{"title":"释放攻击性人工智能:自动生成攻击技术代码","authors":"Eider Iturbe , Oscar Llorente-Vazquez , Angel Rego , Erkuden Rios , Nerea Toledo","doi":"10.1016/j.cose.2024.104077","DOIUrl":null,"url":null,"abstract":"<div><p>Artificial Intelligence (AI) technology is revolutionizing the digital world and becoming the cornerstone of the modern digital systems. The capabilities of cybercriminals are expanding as they adopt new technologies like zero-day exploits or new business models such as hacker-as-a-service. While AI capabilities can improve cybersecurity measures, this same technology can also be utilized as an offensive cyber weapon to create sophisticated and intricate cyber-attacks. This paper describes an AI-powered mechanism for the automatic generation of attack techniques, ranging from initial attack vectors to impact-related actions. It presents a comprehensive analysis of simulated attacks by highlighting the attack tactics and techniques that are more likely to be generated using AI technology, specifically Large Language Model (LLM) technology. The work empirically demonstrates that LLM technology can be easily used by cybercriminals for attack execution. Moreover, the solution can complement Breach and Attack Simulation (BAS) platforms and frameworks that automate the security assessment in a controlled manner. BAS could be enhanced with AI-powered attack simulation by bringing forth new ways to automatically program multiple attack techniques, even multiple versions of the same attack technique. Therefore, AI-enhanced attack simulation can assist in ensuring digital systems are bulletproof and protected against a great variety of attack vectors and actions.</p></div>","PeriodicalId":51004,"journal":{"name":"Computers & Security","volume":"147 ","pages":"Article 104077"},"PeriodicalIF":4.8000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167404824003821/pdfft?md5=50584419d0d6a55d9170eea75a91154b&pid=1-s2.0-S0167404824003821-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Unleashing offensive artificial intelligence: Automated attack technique code generation\",\"authors\":\"Eider Iturbe , Oscar Llorente-Vazquez , Angel Rego , Erkuden Rios , Nerea Toledo\",\"doi\":\"10.1016/j.cose.2024.104077\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Artificial Intelligence (AI) technology is revolutionizing the digital world and becoming the cornerstone of the modern digital systems. The capabilities of cybercriminals are expanding as they adopt new technologies like zero-day exploits or new business models such as hacker-as-a-service. While AI capabilities can improve cybersecurity measures, this same technology can also be utilized as an offensive cyber weapon to create sophisticated and intricate cyber-attacks. This paper describes an AI-powered mechanism for the automatic generation of attack techniques, ranging from initial attack vectors to impact-related actions. It presents a comprehensive analysis of simulated attacks by highlighting the attack tactics and techniques that are more likely to be generated using AI technology, specifically Large Language Model (LLM) technology. The work empirically demonstrates that LLM technology can be easily used by cybercriminals for attack execution. Moreover, the solution can complement Breach and Attack Simulation (BAS) platforms and frameworks that automate the security assessment in a controlled manner. BAS could be enhanced with AI-powered attack simulation by bringing forth new ways to automatically program multiple attack techniques, even multiple versions of the same attack technique. Therefore, AI-enhanced attack simulation can assist in ensuring digital systems are bulletproof and protected against a great variety of attack vectors and actions.</p></div>\",\"PeriodicalId\":51004,\"journal\":{\"name\":\"Computers & Security\",\"volume\":\"147 \",\"pages\":\"Article 104077\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0167404824003821/pdfft?md5=50584419d0d6a55d9170eea75a91154b&pid=1-s2.0-S0167404824003821-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Security\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167404824003821\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Security","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167404824003821","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Artificial Intelligence (AI) technology is revolutionizing the digital world and becoming the cornerstone of the modern digital systems. The capabilities of cybercriminals are expanding as they adopt new technologies like zero-day exploits or new business models such as hacker-as-a-service. While AI capabilities can improve cybersecurity measures, this same technology can also be utilized as an offensive cyber weapon to create sophisticated and intricate cyber-attacks. This paper describes an AI-powered mechanism for the automatic generation of attack techniques, ranging from initial attack vectors to impact-related actions. It presents a comprehensive analysis of simulated attacks by highlighting the attack tactics and techniques that are more likely to be generated using AI technology, specifically Large Language Model (LLM) technology. The work empirically demonstrates that LLM technology can be easily used by cybercriminals for attack execution. Moreover, the solution can complement Breach and Attack Simulation (BAS) platforms and frameworks that automate the security assessment in a controlled manner. BAS could be enhanced with AI-powered attack simulation by bringing forth new ways to automatically program multiple attack techniques, even multiple versions of the same attack technique. Therefore, AI-enhanced attack simulation can assist in ensuring digital systems are bulletproof and protected against a great variety of attack vectors and actions.
期刊介绍:
Computers & Security is the most respected technical journal in the IT security field. With its high-profile editorial board and informative regular features and columns, the journal is essential reading for IT security professionals around the world.
Computers & Security provides you with a unique blend of leading edge research and sound practical management advice. It is aimed at the professional involved with computer security, audit, control and data integrity in all sectors - industry, commerce and academia. Recognized worldwide as THE primary source of reference for applied research and technical expertise it is your first step to fully secure systems.