AI Code Generators for Security: Friend or Foe?
Fuente:
arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866929231638822912 |
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| author | Natella, Roberto Liguori, Pietro Improta, Cristina Cukic, Bojan Cotroneo, Domenico |
| author_facet | Natella, Roberto Liguori, Pietro Improta, Cristina Cukic, Bojan Cotroneo, Domenico |
| contents | Recent advances of artificial intelligence (AI) code generators are opening new opportunities in software security research, including misuse by malicious actors. We review use cases for AI code generators for security and introduce an evaluation benchmark. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_01219 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | AI Code Generators for Security: Friend or Foe? Natella, Roberto Liguori, Pietro Improta, Cristina Cukic, Bojan Cotroneo, Domenico Cryptography and Security Artificial Intelligence Software Engineering Recent advances of artificial intelligence (AI) code generators are opening new opportunities in software security research, including misuse by malicious actors. We review use cases for AI code generators for security and introduce an evaluation benchmark. |
| title | AI Code Generators for Security: Friend or Foe? |
| topic | Cryptography and Security Artificial Intelligence Software Engineering |
| url | https://arxiv.org/abs/2402.01219 |