Leveraging Futuristic Machine Learning and Next-generational Security for E-governance - Rilegato

Rilegato

ISBN 13: 9798369378830

Casa editrice: Information Science Reference, 2024

Riassunto

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.

Dettagli dell'edizione

• Editore: Information Science Reference
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 13: 9798369378830
• Rilegatura: Copertina rigida
• Numero di pagine: 356
• Redattore: Kumar Rajeev, Hamid Abu Bakar Abdul, Yaakub Noor Inayah Binti, Nyamasvisva Tadiwa Elisha, Tiwari Rajesh Kumar
• Contatto del produttore: non disponibile
• Persona responsabile: gpsr@libri.de; gpsr@libri.de; ; Friedensallee 273; Hamburg; 22763; Germania