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

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Advances in Visual Informatics (IVIC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11870))

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Abstract

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.

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Author information

Authors and Affiliations

  1. National Defence University of Malaysia, Kuala Lumpur, Malaysia

    Wan Nurhidayat Wan Muhamad, Noor Afiza Mat Razali, Nor Asiakin Hasbullah, Norulzahrah Mohd Zainudin, Suzaimah Ramli, Muslihah Wook & Nurjannatul Jannah Aqilah MSaad

  2. Institute of Visual Informatics, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

    Khairul Khalil Ishak

  3. Management and Science University, Shah Alam, Malaysia

    Zurida Ishak

Authors
  1. Wan Nurhidayat Wan Muhamad
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  2. Noor Afiza Mat Razali
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  3. Khairul Khalil Ishak
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  4. Nor Asiakin Hasbullah
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  5. Norulzahrah Mohd Zainudin
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  6. Suzaimah Ramli
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  7. Muslihah Wook
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  8. Zurida Ishak
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  9. Nurjannatul Jannah Aqilah MSaad
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Corresponding author

Correspondence to Noor Afiza Mat Razali .

Editor information

Editors and Affiliations

  1. Universiti Kebangsaan Malaysia, Bangi, Malaysia

    Halimah Badioze Zaman

  2. Dublin City University, Dublin, Ireland

    Alan F. Smeaton

  3. National Central University, Taoyuan City, Taiwan

    Timothy K. Shih

  4. Carlos III University of Madrid, Madrid, Spain

    Sergio Velastin

  5. Toyo University, Tokyo, Japan

    Tada Terutoshi

  6. Universiti Kebangsaan Malaysia, Bangi, Malaysia

    Nazlena Mohamad Ali

  7. Universiti Kebangsaan Malaysia, Bangi, Malaysia

    Mohammad Nazir Ahmad

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Wan Muhamad, W.N. et al. (2019). Enhance Multi-factor Authentication Model for Intelligence Community Access to Critical Surveillance Data. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2019. Lecture Notes in Computer Science(), vol 11870. Springer, Cham. https://doi.org/10.1007/978-3-030-34032-2_49

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  • DOI: https://doi.org/10.1007/978-3-030-34032-2_49

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34031-5

  • Online ISBN: 978-3-030-34032-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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