A Survey on Offensive AI Within Cybersecurity
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866913532082126848 |
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| author | Girhepuje, Sahil Verma, Aviral Raina, Gaurav |
| author_facet | Girhepuje, Sahil Verma, Aviral Raina, Gaurav |
| contents | Artificial Intelligence (AI) has witnessed major growth and integration across various domains. As AI systems become increasingly prevalent, they also become targets for threat actors to manipulate their functionality for malicious purposes. This survey paper on offensive AI will comprehensively cover various aspects related to attacks against and using AI systems. It will delve into the impact of offensive AI practices on different domains, including consumer, enterprise, and public digital infrastructure. The paper will explore adversarial machine learning, attacks against AI models, infrastructure, and interfaces, along with offensive techniques like information gathering, social engineering, and weaponized AI. Additionally, it will discuss the consequences and implications of offensive AI, presenting case studies, insights, and avenues for further research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_03566 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Survey on Offensive AI Within Cybersecurity Girhepuje, Sahil Verma, Aviral Raina, Gaurav Cryptography and Security Artificial Intelligence Artificial Intelligence (AI) has witnessed major growth and integration across various domains. As AI systems become increasingly prevalent, they also become targets for threat actors to manipulate their functionality for malicious purposes. This survey paper on offensive AI will comprehensively cover various aspects related to attacks against and using AI systems. It will delve into the impact of offensive AI practices on different domains, including consumer, enterprise, and public digital infrastructure. The paper will explore adversarial machine learning, attacks against AI models, infrastructure, and interfaces, along with offensive techniques like information gathering, social engineering, and weaponized AI. Additionally, it will discuss the consequences and implications of offensive AI, presenting case studies, insights, and avenues for further research. |
| title | A Survey on Offensive AI Within Cybersecurity |
| topic | Cryptography and Security Artificial Intelligence |
| url | https://arxiv.org/abs/2410.03566 |