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Secure IoT Using Weighted Signed Graphs

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Book cover Security and Privacy in Communication Networks (SecureComm 2016)

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Abstract

Key management has always remained a challenging problem for the entire security community. Standard practice in modern times is to agree on symmetric keys using public key protocols. However, public key protocols use heavy computations; rendering them inappropriate for application to low cost devices of Internet of Things (IoT). This led to proposals of various key management strategies for low cost networks; a prominent discovery being key predistribution technique for Wireless Sensor Network (WSN)–a prototype of IoT. Such schemes require several communicating nodes to share the same cryptographic key. This leads to interesting (combinatorial) graphical models and related optimality problems, that get intense for hierarchical architecture. Most protocols meant for hierarchical (low cost) networks employ separate designs for individual levels and/or clusters. Consequently only local optimal values can be computed. We develop a single universal platform using weighted signed graph (WSG) that designs the entire network for a hierarchical setup. This model can be used as itself or clubbed with a key predistribution scheme (KPS) to enhance the latter’s security when applied to a WSN. After generic presentation, we combine our universal model with prominent KPS to facilitate comparative study with existing protocols.

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Notes

  1. 1.

    Use of double encryption requires careful implementation. For instance, double encryption with two smartly chosen AES − 128 keys may enhance the security level by 1.5 times. That is, from 120 − BIT security to approximately 180 − BIT against any present day adversary.

  2. 2.

    This can be best analyzed by employing a particular KPS as a candidate for our global graph.

  3. 3.

    Usually node ids are positive number (like KPS applications). Therefore 0 or negative numbers are not used for global links. So we make extensive use of 0 and − ve sign for our local graph.

  4. 4.

    We have to rely on standard intrusion prevention system and/or traitor protocols like [15, 20] for updated information about compromised nodes to facilitate their deletion.

  5. 5.

    These processes will be detailed in extended version of this work.

  6. 6.

    Represent global links as (lower node no.)(k i )(higher node no.) for 1 ≤ i ≤ ν; k 1 , k 2 , k 3, · · · k ν are all the keys of selected KPS. This automatically captures the (regular) degree (r KPS  = r g ) of concerned KPS. Refer to [18, Sect. 2] for this definition of r KPS , where it is denoted as r.

  7. 7.

    Of course the use of local keys here requires proper cluster formation to ensure desired inter- cluster connectivity. One plausible way to obtain the desired cluster formation is to deploy the nodes and their Cluster Heads in a locally (uniform) random or group-wise random fashion. This assures proper cluster formation in most cases. In a rare event of ‘misplaced node’, we propose implementation of Key Rescheduling Protocol, described in Algorithm 1.

  8. 8.

    In the event of (same set of) multiple keys shared between a pair of nodes, a standard method [11] is to concatenate all of these keys and use hash of this concatenated key.

  9. 9.

    These communications make use of (fixed) publicly available addresses (like MAC or I.P. or email ids) of users (here nodes). Observe that these primary addresses are independent of the created secondary node ids [24, 26, 27] used during (global) key establishment.

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Authors and Affiliations

  1. Department of Computer Science and Automation, Indian Institute of Science, Bangalore, Karnataka, India

    Pinaki Sarkar

  2. School of Information Technology, Deakin University, Burwood Campus, Burwood, VIC, Australia

    Morshed Uddin Chowdhury

Authors
  1. Pinaki Sarkar
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  2. Morshed Uddin Chowdhury
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Correspondence to Pinaki Sarkar .

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Editors and Affiliations

  1. Singapore Management University, Singapore, Singapore

    Robert Deng

  2. Jinan University, Guangzhou, Guangdong, China

    Jian Weng

  3. University at Buffalo, Buffalo, New York, USA

    Kui Ren

  4. SRI International, Menlo Park, California, USA

    Vinod Yegneswaran

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Sarkar, P., Chowdhury, M.U. (2017). Secure IoT Using Weighted Signed Graphs. In: Deng, R., Weng, J., Ren, K., Yegneswaran, V. (eds) Security and Privacy in Communication Networks. SecureComm 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 198. Springer, Cham. https://doi.org/10.1007/978-3-319-59608-2_13

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  • DOI: https://doi.org/10.1007/978-3-319-59608-2_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59607-5

  • Online ISBN: 978-3-319-59608-2

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