Resource Utilization Signatures for Malicious Task Detection
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Solution Overview
Problem
On-demand code execution systems face challenges in detecting and preventing the execution of malicious tasks without compromising user privacy or impacting system efficiency, as existing methods may be thwarted by obfuscated or encrypted malicious code, and can lead to resource inefficiencies.
Innovation Solution
Implementing a resource signature management system that generates and analyzes resource utilization signatures to identify malicious tasks by monitoring computing resource usage without accessing the code or its content, allowing for early detection and prevention of malicious task execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If code inspection methods are used to detect malicious tasks, then security detection capability is improved, but user privacy is compromised and detection can be thwarted by obfuscated code
Solution Approach 1:
The patent introduces resource utilization signatures as an intermediary mechanism that indirectly characterizes code behavior without exposing the code itself. Instead of directly inspecting user-submitted code, the system monitors resource consumption patterns (CPU, memory, I/O) and compares these signatures against known malicious patterns, thereby detecting threats while preserving code privacy.
Solution Approach 2:
The patent replaces the mechanical code inspection approach with a behavioral monitoring system. Instead of analyzing code structure and content directly, the system substitutes this with monitoring the runtime resource utilization characteristics of executing tasks, transforming the detection mechanism from static code analysis to dynamic behavioral observation.
2Measurement precision
If comprehensive code analysis is performed to detect malicious tasks, then detection accuracy is improved, but system efficiency deteriorates due to resource overhead
Solution Approach 1:
The patent extracts only the essential resource utilization metrics needed for malicious task detection, rather than performing comprehensive code analysis. By focusing specifically on resource consumption patterns (CPU usage, memory allocation, I/O operations), the system achieves effective detection while minimizing the analytical overhead and maintaining high system efficiency.
Solution Approach 2:
The patent applies partial action by monitoring only the critical resource utilization aspects necessary for detecting malicious behavior, rather than analyzing all code characteristics. This selective monitoring approach provides sufficient detection accuracy while avoiding the excessive computational burden of complete code inspection.
3Loss of information
If resource utilization monitoring is implemented to detect malicious tasks, then privacy preservation is improved, but detection capability may be reduced compared to direct code inspection
Solution Approach 1:
The patent changes the detection parameters from code-level characteristics to resource utilization characteristics. By monitoring how tasks consume computational resources rather than analyzing code structure directly, the system maintains detection capability through behavioral signatures while preserving privacy through indirect observation of resource patterns.
Solution Approach 2:
The patent uses resource utilization signatures as a form of behavioral 'coloring' that characterizes malicious tasks without exposing their underlying code identity. Similar to how color can identify an object without revealing its material composition, resource patterns identify malicious intent while preserving code privacy.
Data Source
AI summary
Systems and methods are described for detecting and preventing execution of malware on an on-demand code execution system. An on-demand code execution system may execute user-submitted code on virtual machine instances, which may be provisioned with various computing resources (memory, storage, processors, network bandwidth, etc.). These resources may be utilized in varying amounts or at varying rates during execution of the user-submitted code. The user-submitted code may also be unavailable for inspection for security or other reasons. A malware detection system may thus identify user-submitted code that corresponds to malware by monitoring resource utilization during execution of the code and generating a resource utilization signature, which enables comparison between the signature of the user-submitted code and resource utilization signatures of codes previously identified as malware. The malware detection system may then take actions such as notifying the user who requested execution or preventing execution of the user-submitted code.