Model for Quantifying the Quality of Secure Service
Although not common today, communications networks could adjust security postures based on changing mission security requirements, environmental conditions, or adversarial capability, through the coordinated use of multiple channels. This will require the ability to measure the security of communica...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-05-01
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| Series: | Journal of Cybersecurity and Privacy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2624-800X/1/2/16 |
| _version_ | 1797527911364820992 |
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| author | Paul M. Simon Scott Graham Christopher Talbot Micah Hayden |
| author_facet | Paul M. Simon Scott Graham Christopher Talbot Micah Hayden |
| author_sort | Paul M. Simon |
| collection | DOAJ |
| description | Although not common today, communications networks could adjust security postures based on changing mission security requirements, environmental conditions, or adversarial capability, through the coordinated use of multiple channels. This will require the ability to measure the security of communications networks in a meaningful way. To address this need, in this paper, we introduce the Quality of Secure Service (QoSS) model, a methodology to evaluate how well a system meets its security requirements. This construct enables a repeatable and quantifiable measure of security in a single- or multi-channel network under static configurations. In this approach, the quantification of security is based upon the probabilities that adversarial listeners and disruptors may gain access to or manipulate transmitted data. The initial model development, albeit a snap-shot of the network security, provides insights into what may affect end-to-end security and to what degree. The model was compared against the performance and expected security of several point-to-point networks, and three simplified architectures are presented as examples. Message fragmentation and duplication across the available channels provides a security performance trade-space, with an accompanying comprehensive measurement of the QoSS. The results indicate that security may be improved with message fragmentation across multiple channels when compared to the number of adversarial listeners or disruptors. This, in turn, points to the need, in future work, to build a full simulation environment with specific protocols and networks to validate the initial modeled results. |
| first_indexed | 2024-03-10T09:50:34Z |
| format | Article |
| id | doaj.art-2471088288ec4eac89f1f4f0676f2bd1 |
| institution | Directory Open Access Journal |
| issn | 2624-800X |
| language | English |
| last_indexed | 2024-03-10T09:50:34Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Cybersecurity and Privacy |
| spelling | doaj.art-2471088288ec4eac89f1f4f0676f2bd12023-11-22T02:43:34ZengMDPI AGJournal of Cybersecurity and Privacy2624-800X2021-05-011228930110.3390/jcp1020016Model for Quantifying the Quality of Secure ServicePaul M. Simon0Scott Graham1Christopher Talbot2Micah Hayden3Air Force Institute of Technology, 2950 Hobson Way, Wright-Patterson AFB, OH 45433, USAAir Force Institute of Technology, 2950 Hobson Way, Wright-Patterson AFB, OH 45433, USAAir Force Institute of Technology, 2950 Hobson Way, Wright-Patterson AFB, OH 45433, USAAir Force Institute of Technology, 2950 Hobson Way, Wright-Patterson AFB, OH 45433, USAAlthough not common today, communications networks could adjust security postures based on changing mission security requirements, environmental conditions, or adversarial capability, through the coordinated use of multiple channels. This will require the ability to measure the security of communications networks in a meaningful way. To address this need, in this paper, we introduce the Quality of Secure Service (QoSS) model, a methodology to evaluate how well a system meets its security requirements. This construct enables a repeatable and quantifiable measure of security in a single- or multi-channel network under static configurations. In this approach, the quantification of security is based upon the probabilities that adversarial listeners and disruptors may gain access to or manipulate transmitted data. The initial model development, albeit a snap-shot of the network security, provides insights into what may affect end-to-end security and to what degree. The model was compared against the performance and expected security of several point-to-point networks, and three simplified architectures are presented as examples. Message fragmentation and duplication across the available channels provides a security performance trade-space, with an accompanying comprehensive measurement of the QoSS. The results indicate that security may be improved with message fragmentation across multiple channels when compared to the number of adversarial listeners or disruptors. This, in turn, points to the need, in future work, to build a full simulation environment with specific protocols and networks to validate the initial modeled results.https://www.mdpi.com/2624-800X/1/2/16communication modelsecuritymetricsprobabilityconfidentialityintegrity |
| spellingShingle | Paul M. Simon Scott Graham Christopher Talbot Micah Hayden Model for Quantifying the Quality of Secure Service Journal of Cybersecurity and Privacy communication model security metrics probability confidentiality integrity |
| title | Model for Quantifying the Quality of Secure Service |
| title_full | Model for Quantifying the Quality of Secure Service |
| title_fullStr | Model for Quantifying the Quality of Secure Service |
| title_full_unstemmed | Model for Quantifying the Quality of Secure Service |
| title_short | Model for Quantifying the Quality of Secure Service |
| title_sort | model for quantifying the quality of secure service |
| topic | communication model security metrics probability confidentiality integrity |
| url | https://www.mdpi.com/2624-800X/1/2/16 |
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