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FAIR-Based Cyber Influence Damage Assessment for Exploit in Mobile Device

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Mobile Internet Security (MobiSec 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 971))

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Abstract

Recently, as the utilization rate for mobile devices has increased, cyber attacks targeting them have been increasing. Cyber attacks such as ransomware in general network space have started to spread to mobile devices. In addition, malware that exploits mobile vulnerabilities is also increasing rapidly. Threats to these mobile devices could cause negative damage to human life. Thus, the cyber attack that causes secondary damage to the real world is called a Cyber Influence Attack. This paper presents an influence attack scenario in which the exploit of the Android OS acquires the permission of the mobile device for propagating false information. Based on this scenario, we analyze the damage assessment of mobile device exploit that can cause real social damage as well as damage to cyberspace assets through FAIR (Factor Analysis of Information Risk) model.

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References

  1. Clark, D.: Characterizing cyberspace: past, present and future. MIT CSAIL, Version 1, 2016–2028 (2010)

    Google Scholar 

  2. Daware, S., Dahake, S., Thakare, V.: Mobile forensics: overview of digital forensic, computer forensics vs. mobile forensics and tools. Int. J. Comput. Appl. 7–8 (2012)

    Google Scholar 

  3. Deacon, R.E., Firebaugh, F.M.: Family Resource Management: Principles and Applications. Allyn and Bacon, Boston (1981)

    Google Scholar 

  4. D’Orazio, C.J., Lu, R., Choo, K.K.R., Vasilakos, A.V.: A markov adversary model to detect vulnerable ios devices and vulnerabilities in IOS apps. Appl. Math. Comput. 293, 523–544 (2017)

    MathSciNet  Google Scholar 

  5. Economist, T.: The economist intelligence unit’s democracy index (2016). https://infographics.economist.com/2017/DemocracyIndex/

  6. Grimaila, M.R., Fortson, L.W.: Towards an information asset-based defensive cyber damage assessment process. In: 2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications, CISDA 2007, pp. 206–212. IEEE (2007)

    Google Scholar 

  7. Guido, D.: The exploit intelligence project. PowerPoint presentation, iSEC Partners (2011)

    Google Scholar 

  8. Guido, D., Arpaia, M.: The mobile exploit intelligence project. Blackhat EU (2012)

    Google Scholar 

  9. Hern, A.: Hacking team hacked: firm sold spying tools to repressive regimes, documents claim (2015). https://www.theguardian.com/technology/2015/jul/06/hacking-team-hacked-firm-sold-spying-tools-to-repressive-regimes-documents-claim

  10. Herr, T.: Prep: A framework for malware & cyber weapons. Browser Download This Paper (2013)

    Google Scholar 

  11. Horony, M.D.: Information system incidents: the development of a damage assessment model. Technical report, Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio (1999)

    Google Scholar 

  12. HUFFPOST: 2016 general election: Trump vs. clinton (2016). http://elections.huffingtonpost.com/pollster/2016-general-election-trump-vs-clinton

  13. IDC: Smartphone os market share (2017). https://www.idc.com/promo/smartphone-market-share/os

  14. Jajodia, S., Liu, P., Swarup, V., Wang, C.: Cyber Situational Awareness. Advances in Information Security, vol. 14. Springer, Boston (2010). https://doi.org/10.1007/978-1-4419-0140-8

    Book  MATH  Google Scholar 

  15. Jim Sciutto, N.G., Browne, R.: Us finds growing evidence Russia feeding emails to wikileaks (2016). http://edition.cnn.com/2016/10/13/politics/russia-us-election/index.html

  16. Jones, J.: An introduction to factor analysis of information risk (fair). Norwich J. Inf. Assur. 2(1), 67 (2006)

    MathSciNet  Google Scholar 

  17. Joshi, J., Parekh, C.: Android smartphone vulnerabilities: a survey. In: International Conference on Advances in Computing, Communication, & Automation (ICACCA)(Spring), pp. 1–5. IEEE (2016)

    Google Scholar 

  18. LaCapria, K.: As wikileaks released several batches of e-mails in october 2016, partisans claimed they confirmed hillary clinton sold weapons to ISIS (2016). http://www.snopes.com/wikileaks-cofirms-hillary-clinton-sold-weapons-to-isis/

  19. NIST: National vulnerability database (2014–2016). https://nvd.nist.gov/

  20. Cyberspace Operations: Joint publication 3–12 (r). Joint Chief of Staffs (2013)

    Google Scholar 

  21. Ostler, R.: Defensive cyber battle damage assessment through attack methodology modeling. Technical report, Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio (2011)

    Google Scholar 

  22. Pagliery, J.: Wikileaks claims to reveal how CIA hacks TVS and phones all over the world (2017). http://money.cnn.com/2017/03/07/technology/wikileaks-cia-hacking/index.html

  23. Philip, R., et al.: Enabling distributed security in cyberspace. Department of Homeland Security (2011)

    Google Scholar 

  24. RSA: 2016:current state of cybercrime (2016). https://www.rsa.com/content/dam/rsa/PDF/2016/05/2016-current-state-of-cybercrime.pdf

  25. Saenko, I., Lauta, O., Kotenko, I.: Analytical modeling of mobile banking attacks based on a stochastic network conversion technique (2016)

    Google Scholar 

  26. Shezan, F.H., Afroze, S.F., Iqbal, A.: Vulnerability detection in recent android apps: an empirical study. In: 2017 International Conference on Networking, Systems and Security (NSysS), pp. 55–63. IEEE (2017)

    Google Scholar 

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Acknowledgment

This work was supported by Defense Acquisition Program Administration and Agency for Defense Development under the contract (UD060048AD).

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Correspondence to Kyungho Lee .

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Park, M., Han, J., Seo, J., Oh, H., Lee, K. (2019). FAIR-Based Cyber Influence Damage Assessment for Exploit in Mobile Device. In: You, I., Chen, HC., Sharma, V., Kotenko, I. (eds) Mobile Internet Security. MobiSec 2017. Communications in Computer and Information Science, vol 971. Springer, Singapore. https://doi.org/10.1007/978-981-13-3732-1_4

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  • DOI: https://doi.org/10.1007/978-981-13-3732-1_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-3731-4

  • Online ISBN: 978-981-13-3732-1

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