Energy efficient geographical key management scheme for authentication in mobile wireless sensor networks

Thevar, Gnana Kousalya Chella; Rohini, G.

doi:10.1007/s11276-016-1228-9

Cited by 13 publications

(4 citation statements)

References 44 publications

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“…Because of the limited energy, computing power, storage capacity and mobility of WSN nodes the traditional broadcast authentication protocol cannot be applied directly, so it is urgent to design a corresponding broadcast authentication protocol according to the above characteristics. Currently, many energy-efficient broadcast protocols and algorithms have been proposed [16][17][18][19][20], and there are two main WSN broadcast authentication ways: one is signature authentication [15], but the disadvantage of this way is that it uses the public key cryptography which is expensive and hard to be applied in WSN; the other way is based on the message authentication code (MAC), such as one-way hash chain method and the µTESLA protocol proposed by Perrig according to the SPIN security model [5], in which the µTESLA protocol can realize asymmetric authentication based on the delay authentication, but the delay increases gradually with the time change.…”

Section: Identity Authenticationmentioning

confidence: 99%

A WSN Layer-Cluster Key Management Scheme Based on Quadratic Polynomial and Lagrange Interpolation Polynomial

Wang

Yang

Feng

et al. 2020

Sensors

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Since current key management schemes are mainly designed for static and planar networks, they are not very suitable for the layer-cluster wireless sensor networks (WSNs), a WSN layer-cluster key management scheme based on quadratic polynomial and Lagrange interpolation polynomial is proposed, in which the main idea of this scheme along the research line of broadcast identity authentication, session key, group key, network key and personal key. Specifically, authentication key can be established on the basis of Fourier series for identity authentication; session key is established by a multiple asymmetric quadratic polynomial, in which session key information is encrypted by the authentication key to ensure the security of intermediate interactive information; based on the former two keys, group key is established on the basis of Lagrange interpolation polynomial, in which the nodes of the cluster are not directly involved; the generation and management of network key is similar to the group key, in which the establishment idea is to regard the BS and all cluster heads as a group; the generation and management of personal key is also similar to the group key, the difference is that the personal key can be obtained by cluster nodes through getting the Lagrange interpolation polynomial coefficients based on their own random key information. It is analyzed that the proposed layer-cluster key management scheme can guarantee the identity of network nodes firstly through forward authentication and reverse authentication, and session key, group key and network key will guarantee the independence of the keys’ management and avoids the problem of single point failure compared with LEAP protocol, and personal key will guarantee the privacy of network.

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Section: Identity Authenticationmentioning

confidence: 99%

A WSN Layer-Cluster Key Management Scheme Based on Quadratic Polynomial and Lagrange Interpolation Polynomial

Wang

Yang

Feng

et al. 2020

Sensors

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“…In this way, the recovery process is completed by cascading, that is, backup B of A is moved to position of A and newly backup of B is moved to position of B (lines [34][35][36][37][38][39]. If backup node B is critical and its backup is other than its primary, then it notifies to its backup and moves to position of its primary by cascading (lines [40][41][42][43] [34][35][36][37][38][39]. If the backup is critical and its backup is other than its primary, then the recovery procedure takes time NK (lines [40][41][42][43].…”

Section: Proposed Algorithmmentioning

confidence: 99%

“…37 A cluster-based scheme is proposed to attain security by a private key management. 38 Routing protocol for mobile ad hoc network (MANET) is validated through testing methodology. 39 Wireless sensor and actuator networks are modeled using colored Petri nets.…”

Section: Related Workmentioning

confidence: 99%

Hybrid subnet-based node failure recovery formal procedure in wireless sensor and actor networks

Afzaal

Zafar

Alhumaidan

2017

International Journal of Distributed Sensor Networks

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An unattended deployment of wireless sensor and actor networks in a harsh and inhospitable environment may cause its failure by partitioning it into the disjoint segments. Although many variants of this problem are addressed using different approaches, it still needs to be investigated due to its various applications. In this article, an efficient, localized, hybrid failure detection and recovery algorithm is proposed which assumes planned deployment of nodes. The algorithm is approximate and distributed as its topology is partitioned into subnets localizing failure recovery procedure and efficient as the time complexity is reduced from nondeterministic polynomial-time-hard to polynomial time. The algorithm is hybrid as pre-failure planning and post-failure recovery is assumed for the critical nodes. Graph-based model is designed to represent static part which is then transformed into a formal model using Vienna Development Method-specification language. The static model consists of subnets, circular topology, sensors, actors, and gateways as composite objects in Vienna Development Method-specification language. The dynamic model is developed by defining its state space, functions, and possible operations to describe the failure recovery procedure. Invariants are defined on static model to assure correctness, and pre/post conditions are used in the dynamic model to control the behavior preventing system to enter into an unwanted situation. The formal specification is analyzed using Vienna Development Method-specification language Toolbox to visualize the model.

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“…These functions protect enterprise data from information loss or failure that arises from natural disasters, physical operating environment, etc. [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Security Analysis on Wireless Sensor Network in the Data Center for Energy Internet of Things

Xie¹,

Wang²,

Hua³

2020

IJSSE

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In the Energy Internet of Things (EIoT), the sensors in the wireless sensor network (WSN) at the data center (DC) are prone to attacks, and easy to suffer from problems in information security management (ISM), such as poor real-time performance and high complexity. This paper clarifies the structure of the DC WSN for the EIoT, models the WSN under the LEACH, and predicts the possible types of attacks. On this basis, a realtime and dynamic ISM plan was developed for the WSN. In this plan, the structure and operations of LEACH are optimized, and amount of data transmission was reduced through information fusion. Simulation experiment shows that the proposed plan safeguards the communication between adjacent nodes and between upper and lower layers, ensures the durability of network security through real-time update of keys, and promotes the efficiency of data transmission through information fusion.

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Energy efficient geographical key management scheme for authentication in mobile wireless sensor networks

Cited by 13 publications

References 44 publications

A WSN Layer-Cluster Key Management Scheme Based on Quadratic Polynomial and Lagrange Interpolation Polynomial

A WSN Layer-Cluster Key Management Scheme Based on Quadratic Polynomial and Lagrange Interpolation Polynomial

Hybrid subnet-based node failure recovery formal procedure in wireless sensor and actor networks

Security Analysis on Wireless Sensor Network in the Data Center for Energy Internet of Things

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