Malware Path Traceback and Categorization for Drive-by Attacks
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Solution Overview
Problem
Current systems are ineffective in tracing and mitigating malware download paths, particularly in drive-by and social engineering attacks, as they rely on URL blacklisting and do not provide comprehensive context for malicious activities, leading to high infection rates in sensitive networks.
Innovation Solution
A malware path detection and countermeasure system that includes an attack path traceback and categorization module to automatically trace and label web paths leading to malware downloads, distinguishing between drive-by and social engineering attacks, and providing countermeasures by identifying and blocking malicious domain names and code injection points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If URL blacklisting is used to block malware, then implementation is simple, but detection precision and effectiveness are insufficient leading to high infection rates
Solution Approach 1:
The system segments the malware detection problem into multiple components: path reconstruction (tracing web pages visited), categorization (classifying attack types), and countermeasure generation (identifying blocking strategies). This segmentation allows each component to be optimized independently, achieving high detection precision without requiring a monolithic complex system.
Solution Approach 2:
The system performs preliminary actions by reconstructing and analyzing the complete web path before the malware download occurs. By tracing the sequence of web pages visited and categorizing the attack type in advance, the system can generate appropriate countermeasures proactively, improving detection precision before the actual infection happens.
2Reliability
If comprehensive path tracing is implemented to track malware download paths, then detection effectiveness improves, but system complexity and computational resources increase
Solution Approach 1:
The path reconstruction module serves multiple functions: it traces web paths for detection, categorizes attack types, identifies code injection points, and generates countermeasures. This multi-functionality achieves high reliability through comprehensive analysis while avoiding the need for separate specialized systems for each function, thereby controlling overall system complexity.
Solution Approach 2:
The system uses existing web browser referrer headers and HTTP transaction data to reconstruct paths, rather than requiring additional specialized tracing infrastructure. By leveraging data already generated during normal web browsing, the system achieves reliable path tracing without proportionally increasing system complexity or computational overhead.
3Productivity
If automatic path reconstruction and categorization is used, then response time to malware threats improves, but computational resources and processing time increase
Solution Approach 1:
The system applies partial action by focusing computational resources on analyzing only the relevant web path transactions associated with detected malware downloads, rather than processing all network traffic. This selective analysis achieves fast response to malware threats while avoiding the excessive computational energy consumption that would result from comprehensive analysis of all network activity.
Solution Approach 2:
The system uses feedback from malware detection events to trigger path reconstruction and analysis. When a malware download is detected, the system reconstructs and analyzes the associated web path, generating countermeasures based on the categorized attack type. This event-driven feedback mechanism ensures rapid response to actual threats while minimizing unnecessary computational energy consumption during normal operation.
Data Source
AI summary
Systems and methods for event path traceback may utilize a processor and a path traceback and categorization (ATC) module in communication with the processor. The processor may be configured to perform processing associated with receiving network traffic from a network. The ATC module may be configured to perform processing associated with identifying an event within the network traffic, tracing a sequence of network transactions related to the event, and outputting an annotated event path (AMP) including data about the event and the sequence of network transactions related to the event. Performing processing associated with tracing the sequence of network transactions may comprise reconstructing a sequence of transactions within the network traffic that led to the event while filtering out unrelated traffic within the network traffic.