Enhance Multi-factor Authentication Model for Intelligence Community Access to Critical Surveillance Data

  • Wan Nurhidayat Wan Muhamad
  • Noor Afiza Mat RazaliEmail author
  • Khairul Khalil Ishak
  • Nor Asiakin Hasbullah
  • Norulzahrah Mohd Zainudin
  • Suzaimah Ramli
  • Muslihah Wook
  • Zurida Ishak
  • Nurjannatul Jannah Aqilah MSaad
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11870)


Protection of critical data is one of the greatest challenges in any organization around the globe, especially for the intelligence community. Managing data, assets and resources require strong security method such as the authentication process that can guarantee only designated person will be receiving the required information. Any breach of information and assets could risk in the nation’s sovereignty and give significant impacts in social, political, economy and diplomacy or even lives. Authentication method enables intelligence data to be transferred covertly and the access to the system by a legitimate user is guaranteed, hence the elements of confidentiality, integrity, and availability of the data is assured. This study analyzed various authentication methods used to secure multiple platforms of data and system. This study serves as theoretical analysis on multi-factor authentication model for intelligence community access to critical surveillance data. This study aims to propose the enhance model that could be used as a basis to build a framework of the secured authentication system to avoid common attack on authentication and access management.


Multi-factor authentication Intelligence community Identity verification Biometric 


  1. 1.
    Pomerleau, M.: How technology has changed intelligence collection – Defense Systems (2015) Accessed 20 June 2019
  2. 2.
    Van Puyvelde, D., Coulthart, S., Hossain, M.S.: Beyond the buzzword: big data and national security decision-making. Int. Aff. 93(6), 1397–1416 (2017)CrossRefGoogle Scholar
  3. 3.
    Odom, W.E.: Intelligence analysis. Intell. Natl. Secur. 23(3), 316–332 (2008)CrossRefGoogle Scholar
  4. 4.
    Gandhi, P., Sharma, A., Mahoney, A., Sousan, W., Zhu, W., Laplante, P.: Dimensions of cyber-attacks: cultural, social, economic, and political. Technol. Soc. Mag. IEEE 30, 28–38 (2011)CrossRefGoogle Scholar
  5. 5.
  6. 6.
    Raza, M., Iqbal, M., Sharif, M., Haider, W.: A survey of password attacks and comparative analysis on methods for secure authentication. World Appl. Sci. J. 19(4), 439–444 (2012)Google Scholar
  7. 7.
    Arjun, G.S., Rashmi, P.D., Arjun, G.S., Rashmi, P.D.: One Time Keyboard (OTK) Authentication. Int. J. Innov. Res. Sci. Technol. 4(1) 173–177 (2017)Google Scholar
  8. 8.
    Ong, L.: Awareness of information security risks : an investigation of people aspects (a study in Malaysia), pp. 1–256 (2015)Google Scholar
  9. 9.
    Hastings, N., Dempsey, K., Paulsen, C.: Considerations for identity management in public safety mobile networks. US Department of Commerce, National Institute of Standards and Technology (2015)Google Scholar
  10. 10.
    Sharma, D.H., Dhote, C.A., Potey, M.M.: Identity and access management as security-as-a-service from clouds. Proc. Comput. Sci. 79, 170–174 (2016)CrossRefGoogle Scholar
  11. 11.
    Ferrag, M.A., Maglaras, L., Derhab, A.: Authentication and authorization for mobile IoT devices using bio-features: recent advances and future trends 2019 (2019)Google Scholar
  12. 12.
    Opris, V.N.: Biometric multi-factor authentication scheme in cloud computing. Sci. Bull. Nav. Acad. 19(1), 472–475 (2016)Google Scholar
  13. 13.
    Nwabueze, E.E., Obioha, I., Onuoha, O.: Enhancing multi-factor authentication in modern computing. Commun. Netw. 06(03), 172–178 (2017)CrossRefGoogle Scholar
  14. 14.
    J. Task Force Transformation Initiative, “NIST Special Publication 800-53 Security and Privacy Controls for Federal Information Systems and OrganizationsGoogle Scholar
  15. 15.
    Libicki, M.C., Jackson, B.A., Rudavsky, R., Webb, K.W.: Influences on the adoption of multifactor authentication. J. Natl. Cancer Inst. 92(23), 1872(2000)Google Scholar
  16. 16.
    Lal, N.A., Prasad, S., Farik, M.: A review of authentication methods. Int. J. Sci. Technol. Res. 5(11), 246–249 (2016)Google Scholar
  17. 17.
    Waters, T.: Multifactor authentication – a new chain of custody option for military logistics. Cyber Def. Rev. 2(3), 1–14 (2017)Google Scholar
  18. 18.
    Lee, J.: Defense department developing multifactor authentication system—Biometric Update (2017). Accessed 20 June 2019
  19. 19.
    Jasiul, B., Sliwa, J., Piotrowski, R., Goniacz, R., Amanowicz, M.: Authentication and Authorization of Users and Services in Federated SOA Environments-Challenges and OpportunitiesGoogle Scholar
  20. 20.
    Shila, D.M., Srivastava, K., O’Neill, P., Reddy, K., Sritapan, V.: A multi-faceted approach to user authentication for mobile devices—using human movement, usage, and location patterns. In: 2016 IEEE Symposium on Technologies for Homeland Security (HST), pp. 1–6 (2016)Google Scholar
  21. 21.
    Soimart, L., Mookdarsanit, P.: Multi-factor authentication protocol for information accessibility in flash drive. In: 9th Applied Computer Technology Information System (2016)Google Scholar
  22. 22.
    Singh, S.: Multi-factor authentication and their approaches. Int. Res. J. Manag. IT Soc. Sci. 4(3), 68–81 (2017)Google Scholar
  23. 23.
    Mihailescu, D.M.I., Racuciu, C., Grecu, D.L., Nita, L.S.: A multi-factor authentication scheme including biometric characteristics as one factor. Mircea cel Batran Nav. Acad. Sci. Bull. 17(1), 348–352 (2015)Google Scholar
  24. 24.
    Podilchuk, C., Barinov, W., Hulbert, W., Jairaj, A.: Face recognition in a tactical environment. In: 2010-MILCOM 2010 Military Communications Conference, pp. 900–905 (2010)Google Scholar
  25. 25.
    Venukumar, V., Pathari, V.: Multi-factor authentication using threshold cryptography. In: 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1694–1698 (2016)Google Scholar
  26. 26.
    Souza, D.F.L., Burlamaqui, A.M.F., Souza Filho, G.L.: A multi factor authentication approach based on biometrics, optical interference and chaotic maps. IEEE Lat. Am. Trans. 15(9), 1700–1708 (2017)Google Scholar
  27. 27.
    Kim, S.-P., Kang, J.-H., Jo, Y.C., Oakley, I.: Development of a multi-modal personal authentication interface. In: 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), pp. 712–715 (2017)Google Scholar
  28. 28.
    Taher, K.A., Nahar, T., Hossain, S.A.: Enhanced cryptocurrency security by time-based token multi-factor authentication algorithm. In: 2019 International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), pp. 308–312 (2019)Google Scholar
  29. 29.
    Oke, B.A., Olaniyi, O.M., Aboaba, A.A., Arulogun, O.T.: Developing multifactor authentication technique for secure electronic voting system. In: 2017 International Conference on Computing Networking and Informatics (ICCNI), pp. 1–6 (2017)Google Scholar
  30. 30.
    Liu, Y., Zhong, Q., Chang, L., Xia, Z., He, D., Cheng, C.: A secure data backup scheme using multi-factor authentication. IET Inf. Secur. 11(5), 250–255 (2016)Google Scholar
  31. 31.
    Theofanos, M., Garfinkel, S., Choong, Y.-Y.: Secure and usable enterprise authentication: lessons from the field. IEEE Secur. Priv. 14(5), 14–21 (2016)CrossRefGoogle Scholar
  32. 32.
    Banyal, R.K., Jain, P., Jain, V.K.: Multi-factor authentication framework for cloud computing. In: 2013 Fifth International Conference on Computational Intelligence, Modelling and Simulation, pp. 105–110 (2013)Google Scholar
  33. 33.
    Khan, S.H., Akbar, M.A., Shahzad, F., Farooq, M., Khan, Z.: Secure biometric template generation for multi-factor authentication. Pattern Recogn. 48(2), 458–472 (2015)CrossRefGoogle Scholar
  34. 34.
    Jiang, Q., Chen, Z., Li, B., Shen, J., Yang, L., Ma, J.: Security analysis and improvement of bio-hashing based three-factor authentication scheme for telecare medical information systems. J. Ambient Intell. Humaniz. Comput. 9(4), 1061–1073 (2018)CrossRefGoogle Scholar
  35. 35.
    Ray, P.P., Mukherjee, M., Shu, L.: Internet of Things for disaster management: state-of-the-art and prospects. IEEE Access 5(i), 18818–18835 (2017)CrossRefGoogle Scholar
  36. 36.
    Intelligence Community Information Environment (IC IE) Data Strategy 2017-2021 (2017).
  37. 37.
    Ben-Zahia, M.A., Jaluta, I.: Criteria for selecting software development models. In: GSCIT 2014 - Global Summit on Computer and Information Technology, pp. 1–6 (2014)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Wan Nurhidayat Wan Muhamad
    • 1
  • Noor Afiza Mat Razali
    • 1
    Email author
  • Khairul Khalil Ishak
    • 2
  • Nor Asiakin Hasbullah
    • 1
  • Norulzahrah Mohd Zainudin
    • 1
  • Suzaimah Ramli
    • 1
  • Muslihah Wook
    • 1
  • Zurida Ishak
    • 3
  • Nurjannatul Jannah Aqilah MSaad
    • 1
  1. 1.National Defence University of MalaysiaKuala LumpurMalaysia
  2. 2.Institute of Visual InformaticsUniversiti Kebangsaan MalaysiaBangiMalaysia
  3. 3.Management and Science UniversityShah AlamMalaysia

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