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The Relative Security Metric of Information Systems: Using AIMD Algorithms

Owusu-Kesseh, Daniel
http://orcid.org/0000-0001-5759-0521
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1462278857

Abstract Details

2016, MS, University of Cincinnati, Engineering and Applied Science: Computer Science.
Security metrics are required to provide a quantitative and objective basis for security operations. The quantitative and objective basis is needed to support decision making, quality assurance of Information Technology (IT) products, and the reliable maintenance of the information systems and its operations. There had been numerous ways of quantifying the security metrics of information system using Common Vulnerability Scoring System, version 2.0 (CVSS 2.0) of the products that make up the information system. Some of the approaches are the naive (average and maximum) approach, attack graph approach and Bayesian network (BN)-Based approach but this paper will introduce another way of finding the relative security metrics of information system based on the CVSS 2.0 score of the IT products that make up the system. This new approach is called Additive Increase and Multiplicative Decrease (AIMD) and this paper will also show how to use the AIMD algorithm to determine the security states and the security signature of the IT product.
Fred Annexstein, Ph.D. (Committee Chair)
Kenneth Berman, Ph.D. (Committee Member)
Dieter Schmidt, Ph.D. (Committee Member)
73 p.
Computer Science
Security Metrics; Additive Increase and Multiplicative Decrease; AIMD algorithm; Security Ranking; Common Vulnerability Scoring System; CVSS and AIMD

Recommended Citations

Citations

  • Owusu-Kesseh, D. (2016). The Relative Security Metric of Information Systems: Using AIMD Algorithms [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1462278857

    APA Style (7th edition)

  • Owusu-Kesseh, Daniel. The Relative Security Metric of Information Systems: Using AIMD Algorithms. 2016. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1462278857.

    MLA Style (8th edition)

  • Owusu-Kesseh, Daniel. "The Relative Security Metric of Information Systems: Using AIMD Algorithms." Master's thesis, University of Cincinnati, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1462278857

    Chicago Manual of Style (17th edition)

ucin1462278857
453
© 2016, some rights reserved.Creative Commons License The Relative Security Metric of Information Systems: Using AIMD Algorithms by Daniel Owusu-Kesseh is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by University of Cincinnati and OhioLINK.