United States 13 265 0.8× 204 0.7× 139 1.0× 78 0.7× 65 1.4× 19 382

Countries citing papers authored by Lilas Alrahis

Since Specialization
Citations

This map shows the geographic impact of Lilas Alrahis's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lilas Alrahis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lilas Alrahis more than expected).

Fields of papers citing papers by Lilas Alrahis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lilas Alrahis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lilas Alrahis. The network helps show where Lilas Alrahis may publish in the future.

Co-authorship network of co-authors of Lilas Alrahis

This figure shows the co-authorship network connecting the top 25 collaborators of Lilas Alrahis. A scholar is included among the top collaborators of Lilas Alrahis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lilas Alrahis. Lilas Alrahis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Alrahis, Lilas, et al.. (2025). OptiLock: Automated Optimization of Learning-Resilient Logic Locking. IEEE Access. 13. 166649–166669.
2.
Alrahis, Lilas, et al.. (2024). LLMs and the Future of Chip Design: Unveiling Security Risks and Building Trust. 385–390. 10 indexed citations
3.
Paim, Guilherme, Lilas Alrahis, Paulo Flores, et al.. (2024). On the Efficacy and Vulnerabilities of Logic Locking in Tree-Based Machine Learning. IEEE Transactions on Circuits and Systems I Regular Papers. 72(1). 180–191.
4.
Alrahis, Lilas, et al.. (2024). Always be Pre-Training: Representation Learning for Network Intrusion Detection with GNNs. arXiv (Cornell University). 1–8. 6 indexed citations
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7.
Santen, Victor M. van, et al.. (2024). Graph Attention Networks to Identify the Impact of Transistor Degradation on Circuit Reliability. IEEE Transactions on Circuits and Systems I Regular Papers. 71(7). 3269–3281. 1 indexed citations
8.
Alrahis, Lilas, Jonas Krautter, Dennis R. E. Gnad, et al.. (2024). MaliGNNoma: GNN-Based Malicious Circuit Classifier for Secure Cloud FPGAs. 383–393. 3 indexed citations
9.
Alrahis, Lilas, et al.. (2023). FPGA-Patch: Mitigating Remote Side-Channel Attacks on FPGAs using Dynamic Patch Generation. 1–6. 4 indexed citations
10.
Alrahis, Lilas, Satwik Patnaik, Muhammad Abdullah Hanif, Muhammad Shafique, & Ozgur Sinanoglu. (2023). $\tt{PoisonedGNN}$: Backdoor Attack on Graph Neural Networks-Based Hardware Security Systems. IEEE Transactions on Computers. 72(10). 2822–2834. 10 indexed citations
11.
12.
Alrahis, Lilas, et al.. (2023). Security Closure of IC Layouts Against Hardware Trojans. 229–237. 8 indexed citations
13.
Alrahis, Lilas, et al.. (2022). NeuroUnlock: Unlocking the Architecture of Obfuscated Deep Neural Networks. 2022 International Joint Conference on Neural Networks (IJCNN). 1–10. 3 indexed citations
14.
Alrahis, Lilas, et al.. (2022). AppGNN. 1–9. 9 indexed citations
15.
Alrahis, Lilas, Abhrajit Sengupta, Johann Knechtel, et al.. (2021). GNN-RE: Graph Neural Networks for Reverse Engineering of Gate-Level Netlists. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41(8). 2435–2448. 56 indexed citations
16.
Alrahis, Lilas, Satwik Patnaik, Johann Knechtel, et al.. (2021). UNSAIL: Thwarting Oracle-Less Machine Learning Attacks on Logic Locking. IEEE Transactions on Information Forensics and Security. 16. 2508–2523. 27 indexed citations
17.
Alrahis, Lilas, Satwik Patnaik, Muhammad Abdullah Hanif, Muhammad Shafique, & Ozgur Sinanoglu. (2021). UNTANGLE: Unlocking Routing and Logic Obfuscation Using Graph Neural Networks-based Link Prediction. 1–9. 22 indexed citations
18.
Alrahis, Lilas, Satwik Patnaik, Muhammad Abdullah Hanif, et al.. (2021). GNNUnlock+: A Systematic Methodology for Designing Graph Neural Networks-Based Oracle-Less Unlocking Schemes for Provably Secure Logic Locking. IEEE Transactions on Emerging Topics in Computing. 10(3). 1575–1592. 18 indexed citations
19.
Alrahis, Lilas, Muhammad Yasin, Nimisha Limaye, et al.. (2019). ScanSAT: Unlocking Static and Dynamic Scan Obfuscation. IEEE Transactions on Emerging Topics in Computing. 9(4). 1867–1882. 35 indexed citations
20.
Alrahis, Lilas, Muhammad Yasin, Hani Saleh, Baker Mohammad, & Mahmoud Al‐Qutayri. (2019). Functional Reverse Engineering on SAT-Attack Resilient Logic Locking. 1–5. 14 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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