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2022 | OriginalPaper | Buchkapitel

Classification and Analysis of Vulnerabilities in Mobile Device Infrastructure Interfaces

verfasst von : Konstantin Izrailov, Dmitry Levshun, Igor Kotenko, Andrey Chechulin

Erschienen in: Mobile Internet Security

Verlag: Springer Nature Singapore

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Abstract

A consequence of the widespread use of mobile devices is the emergence of a threat to information security. One of the reasons for this lies in the vulnerabilities of device interaction interfaces. This area is quite new, so it is not well investigated. The aim of this investigation is to classify and analyze vulnerabilities of infrastructure interfaces. As a part of the results the general classification model is proposed in an analytical form. This model allows one to map vulnerabilities to the interface classes. Interfaces are separated based on infrastructure components they provide interaction between. Additionally, the interactions themselves are separated into subclasses. The categorical division apparatus is used for classification with 64 classes. The relationship between the infrastructure of mobile devices and the vulnerabilities of its interfaces is analysed. An experiment was carried out for a typical scenario of finding the owner of devices in the infrastructure of mobile devices. The experiment showed the efficiency of the proposed model and made it possible to make a number of predictions regarding potential vulnerabilities in the future.

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Literatur
1.
Zurück zum Zitat Abhishta, A., van Heeswijk, W., Junger, M., Nieuwenhuis, L.J., Joosten, R.: Why would we get attacked? an analysis of attacker’s aims behind DDos attacks. J. Wirel. Mob. Netw. Ubiquit. Comput. Dependable Appl. 11(2), 3–22 (2020) Abhishta, A., van Heeswijk, W., Junger, M., Nieuwenhuis, L.J., Joosten, R.: Why would we get attacked? an analysis of attacker’s aims behind DDos attacks. J. Wirel. Mob. Netw. Ubiquit. Comput. Dependable Appl. 11(2), 3–22 (2020)
2.
Zurück zum Zitat Almaiah, M.A., Al-Zahrani, A., Almomani, O., Alhwaitat, A.K.: Classification of cyber security threats on mobile devices and applications. In: Maleh, Y., Baddi, Y., Alazab, M., Tawalbeh, L., Romdhani, I. (eds.) Artificial Intelligence and Blockchain for Future Cybersecurity Applications. SBD, vol. 90, pp. 107–123. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-74575-2_6CrossRef Almaiah, M.A., Al-Zahrani, A., Almomani, O., Alhwaitat, A.K.: Classification of cyber security threats on mobile devices and applications. In: Maleh, Y., Baddi, Y., Alazab, M., Tawalbeh, L., Romdhani, I. (eds.) Artificial Intelligence and Blockchain for Future Cybersecurity Applications. SBD, vol. 90, pp. 107–123. Springer, Cham (2021). https://​doi.​org/​10.​1007/​978-3-030-74575-2_​6CrossRef
3.
Zurück zum Zitat Bryukhovetskiy, A., Miryanova, V., Moiseev, D.: Research of the model for detecting UMV interfaces vulnerabilities based on information criterion. In: CEUR Workshop Proceedings, pp. 162–168 (2021) Bryukhovetskiy, A., Miryanova, V., Moiseev, D.: Research of the model for detecting UMV interfaces vulnerabilities based on information criterion. In: CEUR Workshop Proceedings, pp. 162–168 (2021)
4.
Zurück zum Zitat Buinevich, M., Izrailov, K., Kotenko, I., Kurta, P.: Method and algorithms of visual audit of program interaction. J. Internet Serv. Inf. Secur. 11(1), 16–43 (2021) Buinevich, M., Izrailov, K., Kotenko, I., Kurta, P.: Method and algorithms of visual audit of program interaction. J. Internet Serv. Inf. Secur. 11(1), 16–43 (2021)
5.
Zurück zum Zitat Chen, H., Zhang, D., Chen, J., Lin, W., Shi, D., Zhao, Z.: An automatic vulnerability classification system for IoT softwares. In: 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pp. 1525–1529. IEEE (2020) Chen, H., Zhang, D., Chen, J., Lin, W., Shi, D., Zhao, Z.: An automatic vulnerability classification system for IoT softwares. In: 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pp. 1525–1529. IEEE (2020)
6.
Zurück zum Zitat Choi, I., Rhiu, I., Lee, Y., Yun, M.H., Nam, C.S.: A systematic review of hybrid brain-computer interfaces: taxonomy and usability perspectives. PLoS ONE 12(4), e0176674 (2017)CrossRef Choi, I., Rhiu, I., Lee, Y., Yun, M.H., Nam, C.S.: A systematic review of hybrid brain-computer interfaces: taxonomy and usability perspectives. PLoS ONE 12(4), e0176674 (2017)CrossRef
8.
Zurück zum Zitat Dey, D., et al.: Taming the eHMI jungle: a classification taxonomy to guide, compare, and assess the design principles of automated vehicles’ external human-machine interfaces. Transp. Res. Interdisc. Perspect. 7, 100174 (2020) Dey, D., et al.: Taming the eHMI jungle: a classification taxonomy to guide, compare, and assess the design principles of automated vehicles’ external human-machine interfaces. Transp. Res. Interdisc. Perspect. 7, 100174 (2020)
9.
Zurück zum Zitat Du, X., Yin, L., Wu, P., Jia, L., Dong, W.: Vulnerability analysis through interface-based checker design. In: 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C), pp. 46–52. IEEE (2020) Du, X., Yin, L., Wu, P., Jia, L., Dong, W.: Vulnerability analysis through interface-based checker design. In: 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C), pp. 46–52. IEEE (2020)
10.
Zurück zum Zitat Huang, G., Li, Y., Wang, Q., Ren, J., Cheng, Y., Zhao, X.: Automatic classification method for software vulnerability based on deep neural network. IEEE Access 7, 28291–28298 (2019)CrossRef Huang, G., Li, Y., Wang, Q., Ren, J., Cheng, Y., Zhao, X.: Automatic classification method for software vulnerability based on deep neural network. IEEE Access 7, 28291–28298 (2019)CrossRef
11.
Zurück zum Zitat Izrailov, K., Chechulin, A., Vitkova, L.: Threats classification method for the transport infrastructure of a smart city. In: 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT), pp. 1–6. IEEE (2020) Izrailov, K., Chechulin, A., Vitkova, L.: Threats classification method for the transport infrastructure of a smart city. In: 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT), pp. 1–6. IEEE (2020)
12.
Zurück zum Zitat Kim, H.: 5G core network security issues and attack classification from network protocol perspective. J. Internet Serv. Inf. Secur. 10(2), 1–15 (2020) Kim, H.: 5G core network security issues and attack classification from network protocol perspective. J. Internet Serv. Inf. Secur. 10(2), 1–15 (2020)
13.
Zurück zum Zitat Kitana, A., Traore, I., Woungang, I.: Towards an epidemic SMS-based cellular botnet. J. Internet Serv. Inf. Secur. 10(4), 38–58 (2020) Kitana, A., Traore, I., Woungang, I.: Towards an epidemic SMS-based cellular botnet. J. Internet Serv. Inf. Secur. 10(4), 38–58 (2020)
14.
Zurück zum Zitat Last, D.: Using historical software vulnerability data to forecast future vulnerabilities. In: 2015 Resilience Week (RWS), pp. 1–7. IEEE (2015) Last, D.: Using historical software vulnerability data to forecast future vulnerabilities. In: 2015 Resilience Week (RWS), pp. 1–7. IEEE (2015)
15.
Zurück zum Zitat Levshun, D., Gaifulina, D., Chechulin, A., Kotenko, I.: Problematic issues of information security of cyber-physical systems. Inform. Autom. 19(5), 1050–1088 (2020) Levshun, D., Gaifulina, D., Chechulin, A., Kotenko, I.: Problematic issues of information security of cyber-physical systems. Inform. Autom. 19(5), 1050–1088 (2020)
16.
Zurück zum Zitat McGrew, R.W.: Vulnerability analysis case studies of control systems human machine interfaces. Ph.D. thesis, Mississippi State University (2013) McGrew, R.W.: Vulnerability analysis case studies of control systems human machine interfaces. Ph.D. thesis, Mississippi State University (2013)
17.
Zurück zum Zitat Moiseev, D., Bryukhovetskiy, A.: Method for detecting vulnerabilities of unmanned vehicle interfaces based on continuous values discretization, pp. 43–47 (2021) Moiseev, D., Bryukhovetskiy, A.: Method for detecting vulnerabilities of unmanned vehicle interfaces based on continuous values discretization, pp. 43–47 (2021)
18.
Zurück zum Zitat Mulliner, C., Robertson, W., Kirda, E.: Hidden gems: automated discovery of access control vulnerabilities in graphical user interfaces. In: 2014 IEEE Symposium on Security and Privacy, pp. 149–162. IEEE (2014) Mulliner, C., Robertson, W., Kirda, E.: Hidden gems: automated discovery of access control vulnerabilities in graphical user interfaces. In: 2014 IEEE Symposium on Security and Privacy, pp. 149–162. IEEE (2014)
19.
Zurück zum Zitat Nowaczewski, S., Mazurczyk, W.: Securing future internet and 5G using customer edge switching using DNSCrypt and DNSSEC. J. Wirel. Mob. Netw. Ubiquit. Comput. Dependable Appl. 11(3), 87–106 (2020) Nowaczewski, S., Mazurczyk, W.: Securing future internet and 5G using customer edge switching using DNSCrypt and DNSSEC. J. Wirel. Mob. Netw. Ubiquit. Comput. Dependable Appl. 11(3), 87–106 (2020)
20.
Zurück zum Zitat Papp, D., Ma, Z., Buttyan, L.: Embedded systems security: threats, vulnerabilities, and attack taxonomy. In: 2015 13th Annual Conference on Privacy, Security and Trust (PST), pp. 145–152. IEEE (2015) Papp, D., Ma, Z., Buttyan, L.: Embedded systems security: threats, vulnerabilities, and attack taxonomy. In: 2015 13th Annual Conference on Privacy, Security and Trust (PST), pp. 145–152. IEEE (2015)
21.
Zurück zum Zitat Qasem, A., Shirani, P., Debbabi, M., Wang, L., Lebel, B., Agba, B.L.: Automatic vulnerability detection in embedded devices and firmware: survey and layered taxonomies. ACM Comput. Surv. (CSUR) 54(2), 1–42 (2021)CrossRef Qasem, A., Shirani, P., Debbabi, M., Wang, L., Lebel, B., Agba, B.L.: Automatic vulnerability detection in embedded devices and firmware: survey and layered taxonomies. ACM Comput. Surv. (CSUR) 54(2), 1–42 (2021)CrossRef
22.
Zurück zum Zitat Sabetta, A., Bezzi, M.: A practical approach to the automatic classification of security-relevant commits. In: 2018 IEEE International Conference on Software Maintenance and Evolution (ICSME), pp. 579–582. IEEE (2018) Sabetta, A., Bezzi, M.: A practical approach to the automatic classification of security-relevant commits. In: 2018 IEEE International Conference on Software Maintenance and Evolution (ICSME), pp. 579–582. IEEE (2018)
23.
Zurück zum Zitat Siewruk, G., Mazurczyk, W.: Context-aware software vulnerability classification using machine learning. IEEE Access 9, 88852–88867 (2021)CrossRef Siewruk, G., Mazurczyk, W.: Context-aware software vulnerability classification using machine learning. IEEE Access 9, 88852–88867 (2021)CrossRef
24.
Zurück zum Zitat Skatkov, A., Bryukhovetskiy, A., Moiseev, D.: Adaptive fuzzy model for detecting of vulnerabilities of unmanned vehicles interfaces based on evaluation of the information state of resources. In: IOP Conference Series: Materials Science and Engineering, vol. 862, p. 052029. IOP Publishing (2020) Skatkov, A., Bryukhovetskiy, A., Moiseev, D.: Adaptive fuzzy model for detecting of vulnerabilities of unmanned vehicles interfaces based on evaluation of the information state of resources. In: IOP Conference Series: Materials Science and Engineering, vol. 862, p. 052029. IOP Publishing (2020)
25.
Zurück zum Zitat Spreitzer, R., Moonsamy, V., Korak, T., Mangard, S.: Systematic classification of side-channel attacks: a case study for mobile devices. IEEE Commun. Surv. Tutor. 20(1), 465–488 (2017)CrossRef Spreitzer, R., Moonsamy, V., Korak, T., Mangard, S.: Systematic classification of side-channel attacks: a case study for mobile devices. IEEE Commun. Surv. Tutor. 20(1), 465–488 (2017)CrossRef
26.
Zurück zum Zitat Wong, S.K., Yiu, S.M.: Identification of device motion status via Bluetooth discovery. J. Internet Serv. Inf. Secur. 10(4), 59–69 (2020) Wong, S.K., Yiu, S.M.: Identification of device motion status via Bluetooth discovery. J. Internet Serv. Inf. Secur. 10(4), 59–69 (2020)
27.
Zurück zum Zitat Wong, S.K., Yiu, S.M.: Location spoofing attack detection with pre-installed sensors in mobile devices. J. Wirel. Mob. Netw. Ubiquit. Comput. Dependable Appl. 11(4), 16–30 (2020) Wong, S.K., Yiu, S.M.: Location spoofing attack detection with pre-installed sensors in mobile devices. J. Wirel. Mob. Netw. Ubiquit. Comput. Dependable Appl. 11(4), 16–30 (2020)
28.
Metadaten
Titel
Classification and Analysis of Vulnerabilities in Mobile Device Infrastructure Interfaces
verfasst von
Konstantin Izrailov
Dmitry Levshun
Igor Kotenko
Andrey Chechulin
Copyright-Jahr
2022
Verlag
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-16-9576-6_21

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