Automated Immune Response for Malicious Software Detection
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Solution Overview
Problem
Signature-based anti-virus systems are ineffective against newly written viruses and may leave computers vulnerable, as they rely on recognizing known unique strings, while immune response-like approaches like virus throttling can mitigate damage by identifying suspicious behavior and limiting connection rates to prevent infection spread.
Innovation Solution
An automated immune response system that operates in parallel with virus throttling, using behavior logic to identify and respond to malicious software infections by selectively delaying connection requests and potentially isolating or quarantining infected processes without relying on virus signatures, thereby reducing the spread of infections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If signature-based anti-virus systems are used to protect computers, then protection against known viruses is improved, but vulnerability to newly written viruses increases
Solution Approach 1:
The system performs preliminary actions by establishing baseline behavior profiles for uninfected computers before infection occurs. These profiles capture normal connection patterns, resource usage, and system behavior. When infection occurs, the system compares current behavior against these pre-established baselines to detect anomalies, enabling detection of new viruses without relying on signature databases.
Solution Approach 2:
The system implements continuous feedback loops that monitor computer behavior and adjust protection measures in real-time. Behavior monitoring components continuously collect data on system operations, connection patterns, and resource usage. This feedback is processed to update anomaly detection algorithms and adapt to evolving threats, allowing the system to respond dynamically to both known and unknown viruses.
2Object-generated harmful factors
If virus throttling is used to limit connection rates, then spread of infection is reduced, but normal network operations may be affected
Solution Approach 1:
The system applies different connection rate limits to different sources based on their behavior characteristics. Rather than imposing uniform throttling, the system identifies suspicious connection patterns specific to infected systems and applies targeted rate limiting only to those sources. Normal connections from uninfected systems continue without restriction, maintaining ease of operation while preventing infection spread.
Solution Approach 2:
The connection rate limits are dynamic rather than static. The system continuously adjusts throttling parameters based on real-time analysis of connection patterns, system state, and detected threats. Connection rates adapt to traffic conditions, allowing normal operations during low-risk periods while imposing stricter limits when infection spread is detected, thus balancing infection control with operational ease.
3Difficulty of detecting and measuring
If behavior monitoring is implemented to detect infections, then detection capability is improved, but system complexity increases
Solution Approach 1:
The behavior monitoring system is segmented into distinct functional modules: baseline profile creation, real-time behavior collection, anomaly detection algorithms, and response coordination. Each module has a specific responsibility and processes data independently before passing results to the next stage. This segmentation reduces overall system complexity by making each component manageable and independently testable while maintaining comprehensive detection capability.
Solution Approach 2:
The behavior monitoring components are designed to be universal and multi-functional. The same baseline comparison mechanism is used across different types of computers and infection scenarios. Connection pattern analysis, resource usage monitoring, and anomaly detection are implemented as reusable modules that can detect various types of malicious behavior without requiring separate specialized systems, thereby reducing complexity while maintaining broad detection capability.
Data Source
AI summary
Systems, methodologies, media, and other embodiments associated with making an automated immune response on a computer that may be infected with a malicious software like a virus are described. One exemplary system embodiment includes a behavior logic that faciltates identifying that a computer is exibiting a behavior that indicates that the computer may be infected by a malicious software. The exemplary system embodiment may also include an immune response logic that is configured to facilitate identifying a process and/or program related to the behavior. The immune response logic may be configured to automatically make an immune response with respect to the process and/or program.