Active Chat Monitoring and Suspicious Chat Detection Over Internet

Abstract

In today's digital landscape, the proliferation of online communication platforms has brought about unprecedented opportunities for interaction and collaboration. However, this vast virtual space also presents challenges in ensuring safety and security, particularly concerning the monitoring of chat activities and the detection of suspicious behaviour. This research paper investigates the methods and technologies employed proactive chat monitoring and random chat across the web. The paper begins by examining the importance of monitoring chat platforms to prevent various forms of malicious activities, including cyberbullying, fraud, terrorism, and other illicit behaviours. It then delves into the techniques utilized for real-time monitoring of chat conversations, such as keyword filtering, sentiment analysis, and natural language processing algorithms. Furthermore, the paper explores the principles behind suspicious chat detection, highlighting the indicators of potentially harmful or illegal activities within chat communications. This includes analysing patterns of conversation, identifying anomalous behaviour, and integrating machine learning models to improve detection accuracy. Moreover, the research discusses the ethical considerations and privacy concerns associated with active chat monitoring, emphasizing the need for transparent policies and safeguards to protect user privacy while ensuring effective security measures. Keywords: Active chat monitoring, Suspicious chat detection, Online communication platforms, Cybersecurity, Malicious activities, Keyword filtering, Sentiment analysis, Natural language processing algorithms.