# A Systematic Literature Review of Information Security in Chatbots
## 5 Discussion  
Although the reviewed literature provides a comprehensive overview of the security threats and vulnerabilities associated with chatbots and the approaches proposed to address them, there are still areas where additional research is needed to address specific security issues. One such area is the need for more research on authentication and authorization mechanisms for chatbots. Article [7] highlights the vulnerability of chatbots to insecure authentication and data integrity issues, which can be exploited by attackers to gain unauthorized access to sensitive information. While some studies, such as article [10], propose solutions for secure authentication and encryption mechanisms, more research is needed to identify effective and scalable solutions that can be implemented in different chatbot contexts and scenarios. Another area where additional research is needed is the detection and prevention of malicious chatbots. Article [3] discusses the potential of malicious chatbots to harm users and highlights the need for more research on identifying and detecting malicious chatbots. Additionally, more research is needed to develop effective and efficient methods for monitoring chatbots and detecting suspicious behavior, such as that described in article [8], which proposes a design and framework for a cyber-aware chatbot service that detects and helps prevent malware behavior from spreading on the user's machine. Furthermore, more research is needed on the security risks and ethical issues relating to information security in chatbot implementation, as highlighted in article [15]. Specifically, more research is needed to develop frameworks and guidelines for ensuring the confidentiality, integrity, and availability of user data, as well as address ethical concerns relating to user privacy and data ownership. Lastly, there is a need for more research on the impact of chatbots on social engineering attacks. Article [2] suggests that chatbots could be exploited by attackers to conduct social engineering attacks, but more research is needed to understand the extent to which chatbots are vulnerable to these types of attacks and to identify effective countermeasures. Besides additional research, we might also consider some best practices for developing secure chatbots. The following are some best practices for developing secure chatbots:  
Conduct comprehensive security assessments: One of the best practices for developing secure chatbots is to conduct comprehensive security assessments throughout the entire chatbot development process. Developers should conduct security testing at different stages of development to identify and mitigate vulnerabilities before the chatbot is deployed. These assessments should cover all modules in the chatbot architecture, including the client module, communication module, response generation module, and database module. For example, a developer could use tools such as static analysis to identify code-level vulnerabilities such as buffer overflows or SQL injections and dynamic analysis tools to test for vulnerabilities during runtime. Implement user authentication and authorization: Another best practice for developing secure chatbots is to implement user authentication and authorization. Developers should ensure that the chatbot requires users to authenticate themselves before accessing sensitive data or services. Authentication could involve traditional username and password combinations, two-factor authentication, biometric authentication, or autonomous inquiry-based authentication [32]. Additionally, authorization should be implemented to ensure that users only have access to data or services that they are authorized to access. For example, a chatbot used for banking should only allow users access to their own accounts. Use encryption for data protection: To protect sensitive data in chatbots, developers should implement encryption. Encryption can protect data from being intercepted and viewed by unauthorized parties during transmission.