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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2605.09124 |
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| _version_ | 1866916019889504256 |
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| author | Abdelaziz, Tamer |
| author_facet | Abdelaziz, Tamer |
| contents | Smart contract security has progressed from vulnerability detection toward a broader research agenda that includes semantic reasoning, automated repair, adversarial robustness, and real-time exploit detection. This paper develops a capstone-oriented research narrative around four directions: foundation-model-based smart contract semantics and vulnerability reasoning [1], automated smart contract repair with formal guarantees [2], adversarial learning for robust malicious contract and transaction detection [3], and real-time transaction-level exploit detection at blockchain scale [4]. We connect these directions to two recent studies that characterize the current frontier: a diagnostic analysis of where smart contract security analyzers fall short [5] and a scalable real-time system for malicious Ethereum transaction detection [6]. The resulting framework is intended to help students formulate capstone projects that are technically grounded, empirically measurable, and aligned with contemporary smart contract security research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_09124 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Smart Contract Security Beyond Detection Abdelaziz, Tamer Cryptography and Security Smart contract security has progressed from vulnerability detection toward a broader research agenda that includes semantic reasoning, automated repair, adversarial robustness, and real-time exploit detection. This paper develops a capstone-oriented research narrative around four directions: foundation-model-based smart contract semantics and vulnerability reasoning [1], automated smart contract repair with formal guarantees [2], adversarial learning for robust malicious contract and transaction detection [3], and real-time transaction-level exploit detection at blockchain scale [4]. We connect these directions to two recent studies that characterize the current frontier: a diagnostic analysis of where smart contract security analyzers fall short [5] and a scalable real-time system for malicious Ethereum transaction detection [6]. The resulting framework is intended to help students formulate capstone projects that are technically grounded, empirically measurable, and aligned with contemporary smart contract security research. |
| title | Smart Contract Security Beyond Detection |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2605.09124 |