DoS Vulnerability Assessment via Latency Analysis
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Solution Overview
Problem
Existing technologies struggle to effectively evaluate and mitigate vulnerabilities in public-facing websites to denial-of-service (DoS) and distributed denial-of-service (DDoS) attacks, which can lead to service disruptions and poor user experiences.
Innovation Solution
The described techniques involve interacting with production websites to collect data on response latencies and other attributes that indicate vulnerability to DoS attacks. A computing system analyzes this data to generate a vulnerability score for each website, identifying those at high risk for further analysis and remediation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vulnerability assessment techniques are implemented to identify DoS attack risks, then website security and resilience are improved, but system complexity and assessment overhead increase
Solution Approach 1:
The patent creates a virtual copy or model of the target website's processing behavior. Assessment computing systems interact with this virtual representation to evaluate DoS vulnerability without directly impacting the production system. This copying approach allows comprehensive security testing while isolating the assessment complexity from the target system.
Solution Approach 2:
The patent introduces an intermediary assessment computing system that acts as a mediator between the evaluator and the target website. This intermediary layer handles the complex assessment operations, collects latency data, and generates vulnerability scores without requiring direct modification of the target system's architecture.
2Measurement precision
If comprehensive data collection from production websites is performed to assess vulnerability, then measurement precision is improved, but loss of time and operational disruption increase
Solution Approach 1:
The patent performs preliminary actions by collecting baseline latency data and establishing normal processing patterns before conducting the full vulnerability assessment. This preliminary data collection enables the system to compare assessment data against established baselines, improving measurement precision while minimizing disruption since the baseline can be captured during normal operation.
Solution Approach 2:
The patent implements periodic data collection at intervals rather than continuous monitoring. Assessment computing systems periodically interact with the target website to collect latency values, allowing the system to gather sufficient data for accurate vulnerability assessment while maintaining normal website operations between assessment intervals.
3Loss of information
If latency values are collected to determine processing behavior, then understanding of website implementation is improved, but loss of information about actual user experience increases
Solution Approach 1:
The patent applies local quality by collecting latency data from specific, targeted interactions rather than attempting to capture all user experiences. Assessment systems focus on measuring latency for specific types of requests that are most relevant to DoS vulnerability assessment, rather than trying to represent the complete spectrum of user interactions. This selective approach maintains useful implementation information while acknowledging limitations in representing overall user experience.
Data Source
AI summary
This disclosure describes techniques that include evaluating websites and web services to identify those that are at risk for a denial-of-service attack or a distributed denial-of-service attack. In one example, this disclosure describes a method that includes interacting, by an assessment computing system, with a target computing system, wherein interacting includes issuing a plurality of requests to the target computing system and receiving a plurality of responses to the plurality of requests; identifying, by the assessment computing system and based on the plurality of responses, a plurality of latency values that are attributable to processing performed by the target computing system; and determining, by the assessment computing system and based on the plurality of latency values, whether the target computing system is vulnerable to a denial-of-service attack.