Enhanced Security and Privacy from Industry 4.0 and 5.0 Vision DOI

Tarun Kumar Vashishth,

Vikas Sharma, Kewal Krishan Sharma

et al.

Published: Jan. 1, 2024

Language: Английский

Advancing occupational and system safety in Industry 5.0: Effective HAZID, risk analysis frameworks, and human-AI interaction management DOI
Kamran Gholamizadeh, Esmaeil Zarei, Luca Gualtieri

et al.

Safety Science, Journal Year: 2025, Volume and Issue: 184, P. 106770 - 106770

Published: Jan. 5, 2025

Language: Английский

Citations

2

Cybersecurity for Sustainable Smart Healthcare: State of the Art, Taxonomy, Mechanisms, and Essential Roles DOI Creative Commons
Guma Ali, Maad M. Mijwil

Deleted Journal, Journal Year: 2024, Volume and Issue: 4(2), P. 20 - 62

Published: May 23, 2024

Cutting-edge technologies have been widely employed in healthcare delivery, resulting transformative advances and promising enhanced patient care, operational efficiency, resource usage. However, the proliferation of networked devices data-driven systems has created new cybersecurity threats that jeopardize integrity, confidentiality, availability critical data. This review paper offers a comprehensive evaluation current state context smart healthcare, presenting structured taxonomy its existing cyber threats, mechanisms essential roles. study explored (SHSs). It identified discussed most pressing attacks SHSs face, including fake base stations, medjacking, Sybil attacks. examined security measures deployed to combat SHSs. These include cryptographic-based techniques, digital watermarking, steganography, many others. Patient data protection, prevention breaches, maintenance SHS integrity are some roles ensuring sustainable healthcare. The long-term viability depends on constant assessment risks harm providers, patients, professionals. aims inform policymakers, practitioners, technology stakeholders about imperatives best practices for fostering secure resilient ecosystem by synthesizing insights from multidisciplinary perspectives, such as cybersecurity, management, sustainability research. Understanding recent is controlling escalating networks encouraging intelligent delivery.

Language: Английский

Citations

8

Digital Physicians: Unleashing Artificial Intelligence in Transforming Healthcare and Exploring the Future of Modern Approaches DOI Creative Commons
Ban Salman Shukur, Mohd Khanapi Abd Ghani, Burhanuddin Mohd Aboobaider

et al.

Mesopotamian Journal of Artificial Intelligence in Healthcare, Journal Year: 2024, Volume and Issue: 2024, P. 28 - 34

Published: Feb. 2, 2024

Growing global awareness that attention to health care is the basis for maintaining citizens' quality of life. Health institutions seek increase interest in electronic services and enhance patient results by integrating artificial intelligence techniques. Artificial tools are indispensable diagnosis, treatment, care. Integrating techniques into development healthcare environment works public disease prevention provide free all citizens. Designing platforms raises society, provides programs initiatives, reaches homes, gardens, schools, universities through applications based on intelligence. The primary purpose this article challenge extent which related medicine its contribution positive negative effects revolutionizing services.

Language: Английский

Citations

7

Deciphering stakeholder voice on the challenges of transformative healthcare 5.0 ecosystem: a quality function deployment analyses DOI
Ravindra Ojha, Alpana Agarwal

Journal of Health Organization and Management, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 13, 2025

Purpose The healthcare ecosystem continues to evolve with new technological developments the support of its stakeholders. technology-driven and patient-centric Healthcare 5.0 (H5.0) is undergoing a transformation promising enormous benefits. However, need identify understand inherent challenges barriers faced in journey H5.0 implementation relevant countermeasures for accelerated has become critical. Design/methodology/approach current research paper utilised Delphi approach collection information applied well-proven quality function deployment (QFD) methodology analysis. Findings house (HOQ) tool from QFD highlighted critical which contribute to, approximately, 60% total weight. identified top five process descriptors developed HOQ also contribute, approximately among overall countermeasures. A useful progress (HIP) index been recommended tracking made journey. Originality/value This first that provided application domain H5.0. It insights Furthermore, development simple practical HIP another value addition.

Language: Английский

Citations

0

Security and privacy considerations in IoMT in Healthcare 5.0 DOI
Bitan Misra, Sayan Chakraborty, Nilanjan Dey

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 151 - 169

Published: Jan. 1, 2025

Language: Английский

Citations

0

Mitigating Data Exfiltration Ransomware through Advanced Decoy File Strategies DOI Creative Commons
Shishi Liu, Xin Chen

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Dec. 15, 2023

Abstract This study introduces an advanced decoy file strategy utilizing Generative Adversarial Networks (GANs) to combat data exfiltration ransomware threats. Focused on creating highly realistic documents, the system embeds these across enterprise networks, engaging threats effectively. It includes real-time monitoring for abnormal interactions and proactive response mechanisms threat containment. Rigorous testing against various samples demonstrated high engagement rates rapid times, confirming system's effectiveness. Integration diverse network types was achieved with minimal operational overhead. highlights adaptability in face of evolving tactics underscores balance between realism deployability.

Language: Английский

Citations

11

Integrating MLSecOps in the Biotechnology Industry 5.0 DOI Creative Commons

Naseela Pervez,

Alexander J. Titus

IntechOpen eBooks, Journal Year: 2024, Volume and Issue: unknown

Published: May 10, 2024

Biotechnology Industry 5.0 is advancing with the integration of cutting-edge technologies such as Machine Learning (ML), Internet Things (IoT), and cloud computing. It no surprise that an industry utilizes data from customers can alter their lives a target variety attacks. This chapter provides perspective on how Security Operations (MLSecOps) help secure biotechnology 5.0. The analysis threats in ML algorithms best practices. explores scope MLSecOps 5.0, highlighting crucial it to comply current regulatory frameworks. With developing innovative solutions healthcare, supply chain management, biomanufacturing, pharmaceutical sectors, more, also discusses practices enterprises should follow while considering ethical responsibilities. Overall, discussion integrate into design, deployment, regulation processes

Language: Английский

Citations

2

Advancing Healthcare Security: Exploring Applications, Challenges, and Future Research Paths in Healthcare 5.0 DOI

Aryan Dahiya,

Anuradha Dhull, Akansha Singh

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

1

Securing Healthcare Data and Cybersecurity Innovations in the Era of Industry 5.0 DOI
Leena Arya

Advances in healthcare information systems and administration book series, Journal Year: 2024, Volume and Issue: unknown, P. 132 - 147

Published: July 23, 2024

This chapter reviews the healthcare prospects that include obsolete infrastructure, disparate ecosystems, human mistakes, and data privacy issues then assesses ability of Industry 5.0 technologies to strengthen resilience while pointing out security risks smart devices, AI, blockchain, IoT applications operating on medical care efficacy. The suggests a multi-faceted approach centering cybersecurity by design, advanced threat detection, governance, joint efforts. To solve these issues, innovations made specifically for in healthcare, overcoming its threats, institutions will be able build more resilient secure digital tomorrow patients providers.

Language: Английский

Citations

0

Deep Learning Applications for Healthcare Risk Assessment DOI

Sana Fateh,

Imdad Ali Shah,

Quratulain Sial

et al.

Advances in healthcare information systems and administration book series, Journal Year: 2024, Volume and Issue: unknown, P. 59 - 76

Published: Nov. 22, 2024

The primary object of this chapter is to focus on deep learning and how it useful for healthcare risk assessment. A potential risk, mitigate weaknesses assessment important early detection through the analysis guarantee patient staff safety. approach tackling everyday problems has radically changed in age artificial intelligence (AI), machine learning, learning. We are now concentrating developing technology that specific fields. Deep techniques offer a wide range applications health care, even though still its phases. From keeping an individual's universal record emerging technologies enabled by we will see many upgrades fundamentally change industry scenario coming years. can evaluate organized or unstructured data at high rate.

Language: Английский

Citations

0