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1 – 10 of over 2000
Article
Publication date: 22 March 2024

Ghulam Mustafa, Waqas Rafiq, Naveed Jhamat, Zeeshan Arshad and Farhana Aziz Rana

This study aims to evaluate blockchain as an e-government governance model. It assesses its alignment with legal frameworks, emphasizing robustness against disruptions and…

Abstract

Purpose

This study aims to evaluate blockchain as an e-government governance model. It assesses its alignment with legal frameworks, emphasizing robustness against disruptions and adherence to existing laws.

Design/methodology/approach

The paper explores blockchain’s potential in e-government, focusing on legal, ethical and governance aspects. It conducts an in-depth analysis of blockchain’s integration into data governance, emphasizing legal compliance and resilient security protocols.

Findings

The study comprehensively evaluates blockchain’s implementation, covering privacy, interoperability, consensus mechanisms, scalability and regulatory alignment. It highlights governance’s critical role in ensuring legal compliance within blockchain paradigms.

Research limitations/implications

Ethical and legal concerns arising from blockchain adoption remain unresolved. The study underscores how blockchain challenges its core principles of anonymity and decentralization in e-government settings.

Practical implications

The framework outlined offers potential for diverse technological environments, albeit raising ethical and legal queries. It emphasizes governance’s pivotal role in achieving legal compliance in blockchain adoption.

Social implications

Blockchain’s impact on legal and ethical facets necessitates further exploration to align with its core principles while addressing governance in e-government settings.

Originality/value

This study presents a robust framework for assessing blockchain’s viability in e-government, emphasizing legal compliance, despite ethical and legal intricacies that challenge its fundamental principles.

Details

International Journal of Law and Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-243X

Keywords

Article
Publication date: 16 October 2023

Chien-Wen Shen and Phung Phi Tran

This study aims to provide a more complete picture of blockchain development by combining numerous methodologies with diverse data sources, such as academic papers and news…

Abstract

Purpose

This study aims to provide a more complete picture of blockchain development by combining numerous methodologies with diverse data sources, such as academic papers and news articles. This study displays the developmental status of each subject based on the interrelationships of each topic cluster by analyzing high-frequency keywords extracted from the collected data. Moreover, applying above methodologies will help understanding top research topics, authors, venues, institutes and countries. The differences of blockchain research and new are identified.

Design/methodology/approach

To identify and find blockchain development linkages, researchers have used search terms such as co-occurrence, bibliographic coupling, co-citation and co-authorship to help us understand the top research topics, authors, venues, institutes and countries. This study also used text mining analysis to identify blockchain articles' primary concepts and semantic structures.

Findings

The findings show the fundamental topics based on each topic cluster's links. While “technology”, “transaction”, “privacy and security”, “environment” and “consensus” were most strongly associated with blockchain in research, “platform”, “big data and cloud”, “network”, “healthcare and business” and “authentication” were closely tied to blockchain news. This article classifies blockchain principles into five patterns: hardware and infrastructure, data, networking, applications and consensus. These statistics helped the authors comprehend the top research topics, authors, venues, publication institutes and countries.

Research limitations/implications

Since Web of Science (WoS) and LexisNexis Academic data are used, the study has few sources. Others advise merging foreign datasets. WoS is one of the world's largest and most-used databases for assessing scientific papers.

Originality/value

This study has several uses and benefits. First, key concept discoveries can help academics understand blockchain research trends so they can prioritize research initiatives. Second, bibliographic coupling links academic papers on blockchain. It helps information seekers search and classify the material. Co-citation analysis results can help researchers identify potential partners and leaders in their field. The network's key organizations or countries should be proactive in discovering, proposing and creating new relationships with other organizations or countries, especially those from the journal network's border, to make the overall network more integrated and linked. Prominent members help recruit new authors to organizations or countries and link them to the co-authorship network. This study also used concept-linking analysis to identify blockchain articles' primary concepts and semantic structures. This may lead to new authors developing research ideas or subjects in primary disciplines of inquiry.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 31 January 2024

Malik Muneer Abu Afifa, Tho Hoang Nguyen, Lien Thuy Le Nguyen, Thuy Hong Thi Tran and Nhan Thanh Dao

This study aims to examine the relationship between blockchain technology (BCT) adoption and firm performance (FIP) mediated by cyber-security risk management (CSRM) in the…

Abstract

Purpose

This study aims to examine the relationship between blockchain technology (BCT) adoption and firm performance (FIP) mediated by cyber-security risk management (CSRM) in the context of Vietnam, a developing country. Besides, the mediating effect of risk-taking tendency (RTT) has been considered in the BCT–CSRM nexus.

Design/methodology/approach

Data is collected using a survey questionnaire of Vietnamese financial firms through strict screening steps to ensure the representativeness of the population. The ending pattern of 449 responses has been used for analysis.

Findings

The findings of partial least squares structural equation modeling demonstrated that CSRM has a positive effect on FIP and acts as a mediator in the BCT–FIP nexus. Furthermore, RTT moderates the relationship between BCT and CSRM significantly.

Practical implications

This study introduces the attractive attributes of applying BCT to CSRM. Accordingly, managers should rely on BCT and take advantage of it to improve investment resources, business activities and functional areas to enhance their firm's CSRM. Especially, managers should pay attention to enhancing their RTT, which improves FIP.

Originality/value

This study supplements the previous literature in the context of CSRM by indicating favorable effects of BCT and RTT. Additionally, this study identifies the effectiveness of RTT as well as its moderating role. Ultimately, this paper has been managed as a pioneering empirical study that integrates BCT, RTT and CSRM in the same model in a developing country, specifically Vietnam.

Details

International Journal of Organizational Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1934-8835

Keywords

Article
Publication date: 27 February 2024

Shefali Arora, Ruchi Mittal, Avinash K. Shrivastava and Shivani Bali

Deep learning (DL) is on the rise because it can make predictions and judgments based on data that is unseen. Blockchain technologies are being combined with DL frameworks in…

Abstract

Purpose

Deep learning (DL) is on the rise because it can make predictions and judgments based on data that is unseen. Blockchain technologies are being combined with DL frameworks in various industries to provide a safe and effective infrastructure. The review comprises literature that lists the most recent techniques used in the aforementioned application sectors. We examine the current research trends across several fields and evaluate the literature in terms of its advantages and disadvantages.

Design/methodology/approach

The integration of blockchain and DL has been explored in several application domains for the past five years (2018–2023). Our research is guided by five research questions, and based on these questions, we concentrate on key application domains such as the usage of Internet of Things (IoT) in several applications, healthcare and cryptocurrency price prediction. We have analyzed the main challenges and possibilities concerning blockchain technologies. We have discussed the methodologies used in the pertinent publications in these areas and contrasted the research trends during the previous five years. Additionally, we provide a comparison of the widely used blockchain frameworks that are used to create blockchain-based DL frameworks.

Findings

By responding to five research objectives, the study highlights and assesses the effectiveness of already published works using blockchain and DL. Our findings indicate that IoT applications, such as their use in smart cities and cars, healthcare and cryptocurrency, are the key areas of research. The primary focus of current research is the enhancement of existing systems, with data analysis, storage and sharing via decentralized systems being the main motivation for this integration. Amongst the various frameworks employed, Ethereum and Hyperledger are popular among researchers in the domain of IoT and healthcare, whereas Bitcoin is popular for research on cryptocurrency.

Originality/value

There is a lack of literature that summarizes the state-of-the-art methods incorporating blockchain and DL in popular domains such as healthcare, IoT and cryptocurrency price prediction. We analyze the existing research done in the past five years (2018–2023) to review the issues and emerging trends.

Details

International Journal of Quality & Reliability Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 19 February 2024

Kashmira Ganji and Nikhat Afshan

In response to the growing interest in Internet of Things (IoT) technology and its profound implications for businesses and individuals, this bibliometric study focuses on a…

Abstract

Purpose

In response to the growing interest in Internet of Things (IoT) technology and its profound implications for businesses and individuals, this bibliometric study focuses on a critical yet understudied aspect, i.e. cybersecurity. As IoT adoption grows, so do concerns regarding user privacy and data security. This study aims to provide a comprehensive understanding of the current research in this vital area, shedding light on research trends, gaps and emerging themes.

Design/methodology/approach

The study conducted a bibliometric analysis and systematic review of literature spanning over two decades (2013–2023). Bibliometric analysis is conducted using Biblioshiny which is R-software-based advanced analytical tool. Further, VOSviewer is used to conduct network analysis. The study highlights the evolving landscape of IoT cybersecurity, emphasizing interdisciplinary intersections and the ethical dimensions of IoT technologies.

Findings

The study uncovers crucial concerns related to IoT adoption, emphasizing the urgent need for comprehensive cybersecurity protocols. It identifies emerging themes such as artificial intelligence and blockchain integration, indicating a shift toward interdisciplinary solutions. Furthermore, the research highlights ethical gaps in current IoT discussions, emphasizing the importance of responsible innovation.

Research limitations/implications

Businesses can bolster their cybersecurity strategies, policymakers can craft informed regulations and researchers are encouraged to explore IoT’s ethical dimensions.

Originality/value

This study pioneers a nuanced analysis of IoT cybersecurity, filling a crucial gap in the existing business and management literature. By synthesizing a decade of scholarly work, it provides foundational insights for researchers, businesses and policymakers. The research not only informs academic discourse but also offers practical guidance for enhancing IoT security measures and fostering ethical innovation.

Details

Journal of Science and Technology Policy Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2053-4620

Keywords

Article
Publication date: 14 January 2022

Sandeep Kumar Reddy Thota, C. Mala and Geetha Krishnan

A wireless body area network (WBAN) is a collection of sensing devices attached to a person’s body that is typically used during health care to track their physical state. This…

Abstract

Purpose

A wireless body area network (WBAN) is a collection of sensing devices attached to a person’s body that is typically used during health care to track their physical state. This paper aims to study the security challenges and various attacks that occurred while transferring a person’s sensitive medical diagnosis information in WBAN.

Design/methodology/approach

This technology has significantly gained prominence in the medical field. These wearable sensors are transferring information to doctors, and there are numerous possibilities for an intruder to pose as a doctor and obtain information about the patient’s vital information. As a result, mutual authentication and session key negotiations are critical security challenges for wearable sensing devices in WBAN. This work proposes an improved mutual authentication and key agreement protocol for wearable sensing devices in WBAN. The existing related schemes require more computational and storage requirements, but the proposed method provides a flexible solution with less complexity.

Findings

As sensor devices are resource-constrained, proposed approach only makes use of cryptographic hash-functions and bit-wise XOR operations, hence it is lightweight and flexible. The protocol’s security is validated using the AVISPA tool, and it will withstand various security attacks. The proposed protocol’s simulation and performance analysis are compared to current relevant schemes and show that it produces efficient outcomes.

Originality/value

This technology has significantly gained prominence in the medical sector. These sensing devises transmit information to doctors, and there are possibilities for an intruder to pose as a doctor and obtain information about the patient’s vital information. Hence, this paper proposes a lightweight and flexible protocol for mutual authentication and key agreement for wearable sensing devices in WBAN only makes use of cryptographic hash-functions and bit-wise XOR operations. The proposed protocol is simulated using AVISPA tool and its performance is better compared to the existing methods. This paper proposes a novel improved mutual authentication and key-agreement protocol for wearable sensing devices in WBAN.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 3 October 2023

Shao-Fang Wen and Basel Katt

Security assurance evaluation (SAE) is a well-established approach for assessing the effectiveness of security measures in systems. However, one aspect that is often overlooked in…

Abstract

Purpose

Security assurance evaluation (SAE) is a well-established approach for assessing the effectiveness of security measures in systems. However, one aspect that is often overlooked in these evaluations is the assurance context in which they are conducted. This paper aims to explore the role of assurance context in system SAEs and proposes a conceptual model to integrate the assurance context into the evaluation process.

Design/methodology/approach

The conceptual model highlights the interrelationships between the various elements of the assurance context, including system boundaries, stakeholders, security concerns, regulatory compliance and assurance assumptions and regulatory compliance.

Findings

By introducing the proposed conceptual model, this research provides a framework for incorporating the assurance context into SAEs and offers insights into how it can influence the evaluation outcomes.

Originality/value

By delving into the concept of assurance context, this research seeks to shed light on how it influences the scope, methodologies and outcomes of assurance evaluations, ultimately enabling organizations to strengthen their system security postures and mitigate risks effectively.

Details

Information & Computer Security, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2056-4961

Keywords

Article
Publication date: 19 August 2022

Anjali More and Dipti Rana

Referred data set produces reliable information about the network flows and common attacks meeting with real-world criteria. Accordingly, this study aims to focus on the use of…

Abstract

Purpose

Referred data set produces reliable information about the network flows and common attacks meeting with real-world criteria. Accordingly, this study aims to focus on the use of imbalanced intrusion detection benchmark knowledge discovery in database (KDD) data set. KDD data set is most preferably used by many researchers for experimentation and analysis. The proposed algorithm improvised random forest classification with error tuning factors (IRFCETF) deals with experimentation on KDD data set and evaluates the performance of a complete set of network traffic features through IRFCETF.

Design/methodology/approach

In the current era of applications, the attention of researchers is immersed by a diverse number of existing time applications that deals with imbalanced data classification (ImDC). Real-time application areas, artificial intelligence (AI), Industrial Internet of Things (IIoT), etc. are dealing ImDC undergo with diverted classification performance due to skewed data distribution (SkDD). There are numerous application areas that deal with SkDD. Many of the data applications in AI and IIoT face the diverted data classification rate in SkDD. In recent advancements, there is an exponential expansion in the volume of computer network data and related application developments. Intrusion detection is one of the demanding applications of ImDC. The proposed study focusses on imbalanced intrusion benchmark data set, KDD data set and other benchmark data set with the proposed IRFCETF approach. IRFCETF justifies the enriched classification performance on imbalanced data set over the existing approach. The purpose of this work is to review imbalanced data applications in numerous application areas including AI and IIoT and tuning the performance with respect to principal component analysis. This study also focusses on the out-of-bag error performance-tuning factor.

Findings

Experimental results on KDD data set shows that proposed algorithm gives enriched performance. For referred intrusion detection data set, IRFCETF classification accuracy is 99.57% and error rate is 0.43%.

Research limitations/implications

This research work extended for further improvements in classification techniques with multiple correspondence analysis (MCA); hierarchical MCA can be focussed with the use of classification models for wide range of skewed data sets.

Practical implications

The metrics enhancement is measurable and helpful in dealing with intrusion detection systems–related imbalanced applications in current application domains such as security, AI and IIoT digitization. Analytical results show improvised metrics of the proposed approach than other traditional machine learning algorithms. Thus, error-tuning parameter creates a measurable impact on classification accuracy is justified with the proposed IRFCETF.

Social implications

Proposed algorithm is useful in numerous IIoT applications such as health care, machinery automation etc.

Originality/value

This research work addressed classification metric enhancement approach IRFCETF. The proposed method yields a test set categorization for each case with error reduction mechanism.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 29 December 2022

K.V. Sheelavathy and V. Udaya Rani

Internet of Things (IoT) is a network, which provides the connection with various physical objects such as smart machines, smart home appliance and so on. The physical objects are…

Abstract

Purpose

Internet of Things (IoT) is a network, which provides the connection with various physical objects such as smart machines, smart home appliance and so on. The physical objects are allocated with a unique internet address, namely, Internet Protocol, which is used to perform the data broadcasting with the external objects using the internet. The sudden increment in the number of attacks generated by intruders, causes security-related problems in IoT devices while performing the communication. The main purpose of this paper is to develop an effective attack detection to enhance the robustness against the attackers in IoT.

Design/methodology/approach

In this research, the lasso regression algorithm is proposed along with ensemble classifier for identifying the IoT attacks. The lasso algorithm is used for the process of feature selection that modeled fewer parameters for the sparse models. The type of regression is analyzed for showing higher levels when certain parts of model selection is needed for parameter elimination. The lasso regression obtains the subset for predictors to lower the prediction error with respect to the quantitative response variable. The lasso does not impose a constraint for modeling the parameters caused the coefficients with some variables shrink as zero. The selected features are classified by using an ensemble classifier, that is important for linear and nonlinear types of data in the dataset, and the models are combined for handling these data types.

Findings

The lasso regression with ensemble classifier–based attack classification comprises distributed denial-of-service and Mirai botnet attacks which achieved an improved accuracy of 99.981% than the conventional deep neural network (DNN) methods.

Originality/value

Here, an efficient lasso regression algorithm is developed for extracting the features to perform the network anomaly detection using ensemble classifier.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 24 June 2022

Maitri Patel, Rajan Patel, Nimisha Patel, Parita Shah and Kamal Gulati

In the field of cryptography, authentication, secrecy and identification can be accomplished by use of secret keys for any computer-based system. The need to acquire certificates…

Abstract

Purpose

In the field of cryptography, authentication, secrecy and identification can be accomplished by use of secret keys for any computer-based system. The need to acquire certificates endorsed through CA to substantiate users for the barter of encoded communications is one of the most significant constraints for the extensive recognition of PKC, as the technique takes too much time and susceptible to error. PKC’s certificate and key management operating costs are reduced with IBC. IBE is a crucial primeval in IBC. The thought behind presenting the IBE scheme was to diminish the complexity of certificate and key management, but it also gives rise to key escrow and key revocation problem, which provides access to unauthorised users for the encrypted information.

Design/methodology/approach

This paper aims to compare the result of IIBES with the existing system and to provide security analysis for the same and the proposed system can be used for the security in federated learning.

Findings

Furthermore, it can be implemented using other encryption/decryption algorithms like elliptic curve cryptography (ECC) to compare the execution efficiency. The proposed system can be used for the security in federated learning.

Originality/value

As a result, a novel enhanced IBE scheme: IIBES is suggested and implemented in JAVA programming language using RSA algorithm, which eradicates the key escrow problem through eliminating the need for a KGC and key revocation problem by sing sub-KGC (SKGC) and a shared secret with nonce. IIBES also provides authentication through IBS as well as it can be used for securing the data in federated learning.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

Keywords

1 – 10 of over 2000