Hamed Taherdoost - Profile on Academia.edu (original) (raw)

Papers by Hamed Taherdoost

Book Chapter, 2024

The response rate, which represents the number of individuals who answered the survey, is one of ... more The response rate, which represents the number of individuals who answered the survey, is one of the factors that impact the validity and reliability of a research study. This chapter aims to investigate the factors that impact the response rate and acceptable values. A scoping literature review is conducted to investigate recent studies in different fields ranging from management to social science and information technology, to determine the ranges of response rates and the effect of factors to gain a higher number of responses. In business and management, the average response rate was 51.18%, while in information technology, it was 41.22%. Performance assessment studies had an average response rate of 50.83%, and in the management information system field, the overall average was 32.26%. Finally, in computer science, the average response rate was 56.55%.

Information, 2025

Today, the world is experiencing constant technological evolution, allowing cyberattacks to manif... more Today, the world is experiencing constant technological evolution, allowing cyberattacks to manifest through different vectors and widely impacting victims, from specific users to serious damage to institutions' integrity. Research has shown that a significant percentage of recorded cyber incidents are attributed to social engineering practices or human error. In response to this growing threat, reinforcing cybersecurity awareness among users has become an urgent strategy to develop and apply. However, addressing cybersecurity awareness is a difficult challenge, specifically in the HE industry, where cybersecurity awareness should be an essential part of this type of institution due to the amount of critical data it handles. In addition to the need to strengthen the preparation of new professionals, statistics have shown a significant increase in successful security attacks in this industry. Therefore, this study proposes a conceptual Cybersecurity Awareness and Training Framework for Higher Education to facilitate the establishment of systems that improve the cybersecurity awareness of students in any academic institution, extending to all audiences that coexist in it. This framework encompasses key components intended to continually improve the development, integration, delivery, and evaluation of cybersecurity knowledge for individuals directly or indirectly related to the institution's information assets.

Information, 2025

This paper examines the key factors recognized as transformative in the field of human resource m... more This paper examines the key factors recognized as transformative in the field of human resource management (HRM) and explores their influence on the global adoption of artificial intelligence (AI). While AI holds significant promise for enhancing HRM efficiency, employee engagement, and Decision Making, its implementation presents a range of organizational, technical, and ethical challenges that organizations worldwide must navigate. Change aversion, data security worries, and integration expenses are major roadblocks, but strong digital leadership, company culture, and advancements in NLP and machine learning are key enablers. This paper presents a complex analysis that questions the common perception of AI as only disruptive by delving into the relationship between power dynamics, corporate culture, and technology infrastructures. In this paper, we bring together research from several fields to help scholars and practitioners understand the nuances of AI adoption in HRM, with an emphasis on the importance of inclusive methods and ethical frameworks.

Information, 2024

The rapid evolution of cybersecurity threats poses a significant challenge to organizations and i... more The rapid evolution of cybersecurity threats poses a significant challenge to organizations and individuals, necessitating strengthening defense mechanisms against malicious operations. Amidst this ever-changing environment, the importance of implementing efficacious cybersecurity awareness training has escalated dramatically. This paper presents the Integrated Cybersecurity Awareness Training (iCAT) model, which leverages knowledge graphs, serious games, and gamification to enhance cybersecurity training. The iCAT model's micro-learning module increases flexibility and accessibility, while real-time progress monitoring and adaptive feedback ensure effective learning outcomes. Evaluations show improved participant engagement and knowledge retention, making iCAT a practical and efficient solution for cybersecurity challenges. With an emphasis on adaptability and applicability, iCAT provides organizations in search of accessible and efficient cybersecurity awareness training with a streamlined approach.

Information, 2024

Supervised learning has been the cornerstone of many successful medical imaging applications. How... more Supervised learning has been the cornerstone of many successful medical imaging applications. However, its reliance on large labeled datasets poses significant challenges, especially in the medical domain, where data annotation is time-consuming and expensive. In response, selfsupervised learning (SSL) has emerged as a promising alternative, leveraging unlabeled data to learn meaningful representations without explicit supervision. This paper provides a detailed overview of supervised learning and its limitations in medical imaging, underscoring the need for more efficient and scalable approaches. The study emphasizes the importance of the area under the curve (AUC) as a key evaluation metric in assessing SSL performance. The AUC offers a comprehensive measure of model performance across different operating points, which is crucial in medical applications, where false positives and negatives have significant consequences. Evaluating SSL methods based on the AUC allows for robust comparisons and ensures that models generalize well to real-world scenarios. This paper reviews recent advances in SSL for medical imaging, demonstrating their potential to revolutionize the field by mitigating challenges associated with supervised learning. Key results show that SSL techniques, by leveraging unlabeled data and optimizing performance metrics like the AUC, can significantly improve the diagnostic accuracy, scalability, and efficiency in medical image analysis. The findings highlight SSL's capability to reduce the dependency on labeled datasets and present a path forward for more scalable and effective medical imaging solutions.

Information, 2024

The dynamic progression of technology has induced a profound metamorphosis within the realm of co... more The dynamic progression of technology has induced a profound metamorphosis within the realm of commerce, ushering in novel prospects and trials for enterprises spanning diverse sectors. In contemporary times, the rise in non-fungible tokens (NFTs) and the conception of the Metaverse have ensnared the focus of corporate entities and visionary proprietors alike. This article explores the transformation of business frameworks during the era of NFTs and the Metaverse. It delves into traditional paradigms, clarifies the unique characteristics of NFTs, and examines their potential impacts on commerce. This article investigates the convergence of virtual reality (VR), augmented reality (AR), and blockchain technology within the Metaverse. To investigate these transformations, this study undertakes a comprehensive literature evaluation. The findings highlight how NFTs and the Metaverse have introduced new avenues for generating revenue and creating value. These advancements are achieved through the utilization of smart contracts and adaptable strategies that cater to evolving consumer behaviors. This article also addresses significant challenges in this landscape and provides a forward-looking perspective on the anticipated trajectory.

Information, 2024

Amidst an unprecedented period of technological progress, incorporating digital platforms into di... more Amidst an unprecedented period of technological progress, incorporating digital platforms into diverse domains of existence has become indispensable, fundamentally altering the operational processes of governments, businesses, and individuals. Nevertheless, the swift process of digitization has concurrently led to the emergence of cybercrime, which takes advantage of weaknesses in interconnected systems. The growing dependence of society on digital communication, commerce, and information sharing has led to the exploitation of these platforms by malicious actors for hacking, identity theft, ransomware, and phishing attacks. With the growing dependence of organizations, businesses, and individuals on digital platforms for information exchange, commerce, and communication, malicious actors have identified the susceptibilities present in these systems and have begun to exploit them. This study examines 28 research papers focusing on intrusion detection systems (IDS), and phishing detection in particular, and how quickly responses and detections in cybersecurity may be made. We investigate various approaches and quantitative measurements to comprehend the link between reaction time and detection time and emphasize the necessity of minimizing both for improved cybersecurity. The research focuses on reducing detection and reaction times, especially for phishing attempts, to improve cybersecurity. In smart grids and automobile control networks, faster attack detection is important, and machine learning can help. It also stresses the necessity to improve protocols to address increasing cyber risks while maintaining scalability, interoperability, and resilience. Although machine-learning-based techniques have the potential for detection precision and reaction speed, obstacles still need to be addressed to attain real-time capabilities and adjust to constantly changing threats. To create effective defensive mechanisms against cyberattacks, future research topics include investigating innovative methodologies, integrating real-time threat intelligence, and encouraging collaboration.

Electronics, 2024

This Special Issue delves into the diverse applications of blockchain technology, spanning topics... more This Special Issue delves into the diverse applications of blockchain technology, spanning topics including democratic elections, business models, secure data storage, and large-scale ICT security. From MANET performance to cloud computing authentication challenges, this collection of papers covers innovative solutions for carbon trading and car insurance. These papers collectively showcase the evolving landscape and promising future of blockchain technology application across various domains. Blockchain is a decentralized ledger system that utilizes cryptographic algorithms to guarantee tamper-proof, secure, and transparent transactions. Network integrity can be improved through the use of consensus mechanisms, and the technology’s adaptability
extends to smart contracts for automating agreements. Blockchain has the potential to revolutionize sectors such as healthcare, finance, supply chain management, and governance by providing a secure, streamlined, and intermediary-free method for conducting digital transactions.
This Editorial provides a complete overview of the Special Issue titled “Advancement in Blockchain Technology and Applications” by combining and contextualizing the featured papers’ different contributions. This Editorial highlights trends, patterns, and important developments in blockchain’s applications in improving democratic processes,
business models, data security, and network performance while addressing obstacles and unanswered concerns. This Editorial also guides readers from various fields by providing insights into potential future research avenues, encouraging a deeper awareness of
blockchain’s cross-sector impact.

Cryptography, 2025

With the rise in applications of artificial intelligence (AI) across various sectors, security co... more With the rise in applications of artificial intelligence (AI) across various sectors, security concerns have become paramount. Traditional AI systems often lack robust security measures, making them vulnerable to adversarial attacks, data breaches, and privacy violations. Cryptography has emerged as a crucial component in enhancing AI security by ensuring data confidentiality, authentication, and integrity. This paper presents a comprehensive bibliometric review to understand the intersection between cryptography, AI, and security. A total of 495 journal articles and reviews were identified using Scopus as the primary database. The results indicate a sharp increase in research interest between 2020 and January 2025, with a significant rise in publications in 2023 and 2024. The key application areas include computer science, engineering, and materials science. Key cryptographic techniques such as homomorphic encryption, secure multiparty computation, and quantum cryptography have gained prominence in AI security. Blockchain has also emerged as an essential technology for securing AI-driven applications, particularly in data integrity and secure transactions. This paper highlights the crucial role of cryptography in safeguarding AI systems and provides future research directions to strengthen AI security through advanced cryptographic solutions.

Computers, 2024

This paper investigates the evolving landscape of blockchain technology in renewable energy. The ... more This paper investigates the evolving landscape of blockchain technology in renewable energy. The study, based on a Scopus database search on 21 February 2024, reveals a growing trend in scholarly output, predominantly in engineering, energy, and computer science. The diverse range of source types and global contributions, led by China, reflects the interdisciplinary nature of this field. This comprehensive review delves into 33 research papers, examining the integration of blockchain in renewable energy systems, encompassing decentralized power dispatching, certificate trading, alternative energy selection, and management in applications like intelligent transportation systems and microgrids. The papers employ theoretical concepts such as decentralized power dispatching models and permissioned blockchains, utilizing methodologies involving advanced algorithms, consensus mechanisms, and smart contracts to enhance efficiency, security, and transparency. The findings suggest that blockchain integration can reduce costs, increase renewable source utilization, and optimize energy management. Despite these advantages, challenges including uncertainties, privacy concerns, scalability issues, and energy consumption are identified, alongside legal and regulatory compliance and market acceptance hurdles. Overcoming resistance to change and building trust in blockchain-based systems are crucial for successful adoption, emphasizing the need for collaborative efforts among industry stakeholders, regulators, and technology developers to unlock the full potential of blockchains in renewable energy integration.

International Journal of Service Science, Management, Engineering, and Technology, 2024

Multi-criteria decision making is a complex process that involves considering various criteria or... more Multi-criteria decision making is a complex process that involves considering various criteria or factors when making a decision. Over the past few decades, several researchers have developed different methods to tackle this problem. This method offers manifold advantages, however, it faces several limits leading to the development of different modified forms. This paper provides a comprehensive review on the TOPSIS concept to help the researchers gain an overview in different aspects of TOPSIS. The literature review presented in this paper offers a comprehensive survey of the TOPSIS method, providing researchers with an overview of the various aspects of the method, its strengths and limitations, and its various applications. The results of the literature review also are provided based on the application, methodology, and reasons to use TOPSIS method.

Archives of Advanced Engineering Science, 2024

The applications of multi-criteria decision-making (MCDM) techniques are numerous. Simple Multi-A... more The applications of multi-criteria decision-making (MCDM) techniques are numerous. Simple Multi-Attribute Rating Technique (SMART) is a popular method for addressing MCDM problems with several criteria. The research investigates the SMART approach discussing how it is used and its benefits and drawbacks, in decision-making situations. It looks at how it can be applied in choosing technology, improving healthcare systems, and managing the environment. SMART simplifies decision-making by comparing options based on factors. Yet it also has drawbacks such as biases in assigning weights and may not fully address the intricacies of certain decisions. The goal of the study is to enhance comprehension of SMART advocate for its use and propose combining it with intricate decision frameworks. Even though the SMART method is now widely used there is a lack of a thorough understanding of the method to identify its various applications. This paper aims to provide a comprehensive guide and a thorough overview of the SMART method to aid in decision-making and ranking in multi-attribute scenarios.

Results in Engineering, 2025

Artificial intelligence (AI) is changing the research landscape through automation, data analysis... more Artificial intelligence (AI) is changing the research landscape through automation, data analysis, and better decision-making in various ways that are of immense help to researchers in conquering obstacles and accelerating their discoveries. From literature search to data analysis, to design experiments and manuscript writing, AIpowered tools using robotics, machine learning (ML), and natural language processing (NLP) go a long way in facilitating easy research. Technology enhances efficiency by summarizing articles, recommending publications, and pointing researchers in the right path. However, challenges such as bias in algorithms, concerns about data privacy, and deficiencies in the infrastructure impede wide-scale application. Training and supporting policies are needed for skill shortages and to surmount resistance to change in order for full utilization of AI in research. The present review has sought to explore how AI has influenced the efficiency of research through an analysis of its uses, advantages, disadvantages, and consequences across many fields. By examining the current tools and making projections on future trends, this study aims at educating academics, policymakers, and institutions on how AI might influence research in a fair and sustainable way.

Results in Engineering , 2024

Multiple industries have been revolutionized by the incorporation of data science advancements in... more Multiple industries have been revolutionized by the incorporation of data science advancements into intelligent environment technologies, specifically in the context of smart grids. Smart grids offer a dynamic and efficient framework for the management and optimization of electricity generation, distribution, and consumption, thanks to developments in big data analytics. This review delves into the integration of Smart Grid applications and Big Data analytics by reviewing 25 papers screened with PRISMA standard. The paper matter encompasses critical domains including adaptive energy management, canonical correlation analysis, and novel methodologies including blockchain and machine learning. The paper emphasizes contributions to energy efficiency, security, and sustainability by means of a rigorous methodology.

Procedia Computer Science, 2025

This paper looks at the complex balance in the acceptance of artificial intelligence (AI) between... more This paper looks at the complex balance in the acceptance of artificial intelligence (AI) between ethics, accountability, and invention. It investigates the several aspects of artificial intelligence acceptance, including the ethical issues influencing society influence as well as the developments fostering technical progress. By means of an extensive analysis of approaches for including ethical issues into artificial intelligence research, the paper underlines the need of encouraging openness, responsibility, and inclusiveness in AI systems. Leveraging multidisciplinary knowledge and cooperative efforts, stakeholders are urged to negotiate the complexity of artificial intelligence adoption with an eye on ethical standards and social benefit.

Procedia Computer Science , 2025

Cryptocurrencies are rapidly emerging as a novel virtual financial system with significant implic... more Cryptocurrencies are rapidly emerging as a novel virtual financial system with significant implications across various industries. This study systematically reviews the factors influencing cryptocurrency adoption, identifying key motivators and barriers that affect individuals' decisions to embrace this technology. Our findings reveal that while there is increasing interest in cryptocurrencies, substantial gaps remain in understanding the underlying motivations for adoption and the disparities in acceptance across different regions. We categorize these gaps and propose future research directions aimed at bridging them. Ultimately, this review contributes to a deeper understanding of cryptocurrency adoption dynamics and highlights the need for more comprehensive studies in this evolving field.

Procedia Computer Science, 2025

This article analyses the concepts behind Smart Cities, and its integration with Information, Com... more This article analyses the concepts behind Smart Cities, and its integration with Information, Communications Technology (ITC), the Internet of Things (IoT) and Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL). A smart city is a city which embraces the combination of the economy with collaboration and technology. These cities have their focus on resource efficiency and in the lenses of sustainability, it becomes a city who uses its smart resources to be environmentally amicable and reduce the carbon footprint. We will be covering an introduction to power grids, environment, transportation, and waste management systems. With the focus on Energy Management, we will further discuss the integration IoT and AI to power grids. The article addresses the main benefits of the application of AI to Energy Systems such as reduced carbon emissions from nonrenewable energy resources, energy waste prevention in homes and organizations through ML and DL, it also includes growth and infrastructure management, improved habits of consumption, and the adaptation and mitigation to climate change. This article also addresses challenges of the application of AI to Energy Management Systems, such as, ethical considerations regarding data privacy, accurate forecasting, and the decrease in funding towards green energy solutions and un updated AI educational systems.

Procedia Computer Science, 2025

Natural Language Processing (NLP) is pivotal in the fight against misinformation, offering tools ... more Natural Language Processing (NLP) is pivotal in the fight against misinformation, offering tools to process and analyze both text and speech. This paper presents the development of NLP algorithms specifically designed for fact-checking, leveraging the capabilities of Question-Answering (QA) systems and knowledge graphs. We conduct a comprehensive analysis of existing QA systems, propose enhancements for fact-checking, and validate our approach through comparative studies. Our findings contribute to the ongoing efforts to improve the reliability of information in the digital age.

Procedia Computer Science , 2025

This paper presents a comprehensive comparative study of blockchain models-public, private, and c... more This paper presents a comprehensive comparative study of blockchain models-public, private, and consortium-focusing on their security features and implications for real-world applications. The analysis reveals that while public blockchains offer strong decentralization and transparency, they face challenges related to scalability and privacy. In contrast, private blockchains prioritize control and efficiency but may introduce vulnerabilities due to centralized governance. Consortium blockchains provide a balanced approach, leveraging the strengths of both public and private models while fostering collaboration among stakeholders. Through detailed examination of security challenges such as double-spending and smart contract vulnerabilities, along with real-world case studies in sectors like supply chain management and healthcare, this study highlights critical trade-offs between security, scalability, privacy, and resilience. The findings offer valuable insights for stakeholders considering blockchain adoption and underscore the need for ongoing research to explore innovative solutions that enhance security without sacrificing decentralization or scalability.

Procedia Computer Science, 2025

Artificial intelligence combined with human resources has great possibilities to improve operatio... more Artificial intelligence combined with human resources has great possibilities to improve operational effectiveness and change HR processes. With an eye on ethics and efficiency, this research investigates the two sides of artificial intelligence adoption in HR. It looks at how artificial intelligence may save time and costs, simplify HR procedures, and enhance decision-making via data analysis. Simultaneously, the study tackles important ethical issues like data privacy, the danger of prejudice, and the requirement of openness in AI-driven judgments. The article seeks to help HR professionals use AI technology ethically by examining present trends and offering a framework for balancing these features. The results highlight the need to match artificial intelligence implementations with corporate principles and encourage an ethical culture to guarantee that the adoption of AI improves operational performance and justice.

Book Chapter, 2024

The response rate, which represents the number of individuals who answered the survey, is one of ... more The response rate, which represents the number of individuals who answered the survey, is one of the factors that impact the validity and reliability of a research study. This chapter aims to investigate the factors that impact the response rate and acceptable values. A scoping literature review is conducted to investigate recent studies in different fields ranging from management to social science and information technology, to determine the ranges of response rates and the effect of factors to gain a higher number of responses. In business and management, the average response rate was 51.18%, while in information technology, it was 41.22%. Performance assessment studies had an average response rate of 50.83%, and in the management information system field, the overall average was 32.26%. Finally, in computer science, the average response rate was 56.55%.

Information, 2025

Today, the world is experiencing constant technological evolution, allowing cyberattacks to manif... more Today, the world is experiencing constant technological evolution, allowing cyberattacks to manifest through different vectors and widely impacting victims, from specific users to serious damage to institutions' integrity. Research has shown that a significant percentage of recorded cyber incidents are attributed to social engineering practices or human error. In response to this growing threat, reinforcing cybersecurity awareness among users has become an urgent strategy to develop and apply. However, addressing cybersecurity awareness is a difficult challenge, specifically in the HE industry, where cybersecurity awareness should be an essential part of this type of institution due to the amount of critical data it handles. In addition to the need to strengthen the preparation of new professionals, statistics have shown a significant increase in successful security attacks in this industry. Therefore, this study proposes a conceptual Cybersecurity Awareness and Training Framework for Higher Education to facilitate the establishment of systems that improve the cybersecurity awareness of students in any academic institution, extending to all audiences that coexist in it. This framework encompasses key components intended to continually improve the development, integration, delivery, and evaluation of cybersecurity knowledge for individuals directly or indirectly related to the institution's information assets.

Information, 2025

This paper examines the key factors recognized as transformative in the field of human resource m... more This paper examines the key factors recognized as transformative in the field of human resource management (HRM) and explores their influence on the global adoption of artificial intelligence (AI). While AI holds significant promise for enhancing HRM efficiency, employee engagement, and Decision Making, its implementation presents a range of organizational, technical, and ethical challenges that organizations worldwide must navigate. Change aversion, data security worries, and integration expenses are major roadblocks, but strong digital leadership, company culture, and advancements in NLP and machine learning are key enablers. This paper presents a complex analysis that questions the common perception of AI as only disruptive by delving into the relationship between power dynamics, corporate culture, and technology infrastructures. In this paper, we bring together research from several fields to help scholars and practitioners understand the nuances of AI adoption in HRM, with an emphasis on the importance of inclusive methods and ethical frameworks.

Information, 2024

The rapid evolution of cybersecurity threats poses a significant challenge to organizations and i... more The rapid evolution of cybersecurity threats poses a significant challenge to organizations and individuals, necessitating strengthening defense mechanisms against malicious operations. Amidst this ever-changing environment, the importance of implementing efficacious cybersecurity awareness training has escalated dramatically. This paper presents the Integrated Cybersecurity Awareness Training (iCAT) model, which leverages knowledge graphs, serious games, and gamification to enhance cybersecurity training. The iCAT model's micro-learning module increases flexibility and accessibility, while real-time progress monitoring and adaptive feedback ensure effective learning outcomes. Evaluations show improved participant engagement and knowledge retention, making iCAT a practical and efficient solution for cybersecurity challenges. With an emphasis on adaptability and applicability, iCAT provides organizations in search of accessible and efficient cybersecurity awareness training with a streamlined approach.

Information, 2024

Supervised learning has been the cornerstone of many successful medical imaging applications. How... more Supervised learning has been the cornerstone of many successful medical imaging applications. However, its reliance on large labeled datasets poses significant challenges, especially in the medical domain, where data annotation is time-consuming and expensive. In response, selfsupervised learning (SSL) has emerged as a promising alternative, leveraging unlabeled data to learn meaningful representations without explicit supervision. This paper provides a detailed overview of supervised learning and its limitations in medical imaging, underscoring the need for more efficient and scalable approaches. The study emphasizes the importance of the area under the curve (AUC) as a key evaluation metric in assessing SSL performance. The AUC offers a comprehensive measure of model performance across different operating points, which is crucial in medical applications, where false positives and negatives have significant consequences. Evaluating SSL methods based on the AUC allows for robust comparisons and ensures that models generalize well to real-world scenarios. This paper reviews recent advances in SSL for medical imaging, demonstrating their potential to revolutionize the field by mitigating challenges associated with supervised learning. Key results show that SSL techniques, by leveraging unlabeled data and optimizing performance metrics like the AUC, can significantly improve the diagnostic accuracy, scalability, and efficiency in medical image analysis. The findings highlight SSL's capability to reduce the dependency on labeled datasets and present a path forward for more scalable and effective medical imaging solutions.

Information, 2024

The dynamic progression of technology has induced a profound metamorphosis within the realm of co... more The dynamic progression of technology has induced a profound metamorphosis within the realm of commerce, ushering in novel prospects and trials for enterprises spanning diverse sectors. In contemporary times, the rise in non-fungible tokens (NFTs) and the conception of the Metaverse have ensnared the focus of corporate entities and visionary proprietors alike. This article explores the transformation of business frameworks during the era of NFTs and the Metaverse. It delves into traditional paradigms, clarifies the unique characteristics of NFTs, and examines their potential impacts on commerce. This article investigates the convergence of virtual reality (VR), augmented reality (AR), and blockchain technology within the Metaverse. To investigate these transformations, this study undertakes a comprehensive literature evaluation. The findings highlight how NFTs and the Metaverse have introduced new avenues for generating revenue and creating value. These advancements are achieved through the utilization of smart contracts and adaptable strategies that cater to evolving consumer behaviors. This article also addresses significant challenges in this landscape and provides a forward-looking perspective on the anticipated trajectory.

Information, 2024

Amidst an unprecedented period of technological progress, incorporating digital platforms into di... more Amidst an unprecedented period of technological progress, incorporating digital platforms into diverse domains of existence has become indispensable, fundamentally altering the operational processes of governments, businesses, and individuals. Nevertheless, the swift process of digitization has concurrently led to the emergence of cybercrime, which takes advantage of weaknesses in interconnected systems. The growing dependence of society on digital communication, commerce, and information sharing has led to the exploitation of these platforms by malicious actors for hacking, identity theft, ransomware, and phishing attacks. With the growing dependence of organizations, businesses, and individuals on digital platforms for information exchange, commerce, and communication, malicious actors have identified the susceptibilities present in these systems and have begun to exploit them. This study examines 28 research papers focusing on intrusion detection systems (IDS), and phishing detection in particular, and how quickly responses and detections in cybersecurity may be made. We investigate various approaches and quantitative measurements to comprehend the link between reaction time and detection time and emphasize the necessity of minimizing both for improved cybersecurity. The research focuses on reducing detection and reaction times, especially for phishing attempts, to improve cybersecurity. In smart grids and automobile control networks, faster attack detection is important, and machine learning can help. It also stresses the necessity to improve protocols to address increasing cyber risks while maintaining scalability, interoperability, and resilience. Although machine-learning-based techniques have the potential for detection precision and reaction speed, obstacles still need to be addressed to attain real-time capabilities and adjust to constantly changing threats. To create effective defensive mechanisms against cyberattacks, future research topics include investigating innovative methodologies, integrating real-time threat intelligence, and encouraging collaboration.

Electronics, 2024

This Special Issue delves into the diverse applications of blockchain technology, spanning topics... more This Special Issue delves into the diverse applications of blockchain technology, spanning topics including democratic elections, business models, secure data storage, and large-scale ICT security. From MANET performance to cloud computing authentication challenges, this collection of papers covers innovative solutions for carbon trading and car insurance. These papers collectively showcase the evolving landscape and promising future of blockchain technology application across various domains. Blockchain is a decentralized ledger system that utilizes cryptographic algorithms to guarantee tamper-proof, secure, and transparent transactions. Network integrity can be improved through the use of consensus mechanisms, and the technology’s adaptability
extends to smart contracts for automating agreements. Blockchain has the potential to revolutionize sectors such as healthcare, finance, supply chain management, and governance by providing a secure, streamlined, and intermediary-free method for conducting digital transactions.
This Editorial provides a complete overview of the Special Issue titled “Advancement in Blockchain Technology and Applications” by combining and contextualizing the featured papers’ different contributions. This Editorial highlights trends, patterns, and important developments in blockchain’s applications in improving democratic processes,
business models, data security, and network performance while addressing obstacles and unanswered concerns. This Editorial also guides readers from various fields by providing insights into potential future research avenues, encouraging a deeper awareness of
blockchain’s cross-sector impact.

Cryptography, 2025

With the rise in applications of artificial intelligence (AI) across various sectors, security co... more With the rise in applications of artificial intelligence (AI) across various sectors, security concerns have become paramount. Traditional AI systems often lack robust security measures, making them vulnerable to adversarial attacks, data breaches, and privacy violations. Cryptography has emerged as a crucial component in enhancing AI security by ensuring data confidentiality, authentication, and integrity. This paper presents a comprehensive bibliometric review to understand the intersection between cryptography, AI, and security. A total of 495 journal articles and reviews were identified using Scopus as the primary database. The results indicate a sharp increase in research interest between 2020 and January 2025, with a significant rise in publications in 2023 and 2024. The key application areas include computer science, engineering, and materials science. Key cryptographic techniques such as homomorphic encryption, secure multiparty computation, and quantum cryptography have gained prominence in AI security. Blockchain has also emerged as an essential technology for securing AI-driven applications, particularly in data integrity and secure transactions. This paper highlights the crucial role of cryptography in safeguarding AI systems and provides future research directions to strengthen AI security through advanced cryptographic solutions.

Computers, 2024

This paper investigates the evolving landscape of blockchain technology in renewable energy. The ... more This paper investigates the evolving landscape of blockchain technology in renewable energy. The study, based on a Scopus database search on 21 February 2024, reveals a growing trend in scholarly output, predominantly in engineering, energy, and computer science. The diverse range of source types and global contributions, led by China, reflects the interdisciplinary nature of this field. This comprehensive review delves into 33 research papers, examining the integration of blockchain in renewable energy systems, encompassing decentralized power dispatching, certificate trading, alternative energy selection, and management in applications like intelligent transportation systems and microgrids. The papers employ theoretical concepts such as decentralized power dispatching models and permissioned blockchains, utilizing methodologies involving advanced algorithms, consensus mechanisms, and smart contracts to enhance efficiency, security, and transparency. The findings suggest that blockchain integration can reduce costs, increase renewable source utilization, and optimize energy management. Despite these advantages, challenges including uncertainties, privacy concerns, scalability issues, and energy consumption are identified, alongside legal and regulatory compliance and market acceptance hurdles. Overcoming resistance to change and building trust in blockchain-based systems are crucial for successful adoption, emphasizing the need for collaborative efforts among industry stakeholders, regulators, and technology developers to unlock the full potential of blockchains in renewable energy integration.

International Journal of Service Science, Management, Engineering, and Technology, 2024

Multi-criteria decision making is a complex process that involves considering various criteria or... more Multi-criteria decision making is a complex process that involves considering various criteria or factors when making a decision. Over the past few decades, several researchers have developed different methods to tackle this problem. This method offers manifold advantages, however, it faces several limits leading to the development of different modified forms. This paper provides a comprehensive review on the TOPSIS concept to help the researchers gain an overview in different aspects of TOPSIS. The literature review presented in this paper offers a comprehensive survey of the TOPSIS method, providing researchers with an overview of the various aspects of the method, its strengths and limitations, and its various applications. The results of the literature review also are provided based on the application, methodology, and reasons to use TOPSIS method.

Archives of Advanced Engineering Science, 2024

The applications of multi-criteria decision-making (MCDM) techniques are numerous. Simple Multi-A... more The applications of multi-criteria decision-making (MCDM) techniques are numerous. Simple Multi-Attribute Rating Technique (SMART) is a popular method for addressing MCDM problems with several criteria. The research investigates the SMART approach discussing how it is used and its benefits and drawbacks, in decision-making situations. It looks at how it can be applied in choosing technology, improving healthcare systems, and managing the environment. SMART simplifies decision-making by comparing options based on factors. Yet it also has drawbacks such as biases in assigning weights and may not fully address the intricacies of certain decisions. The goal of the study is to enhance comprehension of SMART advocate for its use and propose combining it with intricate decision frameworks. Even though the SMART method is now widely used there is a lack of a thorough understanding of the method to identify its various applications. This paper aims to provide a comprehensive guide and a thorough overview of the SMART method to aid in decision-making and ranking in multi-attribute scenarios.

Results in Engineering, 2025

Artificial intelligence (AI) is changing the research landscape through automation, data analysis... more Artificial intelligence (AI) is changing the research landscape through automation, data analysis, and better decision-making in various ways that are of immense help to researchers in conquering obstacles and accelerating their discoveries. From literature search to data analysis, to design experiments and manuscript writing, AIpowered tools using robotics, machine learning (ML), and natural language processing (NLP) go a long way in facilitating easy research. Technology enhances efficiency by summarizing articles, recommending publications, and pointing researchers in the right path. However, challenges such as bias in algorithms, concerns about data privacy, and deficiencies in the infrastructure impede wide-scale application. Training and supporting policies are needed for skill shortages and to surmount resistance to change in order for full utilization of AI in research. The present review has sought to explore how AI has influenced the efficiency of research through an analysis of its uses, advantages, disadvantages, and consequences across many fields. By examining the current tools and making projections on future trends, this study aims at educating academics, policymakers, and institutions on how AI might influence research in a fair and sustainable way.

Results in Engineering , 2024

Multiple industries have been revolutionized by the incorporation of data science advancements in... more Multiple industries have been revolutionized by the incorporation of data science advancements into intelligent environment technologies, specifically in the context of smart grids. Smart grids offer a dynamic and efficient framework for the management and optimization of electricity generation, distribution, and consumption, thanks to developments in big data analytics. This review delves into the integration of Smart Grid applications and Big Data analytics by reviewing 25 papers screened with PRISMA standard. The paper matter encompasses critical domains including adaptive energy management, canonical correlation analysis, and novel methodologies including blockchain and machine learning. The paper emphasizes contributions to energy efficiency, security, and sustainability by means of a rigorous methodology.

Procedia Computer Science, 2025

This paper looks at the complex balance in the acceptance of artificial intelligence (AI) between... more This paper looks at the complex balance in the acceptance of artificial intelligence (AI) between ethics, accountability, and invention. It investigates the several aspects of artificial intelligence acceptance, including the ethical issues influencing society influence as well as the developments fostering technical progress. By means of an extensive analysis of approaches for including ethical issues into artificial intelligence research, the paper underlines the need of encouraging openness, responsibility, and inclusiveness in AI systems. Leveraging multidisciplinary knowledge and cooperative efforts, stakeholders are urged to negotiate the complexity of artificial intelligence adoption with an eye on ethical standards and social benefit.

Procedia Computer Science , 2025

Cryptocurrencies are rapidly emerging as a novel virtual financial system with significant implic... more Cryptocurrencies are rapidly emerging as a novel virtual financial system with significant implications across various industries. This study systematically reviews the factors influencing cryptocurrency adoption, identifying key motivators and barriers that affect individuals' decisions to embrace this technology. Our findings reveal that while there is increasing interest in cryptocurrencies, substantial gaps remain in understanding the underlying motivations for adoption and the disparities in acceptance across different regions. We categorize these gaps and propose future research directions aimed at bridging them. Ultimately, this review contributes to a deeper understanding of cryptocurrency adoption dynamics and highlights the need for more comprehensive studies in this evolving field.

Procedia Computer Science, 2025

This article analyses the concepts behind Smart Cities, and its integration with Information, Com... more This article analyses the concepts behind Smart Cities, and its integration with Information, Communications Technology (ITC), the Internet of Things (IoT) and Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL). A smart city is a city which embraces the combination of the economy with collaboration and technology. These cities have their focus on resource efficiency and in the lenses of sustainability, it becomes a city who uses its smart resources to be environmentally amicable and reduce the carbon footprint. We will be covering an introduction to power grids, environment, transportation, and waste management systems. With the focus on Energy Management, we will further discuss the integration IoT and AI to power grids. The article addresses the main benefits of the application of AI to Energy Systems such as reduced carbon emissions from nonrenewable energy resources, energy waste prevention in homes and organizations through ML and DL, it also includes growth and infrastructure management, improved habits of consumption, and the adaptation and mitigation to climate change. This article also addresses challenges of the application of AI to Energy Management Systems, such as, ethical considerations regarding data privacy, accurate forecasting, and the decrease in funding towards green energy solutions and un updated AI educational systems.

Procedia Computer Science, 2025

Natural Language Processing (NLP) is pivotal in the fight against misinformation, offering tools ... more Natural Language Processing (NLP) is pivotal in the fight against misinformation, offering tools to process and analyze both text and speech. This paper presents the development of NLP algorithms specifically designed for fact-checking, leveraging the capabilities of Question-Answering (QA) systems and knowledge graphs. We conduct a comprehensive analysis of existing QA systems, propose enhancements for fact-checking, and validate our approach through comparative studies. Our findings contribute to the ongoing efforts to improve the reliability of information in the digital age.

Procedia Computer Science , 2025

This paper presents a comprehensive comparative study of blockchain models-public, private, and c... more This paper presents a comprehensive comparative study of blockchain models-public, private, and consortium-focusing on their security features and implications for real-world applications. The analysis reveals that while public blockchains offer strong decentralization and transparency, they face challenges related to scalability and privacy. In contrast, private blockchains prioritize control and efficiency but may introduce vulnerabilities due to centralized governance. Consortium blockchains provide a balanced approach, leveraging the strengths of both public and private models while fostering collaboration among stakeholders. Through detailed examination of security challenges such as double-spending and smart contract vulnerabilities, along with real-world case studies in sectors like supply chain management and healthcare, this study highlights critical trade-offs between security, scalability, privacy, and resilience. The findings offer valuable insights for stakeholders considering blockchain adoption and underscore the need for ongoing research to explore innovative solutions that enhance security without sacrificing decentralization or scalability.

Procedia Computer Science, 2025

Artificial intelligence combined with human resources has great possibilities to improve operatio... more Artificial intelligence combined with human resources has great possibilities to improve operational effectiveness and change HR processes. With an eye on ethics and efficiency, this research investigates the two sides of artificial intelligence adoption in HR. It looks at how artificial intelligence may save time and costs, simplify HR procedures, and enhance decision-making via data analysis. Simultaneously, the study tackles important ethical issues like data privacy, the danger of prejudice, and the requirement of openness in AI-driven judgments. The article seeks to help HR professionals use AI technology ethically by examining present trends and offering a framework for balancing these features. The results highlight the need to match artificial intelligence implementations with corporate principles and encourage an ethical culture to guarantee that the adoption of AI improves operational performance and justice.