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Article
Publication date: 22 October 2019

Navneet Bhatt, Adarsh Anand and Deepti Aggrawal

The purpose of this paper is to provide a mathematical framework to optimally allocate resources required for the discovery of vulnerabilities pertaining to different severity…

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Abstract

Purpose

The purpose of this paper is to provide a mathematical framework to optimally allocate resources required for the discovery of vulnerabilities pertaining to different severity risk levels.

Design/methodology/approach

Different sets of optimization problems have been formulated and using the concept of dynamic programming approach, sequence of recursive functions has been constructed for the optimal allocation of resources used for discovering vulnerabilities of different severity scores. Mozilla Thunderbird web browser data set has been considered for giving the empirical evaluation by working with vulnerabilities of different severities.

Findings

As per the impact associated with a vulnerability, critical and high severity level are required to be patched promptly, and hence, a larger amount of funds have to be allocated for vulnerability discovery. Nevertheless, a low or medium risk vulnerability might also get exploited and thereby their discovery is also crucial for higher severity vulnerabilities. The current framework provides a diversified allocation of funds as per the requirement of a software manager and also aims at improving the discovery of vulnerability significantly.

Practical implications

The finding of this research may enable software managers to adequately assign resources in managing the discovery of vulnerabilities. It may also help in acknowledging the funds required for various bug bounty programs to cater security reporters based on the potential number of vulnerabilities present in software.

Originality/value

Much of the attention has been focused on the vulnerability discovery modeling and the risk associated with the security flaws. But, as far as the authors’ knowledge is concern, there is no such study that incorporates optimal allocation of resources with respect to the vulnerabilities of different severity scores. Hence, the building block of this paper contributes to future research.

Details

International Journal of Quality & Reliability Management, vol. 37 no. 6/7
Type: Research Article
ISSN: 0265-671X

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Book part
Publication date: 18 July 2022

Vimal Sharma and Deepak Sood

Introduction: Artificial intelligence (AI), the engineering of brilliant machinery, performs intelligent human intelligence tasks, such as learning and problem-solving. Insurance…

Abstract

Introduction: Artificial intelligence (AI), the engineering of brilliant machinery, performs intelligent human intelligence tasks, such as learning and problem-solving. Insurance is a financial protection policy either for individuals or entities to reimburse losses from the insured company. The role of AI in insurance always helps enhance customer services and understand their behaviour.

Purpose: This chapter aims to determine the role of AI in the insurance industry in India. The insurance industry is expanding very fast, and to further increase its horizons, the part of the technology of AI is essential. However, this sector has initiated using AI technology and is expanding its scope to benefit the customers.

Methodology: The authors selected research papers of the last five years to review and determine how the technology changed during the period and how an increase in AI benefits the industry and facilitates delivering the best services, and understanding the customer’s needs and behaviour.

Findings: It has been found that the industry is moving very fast and adopting the AI technology methods to enhance customer services, betterment for growing India, and serve insurance services to the nation efficiently.

Details

Big Data Analytics in the Insurance Market
Type: Book
ISBN: 978-1-80262-638-4

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Article
Publication date: 4 December 2020

Vimal Kumar, Pratima Verma, Ajay Jha, Kuei-Kuei Lai and Manh-Hoang Do

This research presents a study on the supply chain process of an Indian apparel industry considering various parameters involved. The study aims to identify the main parameters to…

805

Abstract

Purpose

This research presents a study on the supply chain process of an Indian apparel industry considering various parameters involved. The study aims to identify the main parameters to improve the supply chain process and develop a comprehensive structural relationship to rank them to streamline the apparel supply chain process and business environment.

Design/methodology/approach

The team of five experts from this apparel industry was made to give scores to multiple parameters. The TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) technique is used to develop the model for eleven key parameters and then rank them.

Findings

Based on the data analysis the planning, customer and warehouse storage have emerged as top three key parameters while the non-replenishment approach, push and pull strategy and manufacturing of the product are identified as the bottom three parameters from a hierarchy level. These parameters have been ranked based on their contributing attributes in this apparel supply chain process.

Research limitations/implications

The study provides an overall ranking of parameters and the implications are in the direction of helping the industry to improve its supply chain performances rather than focus only on productivity. Further, the key parameters are identified as critical inputs and show that the firms are being more proactive and well prepared comprised of the industry.

Originality/value

The study indicates that the key parameters are identified by this apparel brand to improve its supply chain process. The key supply chain process involves planning, manufacturing, distribution, end customer and returns logistics of the goods, etc. So, this research also provides the focused parameters on the supply chain performance received by end customer from the supplier and rank them for effectiveness and improve their overall organizational performance. It also provides a critical observation of their supply chain process improvement which includes different brand uses, strategies and approaches.

Details

International Journal of Productivity and Performance Management, vol. 71 no. 2
Type: Research Article
ISSN: 1741-0401

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