Malware Profile Detection for Enterprise Networks
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Solution Overview
Problem
Current malware detection and mitigation techniques are inadequate as nefarious authors continually find ways to circumvent detection methods, necessitating improved identification and prevention strategies.
Innovation Solution
A system comprising a data appliance and security platform that uses static and dynamic analysis, along with malware profiles, to identify and block malicious applications by enforcing policies and generating signatures for known malicious files, and utilizing next-generation firewall technologies for advanced threat prevention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional malware analysis methods are used, then detection capability is limited, but false negatives and false positives increase
Solution Approach 1:
The malware analysis is segmented into multiple independent components: static analysis, dynamic analysis, and malware profile matching. Each component analyzes different aspects of the malware independently, with static analysis examining file properties and dynamic analysis observing runtime behavior. This segmentation allows comprehensive detection while reducing false positives through multi-factor verification.
Solution Approach 2:
The patent adds a new dimension to malware detection by introducing malware profiles that capture behavioral patterns and sequences of actions. Instead of relying solely on traditional signature-based or heuristic methods, the system analyzes malware through multiple dimensions including file structure, runtime behavior, network activity, and sequential action patterns, thereby improving detection accuracy and reliability simultaneously.
2Measurement precision
If comprehensive analysis methods are implemented, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The analysis system is divided into distinct modular components: a static analysis module, a dynamic analysis module, and a profile matching module. Each module performs a specific function and can be independently configured and maintained. This segmentation reduces system complexity by making each component manageable while achieving comprehensive detection through their coordinated operation.
Solution Approach 2:
The patent introduces malware profiles as an intermediary layer between raw malware samples and detection decisions. These profiles serve as pre-defined behavioral patterns that mediate the complex analysis process, allowing the system to match observed malware behavior against known patterns without requiring complex real-time analysis of every possible malware characteristic.
3Speed
If real-time detection is implemented, then threat response time improves, but computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-computing malware profiles from static analysis and preparing detection rules in advance. When real-time detection is needed, the system compares incoming malware samples against these pre-prepared profiles using efficient pattern matching algorithms, significantly reducing the computational resources required for real-time analysis while maintaining fast detection speed.
Solution Approach 2:
The patent applies different levels of analysis depth to different malware samples based on local characteristics. The system first performs lightweight static analysis on all samples, then applies dynamic analysis and profile matching only to samples that exhibit suspicious characteristics. This localized application of computational resources maintains real-time detection capability while reducing overall resource consumption.
Data Source
AI summary
A malware profile is received. The malware profile comprises a set of n-tuples of attributes that describe one or more activities associated with executing a copy of a known malicious application that is associated with the malware profile. A set of one or more log entries is analyzed for a set of entries that matches the malware profile. Based at least in part on identifying the set of entries matching the malware profile, a determination is made that a host was compromised. In response to determining that the host has been compromised, a remedial action is taken with respect to the host.