Distributed IDS Cluster for IP Reputation Propagation
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Solution Overview
Problem
Current IP reputation systems for intrusion detection are centrally managed, leading to slow propagation of important IP reputation information, which can result in unnecessary exposure of client systems to threats, especially in the context of Advanced Persistent Threats (APTs) that are designed to be lightweight and hard to detect.
Innovation Solution
A cluster of intrusion detection systems is configured to share IP reputation information in real-time or near real-time, using a publish-subscribe mechanism to facilitate data sharing and analysis through an IP reputation analytics engine, enabling early and reliable detection of threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a centralized IP reputation service is used to manage and distribute IP reputation information, then the system structure is simplified and easier to manage, but the propagation speed of IP reputation information becomes slow, causing client systems to remain exposed to threats for longer periods
Solution Approach 1:
The patent divides the centralized IP reputation service into multiple distributed IDS nodes that each maintain local IP reputation databases. Instead of a single central authority, the system segments the reputation management function across multiple independent nodes that can operate autonomously while sharing information through peer-to-peer communication.
Solution Approach 2:
The patent combines the IP reputation database functionality directly into each IDS node, merging the advantages of distributed processing with local reputation checking capabilities. Each node maintains its own IP reputation data while simultaneously participating in the collective intelligence of the distributed network.
2Ease of operation
If a centralized IP reputation service is used, then the system is easier to manage and deploy, but the response time for detecting and alerting about new threats becomes delayed, leaving network vulnerabilities exposed
Solution Approach 1:
The patent implements preliminary action by having each IDS node continuously maintain and update its local IP reputation database in advance. When a new threat is detected, the information is immediately propagated to neighboring nodes before the centralized system could potentially respond, enabling proactive threat blocking at the network edge.
Solution Approach 2:
The patent establishes feedback loops where each IDS node continuously monitors for new threats and immediately shares updated IP reputation information with other nodes. This real-time feedback mechanism ensures that all nodes in the distributed network are rapidly informed of new threats, enabling swift collective response.
3Device complexity
If IP reputation information is propagated through a single central system, then the system architecture remains simple, but multiple client systems remain unnecessarily exposed to rogue sources while waiting for updates
Solution Approach 1:
The patent segments the IP reputation service into multiple distributed nodes, where each node independently maintains and enforces IP reputation policies. This segmentation eliminates the single point of failure inherent in centralized systems and ensures that each client system receives protection from its nearest IDS node without waiting for central system updates.
Solution Approach 2:
The patent introduces intermediary IDS nodes that sit between the central system and client systems, acting as local mediators for IP reputation enforcement. These intermediary nodes can immediately block suspicious traffic based on locally cached reputation data, providing reliable protection even when the central system is slow to respond or unavailable.
Data Source
AI summary
An intrusion detection system (IDS) is enhanced to operate in a cluster of such systems, and IDSs organized into a cluster cooperate to exchange IP reputation influencing events information between or among the cooperating systems in real-time to enhance overall system response time and to prevent otherwise hidden attacks from damaging network resources. An IDS includes an IP reputation analytics engine to analyze new and existing events, correlate information, and to raise potential alerts. The IP reputation analytics engines may implement an algorithm, such as a pattern matching algorithm, a continuous data mining algorithm, or the like, to facilitate this operation. Clustering IDS endpoints to share IP reputation influencing events, using the cluster-wide view to determine IP reputation, and feeding the cluster-wide view back to the IDS endpoints, provides for enhanced and early detection of threats that is much more reliable and scalable as compared to prior art techniques.