Network Address Reputation Scoring for Threat Detection
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Solution Overview
Problem
Current Security Information and Event Management (SIEM) systems face challenges in effectively detecting and mitigating threats from network devices with varying malicious behaviors and vulnerabilities, as they lack a robust mechanism to differentiate between good and bad network addresses based on real-time analysis.
Innovation Solution
The implementation of a reputation-based system that determines and updates the reputation of network addresses and devices by analyzing statistical data and event logs, using a combination of long-term and short-term reputation scores to categorize threat levels and trigger appropriate security actions, such as blocking or sandboxing, based on the behavior of these addresses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional SIEM systems analyze security events without reputation-based differentiation, then they can process all network traffic, but they cannot effectively distinguish between malicious and benign network activities
Solution Approach 1:
The system performs preliminary actions by calculating long-term reputation scores for network addresses before analyzing security events. This pre-computed reputation data is stored and reused to quickly differentiate malicious from benign activities during threat detection, avoiding redundant calculations and improving detection accuracy without proportionally increasing system complexity
Solution Approach 2:
The reputation assessment is segmented into distinct components: long-term reputation based on historical data and short-term reputation based on recent behavior. This segmentation allows the system to process different time scales independently and combine them for comprehensive threat assessment, improving measurement precision while managing complexity through modular design
2Reliability
If the system implements comprehensive reputation analysis for all network addresses, then threat detection accuracy improves, but processing time and computational resources increase
Solution Approach 1:
Long-term reputation scores are calculated and stored in advance based on historical security events and network address behavior. When a new security event occurs, the system retrieves pre-computed reputation data instead of performing full analysis, significantly reducing processing time while maintaining reliable threat detection
Solution Approach 2:
The system updates reputation scores periodically based on new security events and behavior patterns rather than continuously re-evaluating all addresses. This periodic update mechanism maintains detection reliability by incorporating new information while avoiding unnecessary computational overhead during stable periods
3Adaptability or versatility
If the system uses only long-term reputation data, then it has a broad historical perspective, but it cannot detect rapid changes in network address behavior
Solution Approach 1:
The reputation system is segmented into long-term and short-term components that track different time scales of behavior. The short-term reputation specifically captures rapid behavior changes by analyzing recent security events, while the long-term component provides historical context. This segmentation enables detection of rapid changes without requiring the system to process and store all historical data at full resolution
Solution Approach 2:
The system applies partial action by focusing computational resources on calculating short-term reputation for network addresses that exhibit suspicious behavior or recent security events. Not all addresses require full short-term analysis, allowing the system to detect behavior changes efficiently by concentrating data collection on relevant targets rather than uniformly processing all network addresses
Data Source
AI summary
Example embodiments disclosed herein relate to determining a reputation of a network address. A long-term reputation of the network address is determined. A short-term reputation of the network address is determined based on the long-term reputation and trend information associated with the long-term reputation.