Automated Cyber Vulnerability Assessment for Embedded Systems

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Solution Overview

Problem

Existing methods for vulnerability analysis of embedded systems and systems-of-systems are inefficient due to their reliance on manual, error-prone, and resource-intensive techniques, which are not feasible in operationally relevant timeframes and often overlook vulnerabilities in firmware and distributed embedded systems.

Innovation Solution

An automated Cyber Vulnerability Assessment (CVA) system using static and dynamic semantic system models to identify vulnerabilities and anomalies, allowing for automated security risk flagging and mitigation without requiring source code or executables, by analyzing the system's structure and behavior through probing and observation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual vulnerability analysis is performed by cyber experts, then expertise and human judgment are applied, but the process is error-prone, time-consuming, and not feasible in operationally relevant timeframes

Engineering Contradiction:

Improvevulnerability detection accuracyVSAvoidanalysis time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical analysis processes with automated computer-based systems. The vulnerability assessment system uses automated data collection, semantic model generation, and attack path analysis algorithms to substitute human experts, thereby eliminating time constraints and human errors while maintaining detection accuracy.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-assessment capabilities where the embedded system automatically generates semantic models from its own operational data and configuration information. The automated vulnerability assessment process allows the system to evaluate itself without external human intervention, significantly reducing analysis time while maintaining comprehensive coverage.

Inventive Principle:

Principle #25Self-service

2Reliability

If resource-intensive techniques such as model checking are applied, then thorough vulnerability analysis is achieved, but the techniques are precluded by performance constraints of embedded systems

Engineering Contradiction:

Improvevulnerability analysis thoroughnessVSAvoidcomputational resource consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent applies partial action by focusing vulnerability analysis on specific attack paths and critical components rather than performing exhaustive model checking of entire embedded systems. The semantic model approach selectively analyzes data flows and interactions relevant to security, achieving thorough vulnerability detection without requiring full-system resource-intensive modeling.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The vulnerability assessment process is segmented into distinct phases: data collection, semantic model generation, attack path analysis, and vulnerability reporting. Each phase processes specific portions of system information independently, reducing the computational burden on embedded systems while maintaining comprehensive analysis through systematic breakdown of the assessment task.

Inventive Principle:

Principle #1Segmentation

3Measurement precision

If source code or binary examination is performed, then detailed firmware analysis is possible, but source code or executables are not always available in deployed systems

Engineering Contradiction:

Improvefirmware vulnerability detectionVSAvoidaccessibility to system resources

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The patent creates semantic models that serve as virtual copies of the embedded system's architecture, data flows, and component interactions. These semantic models replicate essential system characteristics without requiring access to actual source code or binaries, enabling vulnerability analysis through observation and probing of system behavior and configuration data.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The semantic model acts as an intermediary between the vulnerability assessment system and the embedded system. Instead of directly examining source code or binaries, the system uses semantic models generated from observable system characteristics to infer vulnerabilities, bridging the gap when direct access to firmware resources is unavailable.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11297081B2Methods and systems for eliminating and reducing attack surfaces through evaluating reconfigurations

Publication Date: 2022.04.05 RTX BBN TECH INC

AI summary

A method of performing a security assessment of a system includes analyzing a static structure of the system; storing, in a semantic system model, structure information about the static structure of the system; observing the system during a plurality of discrete temporal system states; storing, in the semantic system model, dynamic information about the system during the plurality of discrete temporal system states; performing a semantic composition analysis on the structure information to identify at least one vulnerability of the system; performing a flow analysis on the dynamic information to identify at least one anomalous behavior of the system during at least one of the plurality of discrete temporal system states; and generating, based on the at least one vulnerability of the system and the at least one anomalous behavior of the system, a vulnerability assessment of the system.