SIEM Detection Gap Analysis Using Simulated Attack Files
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Solution Overview
Problem
Existing SIEM systems lack the ability to effectively analyze the protective functions of IT operating environments, leading to potential gaps in detection capabilities, especially in dynamic and evolving IT landscapes.
Innovation Solution
A system and method that proactively exposes IT environments to simulated attacks using varied attack files and codes, analyzing device responses to identify and address detection gaps, utilizing an analysis unit, allocation means, and detection means to evaluate the effectiveness of protective functions and SIEM detection capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SIEM systems monitor and categorize security events continuously, then detection capability improves, but false positive rate increases and system complexity increases
Solution Approach 1:
The system segments the complex SIEM evaluation process into modular components: attack units that execute specific attack scenarios, detection units that monitor for particular threats, and analysis units that evaluate results. Each component handles a specific aspect of security monitoring, reducing overall system complexity while maintaining comprehensive detection capability.
Solution Approach 2:
The system performs preliminary actions by proactively executing simulated attacks against the IT environment before real threats occur. Attack files and attack codes are prepared and stored in advance, allowing the SIEM system to be evaluated under controlled conditions that mimic real attack scenarios, thereby improving detection precision without the chaos of live attacks.
2Measurement precision
If SIEM systems increase sensitivity to capture all relevant events, then detection completeness improves, but false positive rate increases
Solution Approach 1:
The system implements feedback mechanisms where the results of simulated attacks are fed back into the SIEM system for analysis. The analysis units evaluate whether the SIEM correctly detected the simulated threats and generate reports on detection accuracy. This feedback loop allows for tuning of detection sensitivity to optimize the balance between detection completeness and false positive reduction.
Solution Approach 2:
The system changes parameters by using varied attack files and attack codes with different characteristics, severities, and detection signatures. By testing the SIEM against multiple attack variants, the system can evaluate detection performance across different parameter ranges and adjust sensitivity thresholds to achieve optimal detection completeness while minimizing false positives.
3Adaptability or versatility
If the IT landscape and attack methods constantly change, then adaptability requirements increase, but maintaining detection accuracy becomes more difficult
Solution Approach 1:
The system embraces dynamics by continuously updating the library of attack files and attack codes to reflect evolving threat landscapes. The attack unit can execute new attack scenarios as they emerge, and the analysis unit evaluates the SIEM's ability to detect these dynamic threats. This dynamic approach allows the system to maintain detection accuracy despite changing attack methods by constantly adapting the test suite to current threats.
Data Source
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AI summary
The present invention relates to a system (1) for determining IT security-relevant detection gaps in an IT operating environment (2), at least comprising an analysis unit (4), an attack unit (6) for providing a plurality of mutually different attack files (8) and/or attack codes (10) for modifying the functionality of a plurality of devices (12) in the IT operating environment (2), wherein the plurality of devices (12) belong to one device type (14) and/or different device types (14.1 to 14.n), a plurality of allocation means (18) for identifying and/or addressing the plurality of devices (12), wherein each of the plurality of devices (12) is identifiable and/or addressable by at least one allocation means (18), in particular by a respective allocation means (18), for receiving the attack file (8) and/or the attack code (10), and a plurality of detection means (20).