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On security of wireless sensor networks: a data authentication protocol using digital signature

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Abstract

Guaranteeing end-to-end data security in wireless sensor networks (WSNs) is important and has drawn much attention of researchers over past years. Because an attacker may take control of compromised sensor nodes to inject bogus reports into WSNs, enhancing data authenticity becomes a necessary issue in WSNs. Unlike PCREF (Yang et al. in IEEE Trans Comput 64(1):4–18, 2015) (LEDS, Ren et al. in IEEE Trans Mobile Comput 7(5):585–598, 2008), digital signature rather than message authentication polynomials (message authentication codes) is adopted by our protocol in en-route filtering. Keeping the advantages of clusters in PCREF and overcoming the drawbacks in LEDS, an enhanced and efficient cluster-based security protocol is proposed in this paper. The proposed protocol can guarantee end-to-end data authentication with the aid of digital signature and exhibits its effectiveness and efficiency through security analysis and performance analysis. Our analytical results show that the proposed protocol significantly outperforms the closely related protocols in the literature in term of security strength and protocol overhead.

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Notes

  1. Let us briefly explain as follows. In LEDS, a (t, T) threshold linear secret sharing scheme (LSSS) is employed. Therefore, multiple sensor nodes may detect the event of interest simultaneously and are asked to generate shares based on the encrypted report. These shares generated from these non-compromised sensor nodes are then called legitimate secret shares. For details, one can refer to [31].

  2. Undoubtedly, an Imote2 was a widely employed wireless sensor node. To save power consumption, one can design low-power wireless sensor nodes for this purpose, e.g., Mica2 [25]. Therefore, an Imote2 serves as a cluster head and a Mica2 serves as a low-power sensor node in the section of performance analysis.

  3. As for how to establish a pairwise key pool, one can refer to the literature for details, e.g., [3, 7] etc.

  4. This is a feasible approach because it comes from the concept of a distributed hash table (DHT) in a peer-to-peer (P2P) network.

  5. As stated in Sect. 4.1, the size of a cell (an event cell) is covered by a circle with the radius of sensing range \(r_s\). Therefore, an event in the event cell falls within the sensing range of the sensor nodes in the event cell. This implies that the difference between two time instants to sense that event by two sensor nodes should be negligible even if it exists. To achieve the same event time calculated by the sensor nodes in the same event cell sensing the event for sure, such a rounded value is then used by sensor nodes to stand for the “true” event time. Undoubtedly, time synchronization is an important issue in the wireless sensor network but it does not fall within the scope of this paper. However, our solution does not rely on perfect time synchronization because a post-processed event time rather than an exact event time is utilized.

  6. Such overhearing happens in an individual event cell only. Therefore, the range of overhearing is limited to the range of an event cell. This will not become difficult for such a communication range even if the real-world development with different geographical areas or buildings is considered.

  7. Of course, a tradeoff between energy consumption in overhearing and security enhancement is inevitable. To alleviate possible energy consumption incurred, the number of non-participating sensor nodes to overhear can be properly controlled. For example, a random approach my be utilized to allow each non-participating sensor node to overhear and participate later or not by specifying a suitable probability \(p_o\). Such a random approach can then reduce the number of non-participating sensor nodes to overhear by a factor of \(1-p_o\) on average.

Abbreviations

WSN:

Wireless sensor network

LEDS:

Location-aware end-to-end data security

BS:

Base station

DoS:

Denial of service

MAC:

Message authentication code

PCREF:

Polynomial-based compromise-resilient en-route filtering

MAP:

Message authentication polynomial

MKMP:

Multi-BS key management protocol

DSEDA:

Digital signature assisted end-to-end data authentication

LSSS:

Linear secret sharing scheme

SEF:

Statistical en-route filtering

IHA:

Interleaved hop-by-hop authentication

LBRS:

Location-based resilient secrecy

CFFS:

Cluster-based false data filtering scheme

ECC:

Elliptic curve cryptography

ID:

Identity

OOS:

Online/offline signature

ECDSA:

Elliptic curve digital signature algorithm

LEAP:

Localized encryption and authentication protocol

LNCS:

Location-aware network-coding security

GPS:

Global positioning system

CH:

Cluster head

PK:

Public key

SK:

Secret key

DHT:

Distributed hash table

P2P:

Peer-to-peer

SHA:

Secure hash algorithm

HMAC:

Keyed-hashing for message authentication

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Acknowledgments

The work of H. W. Ferng was supported by the Ministry of Science and Technology (MOST), Taiwan under contracts MOST 104-2221-E-011-052-MY2, MOST 103-2221-E-011-012, and MOST 102-2221-E-011-004.

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  1. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, 106, Taiwan

    Huei-Wen Ferng & Nguyen Minh Khoa

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Correspondence to Huei-Wen Ferng.

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Ferng, HW., Khoa, N.M. On security of wireless sensor networks: a data authentication protocol using digital signature. Wireless Netw 23, 1113–1131 (2017). https://doi.org/10.1007/s11276-016-1208-0

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