A systematic literature review of information security in chatbots
Document Type
Article
Publication Date
5-1-2023
Abstract
Chatbots have become increasingly popular in recent years, but they also present security risks and vulnerabilities that need to be addressed. This systematic literature review examines the existing research relating to information security in chatbots, identifying the potential threats, proposed solutions, and future directions for research. The review finds that chatbots face various security threats, including malicious input, user profiling, contextual attacks, and data breaches, and that solutions such as blockchain technology, end-to-end encryption, and organizational controls can be used to mitigate these concerns. The review also highlights the importance of maintaining user trust and addressing privacy concerns for the successful adoption and continued use of chatbots. A taxonomy developed in this review provides a useful framework for categorizing the articles and their findings. The review concludes by identifying future research directions that include developing more sophisticated authentication and authorization mechanisms, exploring the use of privacy-enhancing technologies, and improving the detection and prevention of security threats, among others. This review contributes to the growing body of literature on information security in chatbots and can guide future research and practice in this field.
Keywords
Chatbot, Information security, Systematic literature review (SLR), ChatGPT, Security
Divisions
fsktm
Funders
National Science and Technology Council in Taiwan [Grant No: NSTC-109-2628-E-027-004MY3; NSTC-111-2218-E-027-003; NSTC-111-2622-8-027-009]
Publication Title
Applied Sciences-Basel
Volume
13
Issue
11
Publisher
MDPI
Publisher Location
ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND