Adaptive Honeypot Configuration for Network Security
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Solution Overview
Problem
Current intrusion detection and prevention systems (IDPS) face challenges in efficiently monitoring and responding to attacker behavior, requiring complex and time-consuming processes to update response strategies and configure honeypots.
Innovation Solution
A reactive and pre-emptive security system based on choice theory, which includes a computer-implemented method for receiving and processing network traffic data, determining attacker profiles, and configuring honeypots or honeynets accordingly, with the ability to provide these configurations to authorized users upon request.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If honeypots are configured manually according to network activity and attacker behavior, then the honeypot effectiveness and adaptability are improved, but the configuration process becomes complex and time-consuming
Solution Approach 1:
The honeypot system automatically discovers network characteristics, identifies attacker behavior patterns, and configures appropriate honeypot responses without manual intervention. The system monitors network traffic, profiles attackers, and autonomously adjusts honeypot configurations to match detected threat patterns, eliminating the need for manual configuration while maintaining high adaptability
Solution Approach 2:
The system continuously monitors attacker interactions with honeypots, analyzes behavior patterns, and uses this feedback to dynamically adjust honeypot configurations. The feedback loop enables the system to learn from attacker responses and optimize honeypot effectiveness in real-time, maintaining adaptability without requiring manual reconfiguration
2Adaptability or versatility
If multiple honeypots are deployed to handle diverse attacker behaviors, then the coverage and detection capability are improved, but the system complexity and resource requirements increase
Solution Approach 1:
Instead of deploying multiple static honeypots for different attack scenarios, the system uses a single dynamic honeypot that automatically adapts its configuration based on real-time analysis of attacker behavior. The honeypot transforms from a static decoy to a dynamic system that reconfigures itself to match the detected attack pattern, reducing the number of honeypots needed while maintaining comprehensive coverage
Solution Approach 2:
The honeypot system is designed as a multi-functional platform that can respond to various attack types through a single unified architecture. By integrating network discovery, attacker profiling, and adaptive configuration capabilities into one system, it replaces the need for multiple specialized honeypots while maintaining the ability to handle diverse attacker behaviors
3Reliability
If the IDPS continuously monitors and updates attacker profiles and response strategies, then the response effectiveness is improved, but the processing complexity and computational resources increase
Solution Approach 1:
The IDPS system automatically profiles attackers by analyzing network traffic patterns and honeypot interaction data without requiring manual intervention. The system self-updates attacker profiles and generates appropriate response strategies autonomously, reducing processing complexity while maintaining high response effectiveness through automated machine learning and pattern recognition
Data Source
AI summary
The invention provides mechanisms for enhancing the security and protection of a computer-based system or network. It relates, in part, to the use of a decoy (which may be termed “honeypot” or “honeynet”) for collecting attacker-related data, and/or diverting malicious behaviour away from legitimate resources. In one embodiment, the invention provides a method comprising the steps of receiving, processing and logging network traffic data of a plurality of users, where the network traffic is received from a plurality of participating users; determining an attacker profile from the network traffic data; determining a honeypot or honeynet configuration based on the attacker profile; and upon receipt of a valid information request from a user of the plurality of users, providing the determined attacker profile and configuration to the user. Additionally or alternatively, it may provide a computer-implemented method comprising the steps of receiving, processing and logging network traffic data; based on processed network traffic data: determining that network traffic originates from an attacker, determining a risk classification; and determining a decoy configuration based on the risk classification; upon receipt of a valid information request from a user, providing the determined risk classification and decoy configuration to the user.