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PRAN: A Provenance Based Model and Prototype to Strengthen Authentication

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Web, Artificial Intelligence and Network Applications (WAINA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 927))

Abstract

In this paper, we present the provenance based authentication (PRAN) model, and prototype that aims to strengthen password-based authentication of a system—ensuring legitimacy of a user’s identity by detecting anomalous user logins without the need for other obtrusive authentication factors. The PRAN model utilizes authentication provenance along with traditional methods. We evaluate the prototype with password stealing/sharing use cases. We observe that the PRAN prototype detects anomalous logins, and also legitimate logins thereby preventing applications from allowing anomalous user logins’.

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Notes

  1. 1.

    https://jena.apache.org/.

  2. 2.

    http://lucmoreau.github.io/ProvToolbox/.

  3. 3.

    https://github.com/wso2/balana.

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Author information

Authors and Affiliations

  1. Tata Consultancy Services, Hyderabad, India

    Rajidi Satish Chandra Reddy & Srinivas Reddy Gopu

Authors
  1. Rajidi Satish Chandra Reddy
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  2. Srinivas Reddy Gopu
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Corresponding author

Correspondence to Rajidi Satish Chandra Reddy .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Advanced Sciences, Hosei University, Koganei-Shi, Tokyo, Japan

    Makoto Takizawa

  3. Department of Computer Science, Technical University of Catalonia, Barcelona, Barcelona, Spain

    Fatos Xhafa

  4. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

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Reddy, R.S.C., Gopu, S.R. (2019). PRAN: A Provenance Based Model and Prototype to Strengthen Authentication. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2019. Advances in Intelligent Systems and Computing, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-15035-8_13

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