Layered Network Routing for Adversarial Resiliency Planning
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Solution Overview
Problem
Existing communications networks lack efficient methods to identify and mitigate network weaknesses exploited by adversaries and optimize data routing to enhance resiliency against adversarial attacks, leading to potential disruptions and increased operational costs.
Innovation Solution
A prescriptive network resiliency model is employed to model the network as a directed graph, decompose it into layers with different communication priorities, and use a defender-attacker-defender (DAD) algorithm to determine optimal data routing, identify vulnerabilities, and recommend defensive measures, minimizing operational costs and disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional network routing methods are used, then network operations continue with existing infrastructure, but network vulnerabilities remain exposed to adversarial attacks and operational costs increase
Solution Approach 1:
The patent segments the network model into multiple layers (base layer, attack layer, defense layer) to systematically analyze and optimize routing decisions. This segmentation allows the complex resiliency problem to be broken down into manageable computational components while maintaining overall network reliability
Solution Approach 2:
The patent performs preliminary actions by pre-identifying vulnerable arcs through the attack layer analysis and pre-determining optimal defensive strategies before actual adversarial attacks occur. This proactive approach enhances network resiliency by preparing optimized routing paths in advance
2Reliability
If network redundancy is increased to improve resiliency, then more alternative paths are available for data routing, but operational costs and system complexity increase
Solution Approach 1:
The patent changes parameters by dynamically adjusting routing decisions based on layered analysis results, identifying critical arcs that require enhanced protection while reducing redundancy in less critical paths. This optimized parameter adjustment maintains necessary resiliency while minimizing operational costs
3Measurement precision
If comprehensive network analysis is performed to identify all vulnerabilities, then network weaknesses are thoroughly identified, but computational time and processing resources increase
Solution Approach 1:
The patent segments the vulnerability analysis into distinct layers (base network characteristics, potential attack vectors, defensive capabilities) that can be processed independently and efficiently. This segmentation enables comprehensive vulnerability identification without requiring exhaustive analysis of all possible attack scenarios simultaneously
Solution Approach 2:
The patent applies partial action by focusing computational resources on identifying and analyzing the most critical vulnerable arcs rather than attempting to equally analyze all network components. This approach achieves sufficient measurement precision for resiliency optimization while reducing overall computational time
Data Source
AI summary
A method comprising defining a model that represents a communication network, wherein defining the model comprises: formulating a directed graph comprising nodes that represent communication data sources, communication data sinks, and communication data routers of at least a portion of the communication network and arcs connecting nodes that represent communication links between the communication data sources, communication data sinks, and communication data routers, defining a plurality of layers, each layer associated with a different set of communication priorities and comprising a replication of the directed graph, and assigning data communication attributes to the nodes and arcs of each layer, at least a portion of the data communication attributes being associated with different communication priorities; and determining an optimized set of communication flows through the model based on a minimization of communication cost.