Data, Engineering and Applications : Volume 2 / / edited by Rajesh Kumar Shukla, Jitendra Agrawal, Sanjeev Sharma, Geetam Singh Tomer

• Pubblicazione: Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019
• Edizione: 1st ed. 2019.
• Descrizione fisica: 1 online resource (X, 343 p. 166 illus., 103 illus. in color.)
• Disciplina: 005.7
• Soggetto topico: Big data; Data mining; Artificial intelligence; Big Data; Data Mining and Knowledge Discovery; Artificial Intelligence
• Persona (resp. second.): ShuklaRajesh Kumar; AgrawalJitendra; SharmaSanjeev (Information technology executive); Singh TomerGeetam
• Nota di contenuto: Efficient Map-Reduce Framework Using Summation -- Secret image sharing over cloud using one dimensional chaotic map -- Design and Development of a Cloud-based Electronic Medical Records (EMR) System -- Implementation of a secure Cloud computing authentication using Elliptic curve Cryptography -- Log-based Approach for Security Implementation in Cloud CRM’s -- Performance Analysis of Scheduling Algorithms in Apache Hadoop -- Energy Aware Prediction Based Load Balancing Approach with VM Migration for the Cloud Environment -- Authentication Process using Secure Sum for a New Node in Mobile Ad Hoc Network -- Certificate Revocation in Hybrid Ad-hoc Network -- NB tree based Intrusion detection technique using Rough set theory model -- An Energy Efficient Intrusion Detection System For Manet -- DDoS Attack Mitigation using Random and Flow Based Scheme -- Digital Image Watermarking Against Geometrical Attack -- Efficient key Management Approach for Vehicular Ad-hoc Network -- Image Forgery Detection: Survey and Future directions -- Comparative Study of Digital Forensic Tools -- A Systematic Survey on Mobile Forensic tools used for Forensic Analysis of Android based Social Networking Applications -- Enhanced and Secure Acknowledgement IDS in Mobile Adhoc Network by Hybrid Cryptography Technique -- Formal Verification of Causal Order Based Load Distribution Mechanism Using Event-B.
• Sommario/riassunto: This book presents a compilation of current trends, technologies, and challenges in connection with Big Data. Many fields of science and engineering are data-driven, or generate huge amounts of data that are ripe for the picking. There are now more sources of data than ever before, and more means of capturing data. At the same time, the sheer volume and complexity of the data have sparked new developments, where many Big Data problems require new solutions. Given its scope, the book offers a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of Big Data applications.
• Titolo autorizzato: Data, Engineering and Applications
• ISBN: 981-13-6351-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910350230103321
• Lo trovi qui: Univ. Federico II