IP-Based Intrusion Detection for Account Security
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Solution Overview
Problem
Current security systems face challenges in distinguishing unauthorized intrusions from authorized user activities, particularly when attackers use stolen login credentials and automated devices attempt multiple username-password pairs, leading to false positives and difficulties in identifying intrusions.
Innovation Solution
The system employs IP-based intrusion detection by analyzing login requests from a specific IP address over a threshold time period, checking the number of requests, success ratio, and distinct usernames, and initiating security actions if thresholds are met, including blocking access and forcing password resets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional username-password authentication is used, then user access is granted, but the system cannot distinguish unauthorized intrusions from authorized user activities
Solution Approach 1:
The patent segments the authentication verification process into multiple independent checks: IP address analysis, login pattern recognition, behavioral biometrics, and credential validation. By dividing the detection task into separate analytical components, the system can evaluate multiple factors simultaneously to distinguish authorized users from intruders, resolving the contradiction between granting access and detecting intrusions.
Solution Approach 2:
The patent introduces an intermediary security analysis layer between the authentication system and the resource access layer. This intermediary component analyzes login requests, IP addresses, and behavioral patterns before granting access, acting as a mediator that enables both authentication and intrusion detection without compromising either function.
2Difficulty of detecting and measuring
If security checks are performed on login requests, then intrusions can be detected, but false positives increase and legitimate users are blocked
Solution Approach 1:
The patent applies local quality by implementing differentiated security analysis for different IP addresses, user accounts, and login patterns. Instead of uniform security checks, the system tailors the depth and type of analysis based on local characteristics such as IP reputation, user behavior history, and login context, reducing false positives while maintaining detection capability.
Solution Approach 2:
The patent dynamically changes security parameters such as threshold values, analysis depth, and check intensity based on risk assessment. When login patterns appear suspicious, the system increases scrutiny; when patterns are normal, it reduces checks. This adaptive parameter adjustment resolves the contradiction by making detection sensitivity variable rather than fixed.
3Difficulty of detecting and measuring
If multiple login attempts are monitored, then intrusion patterns can be identified, but system complexity increases
Solution Approach 1:
The patent implements a universal security analysis module that handles multiple detection functions: IP address validation, login pattern recognition, behavioral analysis, and credential verification. By consolidating these functions into a single multi-functional component, the system reduces overall complexity while maintaining comprehensive intrusion detection capabilities.
Data Source
AI summary
Systems and methods for account security are provided. In one example embodiment, a first login request including a username and a password is analyzed to identify a first internet protocol (IP) address and a first request time associated with the first login request. A login history comprising login request data for the server computer is analyzed to identify a plurality of usernames, wherein each username of the plurality of usernames is associated with a corresponding login request from the first IP address within a threshold time period of the first request time. In response to determining a login success ratio is below a threshold login success ratio and a number of unique usernames in the analyzed data is above the unique username threshold, the system automatically performs a security action.