Networked Device Testing With Adaptive Fuzzing for Edge Clouds

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Solution Overview

Problem

Existing networked device testing methods are inadequate for efficiently identifying software vulnerabilities and security gaps in resource-constrained Edge computing environments, particularly in Edge clouds with dynamic network conditions and multi-tenant scenarios.

Innovation Solution

Employing dynamic feedback-based fuzzing techniques and route-exploration scripts to generate test inputs that adapt to network changes, using P4-based representations of network protocols and devices, and creating sandboxes for testing at varying granularities to identify discrepancies between formal specifications and actual implementations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If dynamic feedback-based fuzzing techniques are employed, then the ability to identify software vulnerabilities is improved, but the computational resources required increase

Engineering Contradiction:

Improvevulnerability detection accuracyVSAvoidcomputational resource consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system implements dynamic feedback-based fuzzing where test inputs are generated and executed, results are analyzed, and subsequent test inputs are adjusted based on previous outcomes. This feedback loop enables adaptive exploration of network device behaviors and state transitions, improving vulnerability detection while managing resource usage through intelligent test case selection

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The testing system dynamically adapts its behavior based on runtime conditions, adjusting test input generation strategies according to observed device states, network conditions, and vulnerability patterns. This dynamic approach allows the system to concentrate computational resources on high-risk areas while maintaining comprehensive coverage

Inventive Principle:

Principle #15Dynamics

2Reliability

If comprehensive testing at multiple granularities is performed, then software security is improved, but testing complexity increases

Engineering Contradiction:

Improvesoftware securityVSAvoidtesting system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The testing system divides the network device under test into functional segments or modules, applying targeted test suites to each segment. This segmentation allows comprehensive security testing at multiple granularities (individual functions, protocols, or device components) while managing complexity through modular test organization and execution

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The testing platform implements a universal framework that can execute multiple types of tests (fuzzing, validation, compliance checking) across different network device types and protocols. This multi-functional approach provides comprehensive security coverage while reducing overall system complexity through a unified testing architecture

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Adaptability or versatility

If adaptive test input generation is used, then testing effectiveness in dynamic networks is improved, but processing time increases

Engineering Contradiction:

Improvenetwork condition adaptabilityVSAvoidtest execution time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system performs preliminary analysis of network device specifications, protocols, and expected behaviors before executing comprehensive tests. This preliminary action includes generating initial test input sets and establishing baseline expectations, which accelerates subsequent adaptive testing by providing a head start on understanding the device under test

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The testing system dynamically adjusts test parameters such as input data rates, protocol variations, and state transition sequences based on observed network conditions and device responses. These parameter changes enable adaptive testing that responds to dynamic network environments while maintaining efficient execution through intelligent parameter selection

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12360160B2Systems and methods for networked device testing

Publication Date: 2025.07.15 INTEL CORP

AI summary

Methods, apparatus, systems, and articles of manufacture for networked device testing are disclosed. An example method includes determining an input to be applied to a programmable network device, mutating the input to determine an input variant, applying the input variant to the programmable network device, and in response to determining that the input variant causes the programmable network device to enter an expected state, add the input variant to a test set.