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Article
Publication date: 18 October 2018

Kalyan Nagaraj, Biplab Bhattacharjee, Amulyashree Sridhar and Sharvani GS

Phishing is one of the major threats affecting businesses worldwide in current times. Organizations and customers face the hazards arising out of phishing attacks because of…

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Abstract

Purpose

Phishing is one of the major threats affecting businesses worldwide in current times. Organizations and customers face the hazards arising out of phishing attacks because of anonymous access to vulnerable details. Such attacks often result in substantial financial losses. Thus, there is a need for effective intrusion detection techniques to identify and possibly nullify the effects of phishing. Classifying phishing and non-phishing web content is a critical task in information security protocols, and full-proof mechanisms have yet to be implemented in practice. The purpose of the current study is to present an ensemble machine learning model for classifying phishing websites.

Design/methodology/approach

A publicly available data set comprising 10,068 instances of phishing and legitimate websites was used to build the classifier model. Feature extraction was performed by deploying a group of methods, and relevant features extracted were used for building the model. A twofold ensemble learner was developed by integrating results from random forest (RF) classifier, fed into a feedforward neural network (NN). Performance of the ensemble classifier was validated using k-fold cross-validation. The twofold ensemble learner was implemented as a user-friendly, interactive decision support system for classifying websites as phishing or legitimate ones.

Findings

Experimental simulations were performed to access and compare the performance of the ensemble classifiers. The statistical tests estimated that RF_NN model gave superior performance with an accuracy of 93.41 per cent and minimal mean squared error of 0.000026.

Research limitations/implications

The research data set used in this study is publically available and easy to analyze. Comparative analysis with other real-time data sets of recent origin must be performed to ensure generalization of the model against various security breaches. Different variants of phishing threats must be detected rather than focusing particularly toward phishing website detection.

Originality/value

The twofold ensemble model is not applied for classification of phishing websites in any previous studies as per the knowledge of authors.

Details

Journal of Systems and Information Technology, vol. 20 no. 3
Type: Research Article
ISSN: 1328-7265

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Article
Publication date: 31 January 2022

Rashmi Ranjan Panigrahi, Padma Charan Mishra, Alaka Samantaray and Duryodhan Jena

The purchase is becoming a more difficult cum tactical decision that affects the cost factor, quality factor, time factor and responsive factor of the buy and maintains them. The…

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Abstract

Purpose

The purchase is becoming a more difficult cum tactical decision that affects the cost factor, quality factor, time factor and responsive factor of the buy and maintains them. The purpose of this study is to investigate the effect of inventory management (IM) practices on operational efficiencies (OEs) in Indian steel manufacturing firms.

Design/methodology/approach

The study is based on a quantitative research design that has collected information from 321 key officials of Indian steel manufacturing firms. The analyses are carried out with the use of statistical techniques such as confirmatory factor analysis and structural equation modeling (SEM).

Findings

The paper finds that inventory management (IE) has a considerable impact on the OE of steel manufacturing firms in India. The manufacturing industry must highlight the significance of inventory management practice (IMP) for enhancing firm efficiencies in a volatile environment with the help of management teams. Understanding the impact of IE practices on firms’ OE would be helpful for company shareholders and investors.

Practical implications

The paper suggests the manufacturing industry to emphasize the role of inventory management practices to have better productivity of the firm. This research focuses on the relationship between IMP and OE.

Social implications

Effective and efficient use of inventory will be helpful in reducing the overall cost of production and reduced costs to customers.

Originality/value

Companies require resources to attain a long-term competitive edge. Also, as a consequence, the research is compatible with resource-based view (RBV) theory.

Details

Journal of Advances in Management Research, vol. 19 no. 3
Type: Research Article
ISSN: 0972-7981

Keywords

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