Risks for Conversational AI Security
Vivek Bhardwaj, Safdar Sardar Khan, Gurpreet Singh, Sunil Patil, Devendra Kuril, Sarthak Nahar · 2024
Conversational artificial intelligence (AI) systems have become increasingly popular, and their integration into various industries has grown significantly. With the advent of advanced technologies like machine learning and natural language processing, conversational AI has become capable of performing complex tasks, including processing customer requests, providing recommendations, and facilitating transactions. However, these systems are also vulnerable to various security risks that can expose sensitive data and compromise the privacy of users. This paper provides a comprehensive review of the risks associated with conversational AI security, including attacks such as phishing, malware injection, and voice cloning. The paper also discusses the potential impact of these attacks on businesses and end-users and proposes strategies to mitigate these risks [1]. Conversational AI is a rapidly growing field, with a wide range of applications such as customer service, personal assistants, and healthcare. However, with the increasing use of conversational AI, there are also growing concerns about the security risks associated with these systems. This research paper aims to explore the risks associated with conversational AI security, including privacy breaches, data leakage, and manipulation of conversational agents. This paper also discusses the current state of research in this area and proposes recommendations for improving conversational AI security. Conversational AI has gained significant popularity in recent years due to its ability to enable natural and seamless interactions between humans and machines. However, with the increasing use of conversational AI, the risks for security have also increased. The risks for conversational AI security include both technical and non-technical threats that can compromise the confidentiality, integrity, and availability of sensitive information. This paper provides an overview of the risks associated with conversational AI security, including threats such as data breaches, malicious attacks, impersonation attacks, and social engineering attacks. It also discusses the measures that can be taken to mitigate these risks, including implementing secure authentication mechanisms, using encryption, monitoring user behavior, and adopting a risk management approach. Ultimately, understanding the risks for conversational AI security is crucial for organizations to develop effective security strategies and protect their sensitive information from potential threats.