A Loopix-Based Anonymous Network with Selective Anonymity Removal and AI-Driven Adaptability for Configurable Networks

Abstract

Anonymity networks are crucial for safeguarding user privacy, but they constantly struggle to strike a balance between security, performance, and anonymity because enhancing one of these factors frequently has an impact on the others. To maintain important anonymity properties, such as sender and recipient anonymity, communication relationship confidentiality, unlikability, and unobservability, while enabling the network to adapt to various environments and operational requirements, this paper presents a configurable anonymity network architecture based on the Loopix framework. The framework applies to a variety of scenarios because the proposed architecture enables network designers and administrators to configure network components according to security objectives, desired anonymity levels, control policies, and deployment conditions. Probabilistic random delays, cover traffic generation, and intelligent packet-size normalisation are mechanisms used to fortify the network against traffic analysis, flow correlation, and website fingerprinting attacks. Additionally, an artificial intelligence-based security layer analyses Internet requests in real time and finds suspicious activity and potentially malicious resources before they become security threats by combining text and image processing models with a threat intelligence database. In accordance with predetermined network policies, a selective deanonymization mechanism activates upon detection of malicious activity, enabling controlled access management and security enforcement while protecting authorised users' privacy. According to the conceptual analysis, combining a configurable anonymity framework with artificial intelligence-driven security mechanisms can achieve a practical balance between privacy preservation, security requirements, and network efficiency. Overall, the suggested framework offers a versatile, adaptable method for implementing anonymity networks in operational contexts where responsible security control and user privacy are necessary.