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Identification of Bugs and Vulnerabilities in TLS Implementation for Windows Operating System Using State Machine Learning

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Security in Computing and Communications (SSCC 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 969))

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Abstract

TLS protocol is an essential part of secure Internet communication. In the past, many attacks have been identified on the protocol. Most of these attacks are not due to design flaws of the protocol, but due to flaws in specific implementation of protocol. One of the widely used implementation of TLS is SChannel which is used in Windows operating system since its inception. In this paper, we have used “protocol state fuzzing” to identify vulnerable and undesired state transitions in the state machine models of the protocol for various versions of SChannel. The technique of protocol state fuzzing has been implemented using query based state machine learning. The client as well as server components have been analyzed thoroughly using this technique and various flaws have been discovered in the implementation. Exploitation of these flaws under specific circumstances may lead to serious attacks which have potential to disrupt secure communication.

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Author information

Authors and Affiliations

  1. Defence Research and Development Organisation, Delhi, India

    Tarun Yadav & Koustav Sadhukhan

Authors
  1. Tarun Yadav
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  2. Koustav Sadhukhan
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Corresponding author

Correspondence to Tarun Yadav .

Editor information

Editors and Affiliations

  1. Technology and Management, Indian Institute of Information, Kerala, India

    Sabu M. Thampi

  2. Department of Computer Science, Missouri University of Science and Technology, Rolla, MO, USA

    Sanjay Madria

  3. Guangzhou University, Guangzhou, China

    Guojun Wang

  4. Howard University, Washington, DC, USA

    Danda B. Rawat

  5. University of the West of Scotland, Paisley, Glasgow, UK

    Jose M. Alcaraz Calero

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© 2019 Springer Nature Singapore Pte Ltd.

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Yadav, T., Sadhukhan, K. (2019). Identification of Bugs and Vulnerabilities in TLS Implementation for Windows Operating System Using State Machine Learning. In: Thampi, S., Madria, S., Wang, G., Rawat, D., Alcaraz Calero, J. (eds) Security in Computing and Communications. SSCC 2018. Communications in Computer and Information Science, vol 969. Springer, Singapore. https://doi.org/10.1007/978-981-13-5826-5_27

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  • DOI: https://doi.org/10.1007/978-981-13-5826-5_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-5825-8

  • Online ISBN: 978-981-13-5826-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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