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Article
Publication date: 12 June 2017

Vivek V. Jog and Senthil Murugan T.

Due to the connectivity of the multiple devices and the systems on the same network, rapid development has become possible in Internet of Things (IoTs) for the last…

Abstract

Purpose

Due to the connectivity of the multiple devices and the systems on the same network, rapid development has become possible in Internet of Things (IoTs) for the last decade. But, IoT is mostly affected with severe security challenges due to the potential vulnerabilities happened through the multiple connectivity of sensors, devices and system. In order to handle the security challenges, literature presents a handful of security protocols for IoT. The purpose of this paper is to present a threat profiling and elliptic curve cryptography (ECC)-based mutual and multi-level authentication for the security of IoTs. This work contains two security attributes like memory and machine-related attributes for maintaining the profile table. Also, the profile table stores the value after encrypting the value with ECC to avoid storage resilience using the proposed protocol. Furthermore, three entities like, IoT device, server and authorization centre (AC) performs the verification based on seven levels mutually to provide the resilience against most of the widely accepted attacks. Finally, DPWSim is utilized for simulation of IoT and verification of proposed protocol to show that the protocol is secure against passive and active attacks.

Design/methodology/approach

In this work, the authors have presented a threat profiling and ECC-based mutual and multi-level authentication for the security of IoTs. This work contains two security attributes like memory and machine-related attributes for maintaining the profile table. Also, the profile table stores the value after encrypting the value with ECC to avoid storage resilience using the proposed protocol. Furthermore, three entities like, IoT device, server and AC performs the verification based on seven levels mutually to provide the resilience against most of the widely accepted attacks.

Findings

DPWSim is utilized for simulation of IoT and verification of the proposed protocol to show that this protocol is secure against passive and active attacks. Also, attack analysis is carried out to prove the robustness of the proposed protocol against the password guessing attack, impersonation attack, server spoofing attack, stolen verifier attack and reply attack.

Originality/value

This paper presents a threat profiling and ECC-based mutual and multi-level authentication for the security of IoTs.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 10 no. 2
Type: Research Article
ISSN: 1756-378X

Keywords

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Article
Publication date: 19 May 2020

Praveen Kumar Gopagoni and Mohan Rao S K

Association rule mining generates the patterns and correlations from the database, which requires large scanning time, and the cost of computation associated with the…

Abstract

Purpose

Association rule mining generates the patterns and correlations from the database, which requires large scanning time, and the cost of computation associated with the generation of the rules is quite high. On the other hand, the candidate rules generated using the traditional association rules mining face a huge challenge in terms of time and space, and the process is lengthy. In order to tackle the issues of the existing methods and to render the privacy rules, the paper proposes the grid-based privacy association rule mining.

Design/methodology/approach

The primary intention of the research is to design and develop a distributed elephant herding optimization (EHO) for grid-based privacy association rule mining from the database. The proposed method of rule generation is processed as two steps: in the first step, the rules are generated using apriori algorithm, which is the effective association rule mining algorithm. In general, the extraction of the association rules from the input database is based on confidence and support that is replaced with new terms, such as probability-based confidence and holo-entropy. Thus, in the proposed model, the extraction of the association rules is based on probability-based confidence and holo-entropy. In the second step, the generated rules are given to the grid-based privacy rule mining, which produces privacy-dependent rules based on a novel optimization algorithm and grid-based fitness. The novel optimization algorithm is developed by integrating the distributed concept in EHO algorithm.

Findings

The experimentation of the method using the databases taken from the Frequent Itemset Mining Dataset Repository to prove the effectiveness of the distributed grid-based privacy association rule mining includes the retail, chess, T10I4D100K and T40I10D100K databases. The proposed method outperformed the existing methods through offering a higher degree of privacy and utility, and moreover, it is noted that the distributed nature of the association rule mining facilitates the parallel processing and generates the privacy rules without much computational burden. The rate of hiding capacity, the rate of information preservation and rate of the false rules generated for the proposed method are found to be 0.4468, 0.4488 and 0.0654, respectively, which is better compared with the existing rule mining methods.

Originality/value

Data mining is performed in a distributed manner through the grids that subdivide the input data, and the rules are framed using the apriori-based association mining, which is the modification of the standard apriori with the holo-entropy and probability-based confidence replacing the support and confidence in the standard apriori algorithm. The mined rules do not assure the privacy, and hence, the grid-based privacy rules are employed that utilize the adaptive elephant herding optimization (AEHO) for generating the privacy rules. The AEHO inherits the adaptive nature in the standard EHO, which renders the global optimal solution.

Details

Data Technologies and Applications, vol. 54 no. 3
Type: Research Article
ISSN: 2514-9288

Keywords

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Article
Publication date: 21 August 2013

L. Kozielski, M. Adamczyk, A. Lisińska-Czekaj, D. Czekaj, R. Zachariasz, M. Pawełczyk and M. Pilch

Gaining the precise control over the matter at the nanometre scale is the main leitmotif in a majority of nanoscience oriented research measurements nowadays. The…

Abstract

Gaining the precise control over the matter at the nanometre scale is the main leitmotif in a majority of nanoscience oriented research measurements nowadays. The availability of new advanced tools, as a nanoindentation technique, for evaluation of the mechanical properties, seems to be prerequisite for exploitation of the dramatic development in nanoscience and meeting the emerging needs of the industries in new electronic applications. The nanoindentation technique was applied to evaluate the elastic modulus and hardness values as a function of indentation depth. However, in the presented experiment the nanoscale mechanical properties of BaBi2Nb2O9 ceramics have been characterized and compared with the macroscale measurements with macroscale method with the implementation of ultrasound techniques. A draw conclusion indicates that expensive nanoscale characterisation presented here is not fully consisted with the microscale. The reasons of such state of things are widely discussed.

Details

World Journal of Engineering, vol. 10 no. 4
Type: Research Article
ISSN: 1708-5284

Keywords

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