From Vulnerability to Defense: The Role of Large Language Models in Enhancing Cybersecurity.
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| Title: | From Vulnerability to Defense: The Role of Large Language Models in Enhancing Cybersecurity. |
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| Authors: | Kasri, Wafaa, Himeur, Yassine, Alkhazaleh, Hamzah Ali, Tarapiah, Saed, Atalla, Shadi, Mansoor, Wathiq, Al-Ahmad, Hussain |
| Source: | Computation; Feb2025, Vol. 13 Issue 2, p30, 59p |
| Subject Terms: | LANGUAGE models, NATURAL language processing, DIGITAL technology, CYBERTERRORISM, ORGANIZATIONAL resilience |
| Abstract: | The escalating complexity of cyber threats, coupled with the rapid evolution of digital landscapes, poses significant challenges to traditional cybersecurity mechanisms. This review explores the transformative role of LLMs in addressing critical challenges in cybersecurity. With the rapid evolution of digital landscapes and the increasing sophistication of cyber threats, traditional security mechanisms often fall short in detecting, mitigating, and responding to complex risks. LLMs, such as GPT, BERT, and PaLM, demonstrate unparalleled capabilities in natural language processing, enabling them to parse vast datasets, identify vulnerabilities, and automate threat detection. Their applications extend to phishing detection, malware analysis, drafting security policies, and even incident response. By leveraging advanced features like context awareness and real-time adaptability, LLMs enhance organizational resilience against cyberattacks while also facilitating more informed decision-making. However, deploying LLMs in cybersecurity is not without challenges, including issues of interpretability, scalability, ethical concerns, and susceptibility to adversarial attacks. This review critically examines the foundational elements, real-world applications, and limitations of LLMs in cybersecurity while also highlighting key advancements in their integration into security frameworks. Through detailed analysis and case studies, this paper identifies emerging trends and proposes future research directions, such as improving robustness, addressing privacy concerns, and automating incident management. The study concludes by emphasizing the potential of LLMs to redefine cybersecurity, driving innovation and enhancing digital security ecosystems. [ABSTRACT FROM AUTHOR] |
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| Database: | Biomedical Index |
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