Leveraging futuristic machine learning and next-generational security for e-governance:
"In an era defined by rapid technological advancement and a pressing need for effective governance, the intersection of machine learning and cybersecurity has emerged as a pivotal area of exploration and innovation. E-governance serves as a vital framework for enhancing the delivery of public s...
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| Other Authors: | , , , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
2025.
|
| Series: | Advances in electronic government, digital divide, and regional development (AEGDDRD) book series.
|
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | "In an era defined by rapid technological advancement and a pressing need for effective governance, the intersection of machine learning and cybersecurity has emerged as a pivotal area of exploration and innovation. E-governance serves as a vital framework for enhancing the delivery of public services, increasing governmental transparency, and fostering citizen engagement. However, as governments increasingly rely on digital infrastructures, they expose themselves to a myriad of cyber threats that can undermine public trust and security. The contemporary landscape of e-governance must not only adapt to the wave of new digital tools but also ensure the security and integrity of the data that underpins them. Leveraging Futuristic Machine Learning and Next-Generational Security for e-Governance brings together a comprehensive collection of insights and research from leading experts in the fields of artificial intelligence, cybersecurity, and public administration. The contributions to this volume encompass theoretical frameworks, case studies, and practical applications that showcase the transformative potential of integrating machine learning with next-generation security solutions. With this resource, researchers, practitioners, and academics can work toward a new age where e-governance thrives at the nexus of machine learning and cybersecurity."-- |
| Physical Description: | 18 PDFs (356 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9798369378854 |
| Access: | Restricted to subscribers or individual electronic text purchasers. |
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| 245 | 0 | 0 | |a Leveraging futuristic machine learning and next-generational security for e-governance |c Rajeev Kumar, Abu Bakar Abdul Hamid, Noor Inayah Binti Ya'akub, Tadiwa Elisha Nyamasvisva, Rajesh Kumar Tiwari, editors. |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) |b IGI Global |c 2025. | |
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| 490 | 1 | |a Advances in electronic government, digital divide, and regional development (AEGDDRD) book series | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Preface -- Chapter 1. Bridging E-Governance and Sustainability: Unveiling Synergies for a Sustainable Future -- Chapter 2. The Next Generation of Greentech Trends and Innovations Shaping Sustainable E-Governance -- Chapter 3. A Primer for Governance -- Chapter 4. Machine Learning for Traffic Management, Object Detection, and Collision Avoidance in Autonomous Driving for Smart City Governance -- Chapter 5. Cutting-Edge Deep Learning Approaches for Human Pose Estimation and Activity Recognition in Smart Cities -- Chapter 6. Approaches of Deep Learning Used in Cyber Security and Cyber-Crime -- Chapter 7. Cybersecurity Affected Social Life Using Online Transactions in India -- Chapter 8. Cyber-Physical Systems for Enhancement in Security While Using Cyber -- Chapter 9. Security of Linear Regression Models -- Chapter 10. Optimizing Image Encryption Efficiency Through Advanced Deep Learning Architectures and Techniques -- Chapter 11. Machine Learning for Healthcare Fraud Detection: A Comprehensive Review Literature -- Chapter 12. Impact of the COVID-19 Pandemic on Healthcare Fraud: A Comprehensive Literature Review -- Compilation of References -- About the Contributors -- Index. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "In an era defined by rapid technological advancement and a pressing need for effective governance, the intersection of machine learning and cybersecurity has emerged as a pivotal area of exploration and innovation. E-governance serves as a vital framework for enhancing the delivery of public services, increasing governmental transparency, and fostering citizen engagement. However, as governments increasingly rely on digital infrastructures, they expose themselves to a myriad of cyber threats that can undermine public trust and security. The contemporary landscape of e-governance must not only adapt to the wave of new digital tools but also ensure the security and integrity of the data that underpins them. Leveraging Futuristic Machine Learning and Next-Generational Security for e-Governance brings together a comprehensive collection of insights and research from leading experts in the fields of artificial intelligence, cybersecurity, and public administration. The contributions to this volume encompass theoretical frameworks, case studies, and practical applications that showcase the transformative potential of integrating machine learning with next-generation security solutions. With this resource, researchers, practitioners, and academics can work toward a new age where e-governance thrives at the nexus of machine learning and cybersecurity."-- |c Provided by publisher. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 12/09/2024). | ||
| 650 | 0 | |a Computer security. | |
| 650 | 0 | |a Deep learning (Machine learning) |x Industrial applications. | |
| 653 | |a Activity Recognition. | ||
| 653 | |a Blockchain. | ||
| 653 | |a Cyber Crime. | ||
| 653 | |a Cyber Physical System. | ||
| 653 | |a Cyber Security. | ||
| 653 | |a Deep Learning. | ||
| 653 | |a Exogenous Determinants. | ||
| 653 | |a Greentech Trends. | ||
| 653 | |a Machine Learning. | ||
| 653 | |a Object Detection. | ||
| 653 | |a Online Transactions. | ||
| 653 | |a Optimizing Image Encryption Efficiency. | ||
| 653 | |a Skill Development. | ||
| 653 | |a Smart Cities. | ||
| 653 | |a Sustainable E-Governance. | ||
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a Abdul Hamid, Abu Bakar |d 1967- |e editor. | |
| 700 | 1 | |a Kumar, Rajeev |e editor. | |
| 700 | 1 | |a Nyamasvisva, Tadiwa Elisha |e editor. | |
| 700 | 1 | |a Tiwari, Rajesh Kumar |e editor. | |
| 700 | 1 | |a Ya'akub, Noor Inayah Binti |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 9798369378830 |
| 830 | 0 | |a Advances in electronic government, digital divide, and regional development (AEGDDRD) book series. | |
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| author2 | Abdul Hamid, Abu Bakar 1967- Kumar, Rajeev Nyamasvisva, Tadiwa Elisha Tiwari, Rajesh Kumar Ya'akub, Noor Inayah Binti |
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| author_facet | Abdul Hamid, Abu Bakar 1967- Kumar, Rajeev Nyamasvisva, Tadiwa Elisha Tiwari, Rajesh Kumar Ya'akub, Noor Inayah Binti |
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| contents | Preface -- Chapter 1. Bridging E-Governance and Sustainability: Unveiling Synergies for a Sustainable Future -- Chapter 2. The Next Generation of Greentech Trends and Innovations Shaping Sustainable E-Governance -- Chapter 3. A Primer for Governance -- Chapter 4. Machine Learning for Traffic Management, Object Detection, and Collision Avoidance in Autonomous Driving for Smart City Governance -- Chapter 5. Cutting-Edge Deep Learning Approaches for Human Pose Estimation and Activity Recognition in Smart Cities -- Chapter 6. Approaches of Deep Learning Used in Cyber Security and Cyber-Crime -- Chapter 7. Cybersecurity Affected Social Life Using Online Transactions in India -- Chapter 8. Cyber-Physical Systems for Enhancement in Security While Using Cyber -- Chapter 9. Security of Linear Regression Models -- Chapter 10. Optimizing Image Encryption Efficiency Through Advanced Deep Learning Architectures and Techniques -- Chapter 11. Machine Learning for Healthcare Fraud Detection: A Comprehensive Review Literature -- Chapter 12. Impact of the COVID-19 Pandemic on Healthcare Fraud: A Comprehensive Literature Review -- Compilation of References -- About the Contributors -- Index. |
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| genre | Electronic books. |
| genre_facet | Electronic books. |
| id | ZDB-98-IGB-00349576 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-18T14:30:39Z |
| institution | BVB |
| isbn | 9798369378854 |
| language | English |
| oclc_num | 1479494569 |
| open_access_boolean | |
| owner | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| owner_facet | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| physical | 18 PDFs (356 Seiten) Also available in print. |
| psigel | ZDB-98-IGB FWS_PDA_IGB ZDB-98-IGB |
| publishDate | 2025 |
| publishDateSearch | 2025 |
| publishDateSort | 2025 |
| publisher | IGI Global |
| record_format | marc |
| series | Advances in electronic government, digital divide, and regional development (AEGDDRD) book series. |
| series2 | Advances in electronic government, digital divide, and regional development (AEGDDRD) book series |
| spelling | Leveraging futuristic machine learning and next-generational security for e-governance Rajeev Kumar, Abu Bakar Abdul Hamid, Noor Inayah Binti Ya'akub, Tadiwa Elisha Nyamasvisva, Rajesh Kumar Tiwari, editors. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global 2025. 18 PDFs (356 Seiten) text rdacontent electronic isbdmedia online resource rdacarrier Advances in electronic government, digital divide, and regional development (AEGDDRD) book series Includes bibliographical references and index. Preface -- Chapter 1. Bridging E-Governance and Sustainability: Unveiling Synergies for a Sustainable Future -- Chapter 2. The Next Generation of Greentech Trends and Innovations Shaping Sustainable E-Governance -- Chapter 3. A Primer for Governance -- Chapter 4. Machine Learning for Traffic Management, Object Detection, and Collision Avoidance in Autonomous Driving for Smart City Governance -- Chapter 5. Cutting-Edge Deep Learning Approaches for Human Pose Estimation and Activity Recognition in Smart Cities -- Chapter 6. Approaches of Deep Learning Used in Cyber Security and Cyber-Crime -- Chapter 7. Cybersecurity Affected Social Life Using Online Transactions in India -- Chapter 8. Cyber-Physical Systems for Enhancement in Security While Using Cyber -- Chapter 9. Security of Linear Regression Models -- Chapter 10. Optimizing Image Encryption Efficiency Through Advanced Deep Learning Architectures and Techniques -- Chapter 11. Machine Learning for Healthcare Fraud Detection: A Comprehensive Review Literature -- Chapter 12. Impact of the COVID-19 Pandemic on Healthcare Fraud: A Comprehensive Literature Review -- Compilation of References -- About the Contributors -- Index. Restricted to subscribers or individual electronic text purchasers. "In an era defined by rapid technological advancement and a pressing need for effective governance, the intersection of machine learning and cybersecurity has emerged as a pivotal area of exploration and innovation. E-governance serves as a vital framework for enhancing the delivery of public services, increasing governmental transparency, and fostering citizen engagement. However, as governments increasingly rely on digital infrastructures, they expose themselves to a myriad of cyber threats that can undermine public trust and security. The contemporary landscape of e-governance must not only adapt to the wave of new digital tools but also ensure the security and integrity of the data that underpins them. Leveraging Futuristic Machine Learning and Next-Generational Security for e-Governance brings together a comprehensive collection of insights and research from leading experts in the fields of artificial intelligence, cybersecurity, and public administration. The contributions to this volume encompass theoretical frameworks, case studies, and practical applications that showcase the transformative potential of integrating machine learning with next-generation security solutions. With this resource, researchers, practitioners, and academics can work toward a new age where e-governance thrives at the nexus of machine learning and cybersecurity."-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 12/09/2024). Computer security. Deep learning (Machine learning) Industrial applications. Activity Recognition. Blockchain. Cyber Crime. Cyber Physical System. Cyber Security. Deep Learning. Exogenous Determinants. Greentech Trends. Machine Learning. Object Detection. Online Transactions. Optimizing Image Encryption Efficiency. Skill Development. Smart Cities. Sustainable E-Governance. Electronic books. Abdul Hamid, Abu Bakar 1967- editor. Kumar, Rajeev editor. Nyamasvisva, Tadiwa Elisha editor. Tiwari, Rajesh Kumar editor. Ya'akub, Noor Inayah Binti editor. IGI Global, publisher. Print version: 9798369378830 Advances in electronic government, digital divide, and regional development (AEGDDRD) book series. |
| spellingShingle | Leveraging futuristic machine learning and next-generational security for e-governance Advances in electronic government, digital divide, and regional development (AEGDDRD) book series. Preface -- Chapter 1. Bridging E-Governance and Sustainability: Unveiling Synergies for a Sustainable Future -- Chapter 2. The Next Generation of Greentech Trends and Innovations Shaping Sustainable E-Governance -- Chapter 3. A Primer for Governance -- Chapter 4. Machine Learning for Traffic Management, Object Detection, and Collision Avoidance in Autonomous Driving for Smart City Governance -- Chapter 5. Cutting-Edge Deep Learning Approaches for Human Pose Estimation and Activity Recognition in Smart Cities -- Chapter 6. Approaches of Deep Learning Used in Cyber Security and Cyber-Crime -- Chapter 7. Cybersecurity Affected Social Life Using Online Transactions in India -- Chapter 8. Cyber-Physical Systems for Enhancement in Security While Using Cyber -- Chapter 9. Security of Linear Regression Models -- Chapter 10. Optimizing Image Encryption Efficiency Through Advanced Deep Learning Architectures and Techniques -- Chapter 11. Machine Learning for Healthcare Fraud Detection: A Comprehensive Review Literature -- Chapter 12. Impact of the COVID-19 Pandemic on Healthcare Fraud: A Comprehensive Literature Review -- Compilation of References -- About the Contributors -- Index. Computer security. Deep learning (Machine learning) Industrial applications. |
| title | Leveraging futuristic machine learning and next-generational security for e-governance |
| title_auth | Leveraging futuristic machine learning and next-generational security for e-governance |
| title_exact_search | Leveraging futuristic machine learning and next-generational security for e-governance |
| title_full | Leveraging futuristic machine learning and next-generational security for e-governance Rajeev Kumar, Abu Bakar Abdul Hamid, Noor Inayah Binti Ya'akub, Tadiwa Elisha Nyamasvisva, Rajesh Kumar Tiwari, editors. |
| title_fullStr | Leveraging futuristic machine learning and next-generational security for e-governance Rajeev Kumar, Abu Bakar Abdul Hamid, Noor Inayah Binti Ya'akub, Tadiwa Elisha Nyamasvisva, Rajesh Kumar Tiwari, editors. |
| title_full_unstemmed | Leveraging futuristic machine learning and next-generational security for e-governance Rajeev Kumar, Abu Bakar Abdul Hamid, Noor Inayah Binti Ya'akub, Tadiwa Elisha Nyamasvisva, Rajesh Kumar Tiwari, editors. |
| title_short | Leveraging futuristic machine learning and next-generational security for e-governance |
| title_sort | leveraging futuristic machine learning and next generational security for e governance |
| topic | Computer security. Deep learning (Machine learning) Industrial applications. |
| topic_facet | Computer security. Deep learning (Machine learning) Industrial applications. Electronic books. |
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