IP Address Intelligence via User Behavior Mining
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Solution Overview
Problem
The dynamic nature of Internet Protocol (IP) addresses makes it challenging to effectively combat botnets and malicious activities, as these entities can frequently change their IP addresses, evading protective measures and potentially affecting innocent users.
Innovation Solution
A method and system that mine user behavior data to enhance IP address space intelligence by monitoring and recording user behavior, determining the nature of IP addresses, and characterizing network types, allowing for the detection and tracking of malicious activities across dynamic IP addresses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If IP addresses are monitored to combat botnets, then malicious activity detection is improved, but false positives affecting innocent users increase due to dynamic IP address changes
Solution Approach 1:
The patent segments the IP address monitoring problem into multiple dimensions by introducing behavioral parameters (login patterns, activity timing, interaction frequency) separate from IP address tracking. This segmentation allows the system to distinguish between malicious and innocent users even when they share dynamic IP addresses, reducing false positives while maintaining detection accuracy.
Solution Approach 2:
The patent introduces user behavior data as an intermediary layer between IP address monitoring and malicious activity detection. This intermediary behavioral analysis acts as a mediator that refines the connection between IP addresses and malicious activities, allowing the system to accurately identify threats without mistakenly targeting innocent users with dynamic IP addresses.
2Reliability
If botnets are tracked by IP address, then malicious activity can be prevented, but botnets can evade detection by frequently changing IP addresses
Solution Approach 1:
The patent transitions from static IP address-based tracking to dynamic behavior-based tracking. By monitoring evolving user behavior patterns (login times, activity sequences, interaction frequencies) rather than fixed IP addresses, the system adapts to botnets that frequently change IP addresses, maintaining detection effectiveness against adaptive threats.
Solution Approach 2:
The patent performs preliminary behavior analysis by establishing baseline user behavior patterns before malicious activities occur. This preliminary characterization of normal behavior allows the system to detect deviations indicating botnet activity even when IP addresses change, enabling proactive detection rather than reactive response.
3Productivity
If curative measures are taken against an IP address, then malicious activity is addressed, but innocent users connected through the same IP are affected
Solution Approach 1:
The patent applies local quality by tailoring curative measures to specific user behavior patterns rather than applying blanket IP-based restrictions. By analyzing individual user behaviors (login patterns, activity types, interaction frequencies) associated with each IP address, the system can selectively target malicious activities while preserving access for innocent users, reducing collateral impact while maintaining response efficiency.
Data Source
AI summary
The claimed subject matter is directed to mining user behavior data for increasing Internet Protocol (“IP”) space intelligence. Specifically, the claimed subject matter provides a method and system of mining user behavior within an IP address space and the application of the IP address space intelligence derived from the mined user behavior.In one embodiment, the IP address space intelligence is formed and/or increased with information obtained from the mined user behavior data. A system of uniquely-identified users is monitored and their behavior within the IP address space is recorded. Further data is mined from estimated characteristics about the user, including the nature of the IP address the user uses to log into the service, and characterizing the IP address according to a network type.