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1.
9th International Conference on Computing for Sustainable Global Development, INDIACom 2022 ; : 323-329, 2022.
Article in English | Scopus | ID: covidwho-1863576

ABSTRACT

Undoubtedly, technology has not only transformed our world of work and lifestyle, but it also carries with it a lot of security challenges. The Distributed Denial-of-Service (DDoS) attack is one of the most prominent attacks witnessed by cyberspace of the current era. This paper outlines several DDoS attacks, their mitigation stages, propagation of attacks, malicious codes, and finally provides redemptions of exhibiting normal and DDoS attacked scenarios. A case study of a SYN flooding attack has been exploited by using Metasploit. The utilization of CPU frame length and rate have been observed in normal and attacked phases. Preliminary results clearly show that in a normal scenario, CPU usage is about 20%. However, in attacked phases with the same CPU load, CPU execution overhead is nearly 90% or 100%. Thus, through this research, the major difference was found in CPU usage, frame length, and degree of data flow. Wireshark tool has been used for network traffic analyzer. © 2022 Bharati Vidyapeeth, New Delhi.

2.
Journal of Knowledge Management ; 2022.
Article in English | Scopus | ID: covidwho-1706104

ABSTRACT

Purpose: Today many firms are pushed towards digitalization to ensure business continuity and their survival due to COVID-19. Therefore, this study aims to investigate the emerging knowledge management models in the era of digitalization and disruption. Design/methodology/approach: The authors have adopted a semi-structured approach composed of qualitative data collection from 37 business executives from India representing different industry sectors. The authors adopted a three-layer coding process (axial, open and selective) to develop a framework grounded in organizational information processing theory. Findings: Scanning the business environment leads to understand the status of current and potential business through intelligence of information, whereas better planning and execution can be achieved through employing and using the information intelligently that fits to the overall and strategic objective of the business. Overall, the business continuity can be obtained by information prosperity across the business by engaging diverse stakeholders. According to the findings, these aspects lead to the effective implementation of digital knowledge to ensure business continuity in uncertain business environment. Practical implications: The study offers the insights for managing and executing the knowledge in digital platforms, where they can think of developing a system architecture on the basis of degree of uncertainty and information processing requirements for combining the knowledge. Originality/value: The present study is unique, where it offers the meaningful visions to the designers and users of virtual knowledge management systems. © 2022, Emerald Publishing Limited.

3.
IEEE Transactions on Engineering Management ; 2021.
Article in English | Scopus | ID: covidwho-1515171

ABSTRACT

Artificial Intelligence (AI) as a technology has the potential to interpret and evaluate alternatives where multidimensional data are involved in dynamic situations such as supply chain disruption. This article aims to explore the role of resilient information systems in minimizing the risk magnitude in disruption situations in supply chain operations. The article is conducted in the qualitative mode through a semistructured interview schedule for professionals of supply chains. A thematic analysis has been used to create emerging categories. The findings of this article present critical gaps in current information systems and demonstrate how AI-oriented systems can facilitate the ecosystem of disrupted supply chains to save costs and drive efficiency on multiple parameters. The article also proposes a conceptual framework where organizational values and architectural components can be viewed jointly for quick and adequate business decisions in complex and uncertain disruptions. The framework presents the relationships among AI, information systems, and supply chain disruption. Installing appropriate AI-based data acquisition, processing, and self-training capabilities along with information system infrastructure can help organizations lessen the impact of supply chain disruption while aligning the transportation network and ensuring geographically suitable supply chains and cybersecurity. Finally, the implications for theory and practice with the limitations and scope for future research are described. IEEE

4.
International Journal of Logistics Management ; ahead-of-print(ahead-of-print):23, 2021.
Article in English | Web of Science | ID: covidwho-1331639

ABSTRACT

Purpose Many supply chains have faced disruption during Covid-19. Artificial intelligence (AI) is one mechanism that can be used to improve supply chain resilience by developing business continuity capabilities. This study examines how firms employ AI and consider the opportunities for AI to enhance supply chain resilience by developing visibility, risk, sourcing and distribution capabilities. Design/methodology/approach The authors have gathered rich data by conducting semistructured interviews with 35 experts from the e-commerce supply chain. The authors have adopted a systematic approach of coding using open, axial and selective methods to map and identify the themes that represent the critical elements of AI-enabled supply chain resilience. Findings The results of the study highlight the emergence of five critical areas where AI can contribute to enhanced supply chain resilience;(1) transparency, (2) ensuring last-mile delivery, (3) offering personalized solutions to both upstream and downstream supply chain stakeholders, (4) minimizing the impact of disruption and (5) facilitating an agile procurement strategy. Research limitations/implications The study offers interesting implications for bridging the theory-practice gap by drawing on contemporary empirical data to demonstrate how enhancing dynamic capabilities via AI technologies further strengthens supply chain resilience. The study also offers suggestions for utilizing the findings and proposes a framework to strengthen supply chain resilience through AI. Originality/value The study presents the dynamic capabilities for supply chain resilience through the employment of AI. AI can contribute to readying supply chains to reduce their risk of disruption through enhanced resilience.

5.
International Journal of Physical Distribution and Logistics Management ; 2021.
Article in English | Scopus | ID: covidwho-1281939

ABSTRACT

Purpose: COVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19. Design/methodology/approach: We adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework. Findings: An AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly. Research limitations/implications: As the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure. Practical implications: Supply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases. Originality/value: The present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience. © 2021, Emerald Publishing Limited.

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