AI-Driven Chatbot for Intrusion Detection in Edge Networks: Enhancing Cybersecurity with Ethical User Consent

• URL: http://arxiv.org/abs/2408.04281v1
• Date: Thu, 8 Aug 2024 07:39:23 GMT
• Title: AI-Driven Chatbot for Intrusion Detection in Edge Networks: Enhancing Cybersecurity with Ethical User Consent
• Authors: Mugheez Asif, Abdul Manan, Abdul Moiz ur Rehman, Mamoona Naveed Asghar, Muhammad Umair,
• Abstract summary: We propose an architecture that enhances security within edge networks specifically for intrusion detection. By securing the network environment using an edge network managed by a Raspberry Pi module, we aim to safeguard sensitive data and maintain a secure workplace.
• Score: 1.3643061988716354
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In today's contemporary digital landscape, chatbots have become indispensable tools across various sectors, streamlining customer service, providing personal assistance, automating routine tasks, and offering health advice. However, their potential remains underexplored in the realm of network security, particularly for intrusion detection. To bridge this gap, we propose an architecture chatbot specifically designed to enhance security within edge networks specifically for intrusion detection. Leveraging advanced machine learning algorithms, this chatbot will monitor network traffic to identify and mitigate potential intrusions. By securing the network environment using an edge network managed by a Raspberry Pi module and ensuring ethical user consent promoting transparency and trust, this innovative solution aims to safeguard sensitive data and maintain a secure workplace, thereby addressing the growing need for robust network security measures in the digital age.

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