Chatgpt for cybersecurity: practical applications, challenges, and future directions

被引:33
作者
Al-Hawawreh, Muna [1 ]
Aljuhani, Ahamed [2 ]
Jararweh, Yaser [3 ]
机构
[1] Deakin Univ, 75 Pigdons Rd, Geelong, Vic 3216, Australia
[2] Tabuk Univ, Tabuk 47512, Saudi Arabia
[3] Jordan Univ Sci & Technol, Irbid, Jordan
来源
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2023年 / 26卷 / 06期
关键词
Transformer; Cybersecurity; False data injection; Control system; Anomaly detection;
D O I
10.1007/s10586-023-04124-5
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Artificial intelligence (AI) advancements have revolutionized many critical domains by providing cost-effective, automated, and intelligent solutions. Recently, ChatGPT has achieved a momentous change and made substantial progress in natural language processing. As such, a chatbot-driven AI technology has the capabilities to interact and communicate with users and generate human-like responses. ChatGPT, on the other hand, has the potential to influence changes in the cybersecurity domain. ChatGPT can be utilized as a chatbot-driven security assistant for penetration testing to analyze, investigate, and develop security solutions. However, ChatGPT raises concerns about how the tool can be used for cybercrime and malicious activities. Attackers can use such a tool to cause substantial harm by exploiting vulnerabilities, writing malicious code, and circumventing security measures on a targeted system. This article investigates the implications of the ChatGPT model in the domain of cybersecurity. We present the state-of-the-art practical applications of ChatGPT in cybersecurity. In addition, we demonstrate in a case study how a ChatGPT can be used to design and develop False data injection attacks against critical infrastructure such as industrial control systems. Conversely, we show how such a tool can be used to help security analysts to analyze, design, and develop security solutions against cyberattacks. Finally, this article discusses the open challenges and future directions of ChatGPT in cybersecurity.
引用
收藏
页码:3421 / 3436
页数:16
相关论文
共 41 条
  • [1] Abdullah Malak, 2022, 2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS), P1, DOI 10.1109/SNAMS58071.2022.10062688
  • [2] A threat intelligence framework for protecting smart satellite-based healthcare networks
    Al-Hawawreh, Muna
    Moustafa, Nour
    Slay, Jill
    [J]. NEURAL COMPUTING & APPLICATIONS, 2024, 36 (01) : 15 - 35
  • [3] An Efficient Intrusion Detection Model for Edge System in Brownfield Industrial Internet of Things
    AL-Hawawreh, Muna
    Sitnikova, Elena
    den Hartog, Frank
    [J]. 3RD INTERNATIONAL CONFERENCE ON BIG DATA AND INTERNET OF THINGS (BDIOT 2019), 2018, : 83 - 87
  • [4] Scaling and Effectiveness of Email Masquerade Attacks: Exploiting Natural Language Generation
    Baki, Shahryar
    Verma, Rakesh
    Mukherjee, Arjun
    Gnawali, Omprakash
    [J]. PROCEEDINGS OF THE 2017 ACM ASIA CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (ASIA CCS'17), 2017, : 469 - 482
  • [5] Balash DG, 2022, PROCEEDINGS OF THE 31ST USENIX SECURITY SYMPOSIUM, P3397
  • [6] Ben-Moshe S., OPWNAI AI CAN SAVE D
  • [7] Brown TB., 2020, ADV NEURAL INFORM PR, DOI DOI 10.48550/ARXIV.2005.14165
  • [8] checkpoint, CHECKP CYB BYP CHATG
  • [9] Clark Elizabeth, 2021, ARXIV
  • [10] GPT-3: What's it good for?
    Dale, Robert
    [J]. NATURAL LANGUAGE ENGINEERING, 2021, 27 (01) : 113 - 118