Cybersecurity Threat Detection Assessment via Statistical Analysis
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Solution Overview
Problem
It is challenging to objectively assess the effectiveness of cybersecurity threat detection programs, particularly for vehicular systems, as existing methods rely on subjective claims and lack objective evaluation criteria.
Innovation Solution
A method involving statistical analysis of test result data from manipulated threat datasets, using a processor to determine the effectiveness of cybersecurity threat detection programs by comparing test results under different operating conditions, such as highway and urban travel, without the need for installation on a vehicle computer system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cybersecurity threat detection programs make subjective claims about their effectiveness, then they can be developed and deployed quickly, but it becomes difficult to objectively assess how good a particular program is
Solution Approach 1:
The patent replaces subjective human assessment with automated statistical analysis. Test results from multiple data sets are processed through statistical algorithms that objectively calculate effectiveness metrics, eliminating the need for manual evaluation while maintaining high assessment accuracy.
Solution Approach 2:
The patent transforms qualitative subjective claims into quantitative measurable parameters. By defining specific statistical metrics (detection rate, false positive rate, etc.) and calculating them from test data, the system converts vague effectiveness claims into precise numerical values that can be objectively compared.
2Reliability
If cybersecurity threat detection programs are tested under multiple different operating conditions, then the assessment becomes more comprehensive and reliable, but the complexity of the testing process increases
Solution Approach 1:
The patent divides the testing process into separate, independent data sets, each representing a specific operating condition. By segmenting the test environment into distinct data sets (e.g., highway travel, urban travel), the system can comprehensively evaluate performance across multiple conditions while keeping each individual test simple and manageable.
Solution Approach 2:
The patent uses multiple copied data sets that represent different operating conditions. Instead of creating complex physical test environments, the system creates virtual copies of operational scenarios through manipulated threat data, allowing comprehensive testing without proportional increases in physical complexity.
3Measurement precision
If statistical analysis is performed on test result data from multiple data sets, then objective and verifiable effectiveness results are produced, but the computational processing requirements increase
Solution Approach 1:
The patent applies statistical analysis selectively to the most critical effectiveness metrics rather than performing exhaustive analysis on all possible parameters. By focusing computational resources on key measurements (detection rate, false positive rate), the system achieves high objectivity in assessing effectiveness while avoiding unnecessary computational overhead.
4Ease of operation
If the cybersecurity threat detection program is assessed without installation on a vehicle computer system, then the assessment process becomes simpler and faster, but the ability to evaluate real-world performance may be reduced
Solution Approach 1:
The patent introduces manipulated threat data as an intermediary between the detection program and real-world scenarios. These artificially constructed data sets simulate real threat conditions while allowing testing in a controlled environment, bridging the gap between simplified lab testing and complex real-world deployment.
Data Source
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AI summary
A cybersecurity threat detection program effectiveness assessment method (200) comprising: receiving a first test result data (130) obtained from threat testing a first data set (120) comprising manipulated threats data by a first cybersecurity threat detection program (110); receiving a second test result data (130) obtained from threat testing a second data set (120) comprising manipulated threats data by the first cybersecurity threat detection program (110); statistically analysing, by a processor (102), the first test result data (130) together with the second test result data (130); and determining, by the processor (102), a first statistical analysis result data (140) that indicates the effectiveness of the first cybersecurity threat detection program (110).