TCP/IP Protocol Stack IR Analysis for Cross-Layer Vulnerability Detection
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Solution Overview
Problem
Existing network protocols in the TCP/IP layered model face significant security vulnerabilities due to cross-layer interactions, which are not adequately addressed by current security measures, leading to issues such as ambiguity, information leakage, false operations, identity fraud, and semantic overload.
Innovation Solution
A method and system for analyzing interaction security in the TCP/IP layered network model by converting protocol stack source codes into intermediate representations (IRs), dividing layers, identifying source and propagation variables, and detecting vulnerabilities using a cross-layer interaction vulnerability set and propagation paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cross-layer interaction is implemented in TCP/IP protocol stack, then functionality and protocol capabilities are improved, but security vulnerabilities and attack surfaces increase
Solution Approach 1:
The patent segments the protocol stack analysis into distinct layers (application, transport, network, link layers) and identifies cross-layer interaction points. By dividing the complex protocol stack into manageable segments and analyzing each layer's interaction with others, the system can detect vulnerabilities at specific cross-layer boundaries without overwhelming complexity.
Solution Approach 2:
The patent introduces intermediate representations (IRs) as a mediator between source code and vulnerability detection. The IRs serve as an intermediate layer that captures protocol semantics and data flows, enabling the detection system to analyze cross-layer interactions without directly parsing complex source code, thus improving both detection accuracy and efficiency.
2Productivity
If automated vulnerability detection is implemented, then security analysis efficiency is improved, but analysis accuracy and detection precision may be compromised
Solution Approach 1:
The patent performs preliminary actions by converting source code to intermediate representations and pre-identifying cross-layer interaction points before actual vulnerability detection. This preliminary processing organizes the data in a structured manner, enabling automated detection to maintain high accuracy while improving efficiency through systematic analysis.
Solution Approach 2:
The patent replaces manual security analysis mechanisms with automated static analysis systems. The system uses computer-executable instructions to automatically traverse protocol layers, track data flows, and detect vulnerabilities, substituting human analysts with algorithmic processes that maintain consistency and scalability.
3Reliability
If detailed protocol stack analysis is performed, then vulnerability detection capability is improved, but system complexity and computational resources increase
Solution Approach 1:
The patent applies local quality by focusing analysis on specific cross-layer interaction points rather than uniformly analyzing the entire protocol stack. The system identifies and concentrates computational resources on critical boundaries where cross-layer vulnerabilities are most likely to occur, such as between application-transport, transport-network, and network-link layers.
Solution Approach 2:
The patent introduces a new dimension of analysis by using intermediate representations that add semantic layering between source code and vulnerability patterns. This additional dimensional layer enables the system to analyze protocol semantics and data flows without increasing physical system complexity, as the IRs provide an abstract view that simplifies the analysis process.
4Loss of information
If cross-layer variable tracking is implemented, then propagation path identification is improved, but computational overhead and processing time increase
Solution Approach 1:
The patent extracts only the critical cross-layer variables and data flows that are relevant to vulnerability propagation, rather than tracking all variables in the protocol stack. By selectively extracting and monitoring only those variables that participate in cross-layer interactions and potential vulnerability chains, the system maintains accurate propagation path identification while reducing computational overhead.
Data Source
AI summary
A method system for analyzing interaction security a TCP/IP layered network model includes: acquiring a cross-layer interaction vulnerability set in the TCP/IP layered network model, and converting target protocol stack source codes into intermediate representations (IRs); dividing a network protocol stack into different layers by scanning the converted IRs, and obtaining source key variables by marking variables for indicating cross-layer interaction in the network protocol stack; obtaining propagation variables by marking variables based on a relationship with the source key variables, and obtaining a propagation path based on a marking sequence of the propagation variables; and obtaining a vulnerability detection result, by performing vulnerability detection based on the propagation path and the cross-layer interaction vulnerability set.