Chatbots to ChatGPT in a Cybersecurity Space: Evolution, Vulnerabilities, Attacks, Challenges, and Future Recommendations

• URL: http://arxiv.org/abs/2306.09255v1
• Date: Mon, 29 May 2023 12:26:44 GMT
• Title: Chatbots to ChatGPT in a Cybersecurity Space: Evolution, Vulnerabilities, Attacks, Challenges, and Future Recommendations
• Authors: Attia Qammar, Hongmei Wang, Jianguo Ding, Abdenacer Naouri, Mahmoud Daneshmand, Huansheng Ning
• Abstract summary: OpenAI developed ChatGPT blizzard on the Internet as it crossed one million users within five days of its launch. With the enhanced popularity, ChatGPT experienced cybersecurity threats and vulnerabilities.
• Score: 6.1194122931444035
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Chatbots shifted from rule-based to artificial intelligence techniques and gained traction in medicine, shopping, customer services, food delivery, education, and research. OpenAI developed ChatGPT blizzard on the Internet as it crossed one million users within five days of its launch. However, with the enhanced popularity, chatbots experienced cybersecurity threats and vulnerabilities. This paper discussed the relevant literature, reports, and explanatory incident attacks generated against chatbots. Our initial point is to explore the timeline of chatbots from ELIZA (an early natural language processing computer program) to GPT-4 and provide the working mechanism of ChatGPT. Subsequently, we explored the cybersecurity attacks and vulnerabilities in chatbots. Besides, we investigated the ChatGPT, specifically in the context of creating the malware code, phishing emails, undetectable zero-day attacks, and generation of macros and LOLBINs. Furthermore, the history of cyberattacks and vulnerabilities exploited by cybercriminals are discussed, particularly considering the risk and vulnerabilities in ChatGPT. Addressing these threats and vulnerabilities requires specific strategies and measures to reduce the harmful consequences. Therefore, the future directions to address the challenges were presented.

Related papers

• IntellBot: Retrieval Augmented LLM Chatbot for Cyber Threat Knowledge Delivery [10.937956959186472]
  IntellBot is an advanced cyber security built on top of cutting-edge technologies like Large Language Models and Langchain. It gathers information from diverse data sources to create a comprehensive knowledge base covering known vulnerabilities, recent cyber attacks, and emerging threats. It delivers tailored responses, serving as a primary hub for cyber security insights.
  arXiv  Detail & Related papers  (2024-11-08T09:40:53Z)
• AbuseGPT: Abuse of Generative AI ChatBots to Create Smishing Campaigns [0.0]
  We propose AbuseGPT method to show how the existing generative AI-based chatbots can be exploited by attackers in real world to create smishing texts. We have found strong empirical evidences to show that attackers can exploit ethical standards in the existing generative AI-based chatbots services. We also discuss some future research directions and guidelines to protect the abuse of generative AI-based services.
  arXiv  Detail & Related papers  (2024-02-15T05:49:22Z)
• Exploring ChatGPT's Capabilities on Vulnerability Management [56.4403395100589]
  We explore ChatGPT's capabilities on 6 tasks involving the complete vulnerability management process with a large-scale dataset containing 70,346 samples. One notable example is ChatGPT's proficiency in tasks like generating titles for software bug reports. Our findings reveal the difficulties encountered by ChatGPT and shed light on promising future directions.
  arXiv  Detail & Related papers  (2023-11-11T11:01:13Z)
• From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy [0.0]
  This research paper highlights the limitations, challenges, potential risks, and opportunities of GenAI in the domain of cybersecurity and privacy. The paper investigates how cyber offenders can use the GenAI tools in developing cyber attacks. We will also discuss the social, legal, and ethical implications of ChatGPT.
  arXiv  Detail & Related papers  (2023-07-03T00:36:57Z)
• Deceptive AI Ecosystems: The Case of ChatGPT [8.128368463580715]
  ChatGPT has gained popularity for its capability in generating human-like responses. This paper investigates how ChatGPT operates in the real world where societal pressures influence its development and deployment. We examine the ethical challenges stemming from ChatGPT's deceptive human-like interactions.
  arXiv  Detail & Related papers  (2023-06-18T10:36:19Z)
• Generating Phishing Attacks using ChatGPT [1.392250707100996]
  We identify several malicious prompts that can be provided to ChatGPT to generate functional phishing websites. These attacks can be generated using vanilla ChatGPT without the need of any prior adversarial exploits.
  arXiv  Detail & Related papers  (2023-05-09T02:38:05Z)
• A Categorical Archive of ChatGPT Failures [47.64219291655723]
  ChatGPT, developed by OpenAI, has been trained using massive amounts of data and simulates human conversation. It has garnered significant attention due to its ability to effectively answer a broad range of human inquiries. However, a comprehensive analysis of ChatGPT's failures is lacking, which is the focus of this study.
  arXiv  Detail & Related papers  (2023-02-06T04:21:59Z)
• A System for Efficiently Hunting for Cyber Threats in Computer Systems Using Threat Intelligence [78.23170229258162]
  We build ThreatRaptor, a system that facilitates cyber threat hunting in computer systems using OSCTI. ThreatRaptor provides (1) an unsupervised, light-weight, and accurate NLP pipeline that extracts structured threat behaviors from unstructured OSCTI text, (2) a concise and expressive domain-specific query language, TBQL, to hunt for malicious system activities, and (3) a query synthesis mechanism that automatically synthesizes a TBQL query from the extracted threat behaviors.
  arXiv  Detail & Related papers  (2021-01-17T19:44:09Z)
• Robust Text CAPTCHAs Using Adversarial Examples [129.29523847765952]
  We propose a user-friendly text-based CAPTCHA generation method named Robust Text CAPTCHA (RTC) At the first stage, the foregrounds and backgrounds are constructed with randomly sampled font and background images. At the second stage, we apply a highly transferable adversarial attack for text CAPTCHAs to better obstruct CAPTCHA solvers.
  arXiv  Detail & Related papers  (2021-01-07T11:03:07Z)
• Enabling Efficient Cyber Threat Hunting With Cyber Threat Intelligence [94.94833077653998]
  ThreatRaptor is a system that facilitates threat hunting in computer systems using open-source Cyber Threat Intelligence (OSCTI) It extracts structured threat behaviors from unstructured OSCTI text and uses a concise and expressive domain-specific query language, TBQL, to hunt for malicious system activities. Evaluations on a broad set of attack cases demonstrate the accuracy and efficiency of ThreatRaptor in practical threat hunting.
  arXiv  Detail & Related papers  (2020-10-26T14:54:01Z)
• Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain [58.30296637276011]
  This paper summarizes the latest research on adversarial attacks against security solutions based on machine learning techniques. It is the first to discuss the unique challenges of implementing end-to-end adversarial attacks in the cyber security domain.
  arXiv  Detail & Related papers  (2020-07-05T18:22:40Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.