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On designing an unaided authentication service with threat detection and leakage control for defeating opportunistic adversaries

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Abstract

Unaided authentication services provide the flexibility to login without being dependent on any additional device. The power of recording attack resilient unaided authentication services (RARUAS) is undeniable as, in some aspects, they are even capable of offering better security than the biometric based authentication systems. However, high login complexity of these RARUAS makes them far from usable in practice. The adopted information leakage control strategies have often been identified as the primary cause behind such high login complexities. Though recent proposals have made some significant efforts in designing a usable RARUAS by reducing its login complexity, most of them have failed to achieve the desired usability standard. In this paper, we have introduced a new notion of controlling the information leakage rate. By maintaining a good security standard, the introduced idea helps to reduce the login complexity of our proposed mechanism — named as Textual-Graphical Password-based Mechanism or TGPM, by a significant extent. Along with resisting the recording attack, TGPM also achieves a remarkable property of threat detection. To the best of our knowledge, TGPM is the first RARUAS, which can both prevent and detect the activities of the opportunistic recording attackers who can record the complete login activity of a genuine user for a few login sessions. Our study reveals that TGPM assures much higher session resiliency compared to the existing authentication services, having the same or even higher login complexities. Moreover, TGPM stores the password information in a distributed way and thus restricts the adversaries to learn the complete secret from a single compromised server. A thorough theoretical analysis has been performed to prove the strength of our proposal from both the security and usability perspectives. We have also conducted an experimental study to support the theoretical argument made on the usability standard of TGPM.

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Authors and Affiliations

  1. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China

    Nilesh Chakraborty

  2. Department of Computer Science, Indian Institute of Technology Patna, Bihar, 801106, India

    Samrat Mondal

Authors
  1. Nilesh Chakraborty
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  2. Samrat Mondal
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Corresponding author

Correspondence to Nilesh Chakraborty.

Additional information

Nilesh Chakraborty received the Master degree and the PhD degree from National Institute of Technology (NIT) Durgapur, India in 2013 and Indian Institute of Technology (IIT) Patna, India in 2018, respectively. He is currently working as a Postdoctoral fellow in Shenzhen University, China. During his PhD, he successfully completed a security project funded by Science & Engineering Research Board (SERB), Government of India. His primary research topic includes authentication and usable security.

Samrat Mondal received the PhD degree from School of IIT Kharagpur, India in 2010. He is working as an assistant professor in the Department of Computer Science and Engineering, IIT Patna, India since 2010. He has also served as a Visiting Associate Professor at the University of Denver, USA for 11 months. His primary research interests include security & privacy, database & data mining and smart energy management related applications. Dr. Mondal has served as a reviewer of journals like IEEE TDSC, Computers & Security, etc. He has received research grants from the Science and Engineering Research Board (SERB), Government of India on multiple occasions. He is also a Senior Member of IEEE since 2019.

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On designing an unaided authentication service with threat detection and leakage control for defeating opportunistic adversaries

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Chakraborty, N., Mondal, S. On designing an unaided authentication service with threat detection and leakage control for defeating opportunistic adversaries. Front. Comput. Sci. 15, 152803 (2021). https://doi.org/10.1007/s11704-019-9134-9

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