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[null,"1.","Record Nr.",null,"UNINA9910915783003321"]
[null,null,"Autore",null,"Ansari Irshad Ahmad"]
[null,null,"Titolo",null,"Advanced Security Solutions for Multimedia"]
[null,null,"Pubbl/distr/stampa",null,"Bristol : , : Institute of Physics Publishing, , 2021"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"0-7503-4572-1"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (276 pages)"]
[null,null,"Collana",null,"IOP Ebooks Series"]
[null,null,"Soggetti",null,"Data encryption (Computer science)"]
[{"$nulls":4},"Digital watermarking"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Acknowledgements -- Editor biographies -- Irshad Ahmad Ansari -- Varun Bajaj -- Contributor biographies -- Mahdie Abazar -- Parmeshwar Birajadar -- Seyed Mostafa FakhrAhmad -- Vikram M Gadre -- Ali Ghorbani -- Jay Gohil -- Abdelhamid Helali -- Sunil Kumar Jauhar -- Ameya Kshirsagar -- S Kuppa -- Hassen Maaref -- V M Manikandan -- Suja Cherukullapurath Mana -- Peyman Masjedi -- Ridha Mghaieth -- Amina Msolli -- Esmaeil Najafi -- Akash S Palde -- Jay Patel -- D S Raghukumar -- Vishal Rajput -- Antti Rissanen -- Marjo Rissanen -- T Saipraba -- Sagar G Sangodkar -- Manan Shah -- Tarun Kumar Sharma -- Rishi Sinhal -- M Suresha -- Niranjan Suthar -- Mohammad Taheri -- Hanzhou Wu -- Chapter 1 Blind image watermarking with efficient dual restoration feature -- 1.1 Introduction -- 1.2 Literature review -- 1.3 Proposed fragile watermarking scheme -- 1.3.1 Watermark pre-processing -- 1.3.2 Watermark embedding -- 1.3.3 Watermark extraction -- 1.3.4 Self-recovery process -- 1.4 Experimental results and discussion -- 1.4.1 Tamper detection anaylsis -- 1.4.2 Self-recovery of the tampered portion -- 1.5 Conclusion -- Acknowledgements -- References -- Chapter 2 Secure, robust and imperceptible image watermarking scheme based on sharp frequency localized contourlet transform -- 2.1 Introduction -- 2.2 The properties of SFLCT -- 2.3 The proposed SFLCT watermarking scheme -- 2.3.1 Computing strength factors -- 2.4 Implementations and results of the proposed SFLCT scheme -- 2.4.1 Robustness of the proposed SFLCT scheme -- 2.4.2 The security examination of the proposed scheme -- 2.5 Comparative analysis of the proposed scheme "]
[{"$nulls":4},"-- 2.6 Conclusion -- References -- Chapter 3 Content watermarking and data hiding in multimedia security -- 3.1 Introduction -- 3.2 Content watermarking in multimedia security -- 3.2.1 Introduction."]
[{"$nulls":4},"3.2.2 Content watermarking technique reviews -- 3.2.3 Table pertaining to research work on content watermarking in multimedia security -- 3.2.4 Inference -- 3.3 Data hiding in multimedia security -- 3.3.1 Background -- 3.3.2 Data hiding technique reviews -- 3.3.3 Table pertaining to research work on data hiding in multimedia security -- 3.3.4 Inference -- 3.4 Conclusion -- Acknowledgments -- References -- Chapter 4 Recent advances in reversible watermarking in an encrypted domain -- 4.1 Introduction -- 4.2 Preliminaries -- 4.2.1 Cover source and formats -- 4.2.2 Encryption methods -- 4.2.3 Evaluation metrics -- 4.2.4 Auxiliary data -- 4.3 State-of-the-art methods -- 4.3.1 General framework -- 4.3.2 Reserving room after encryption -- 4.3.3 Reserving room before encryption -- 4.3.4 Challenges and opportunities -- 4.4 Conclusion -- Acknowledgements -- References -- Chapter 5 An analysis of deep steganography and steganalysis -- 5.1 Introduction -- 5.2 Deep learning -- 5.2.1 Steganalysis -- 5.2.2 Steganography -- 5.3 Conclusion -- References -- Chapter 6 Recent trends in reversible data hiding techniques -- 6.1 Introduction -- 6.2 Types of RDH schemes -- 6.2.1 RDH in natural images -- 6.2.2 RDH in encrypted images -- 6.2.3 RDH through encryption (RDHTE) -- 6.3 Analysis of RDH schemes -- 6.4 Image dataset for experimental study -- 6.5 Future scope of the research in RDH -- 6.6 Conclusion -- References -- Chapter 7 Anatomized study of security solutions for multimedia: deep learning-enabled authentication, cryptography and information hiding -- 7.1 Introduction -- 7.2 Hurdles in conventional approaches for security -- 7.2.1 Vulnerability due to expansion -- 7.2.2 Authentication and computational latency -- 7.2.3 Discrepancy in authentication -- 7.3 Vulnerability to multimedia content -- 7.3.1 Data disclosure -- 7.3.2 Content manipulation."]
[{"$nulls":4},"7.3.3 Link sharing -- 7.3.4 Steganography -- 7.3.5 Common workspace -- 7.4 Analysis of security solutions for multimedia content -- 7.4.1 Cryptography -- 7.4.2 Data hiding -- 7.4.3 Deep learning enabled authentication -- 7.5 Future scope -- 7.6 Conclusion -- Acknowledgements -- References -- Chapter 8 New lightweight image encryption algorithm for the Internet of Things and wireless multimedia sensor networks -- 8.1 Introduction -- 8.2 Cryptographic primitives -- 8.2.1 Cryptanalysis -- 8.2.2 Cryptography system -- 8.3 Proposed lightweight algorithm -- 8.4 Safety assessment -- 8.4.1 Statistical analysis -- 8.4.2 Sensitivity test: robustness against differential attacks -- 8.4.3 Calculations speed analysis -- 8.5 Conclusion -- References -- Chapter 9 Applying the capabilities of machine learning for multimedia security: an analysis -- 9.1 Introduction -- 9.2 Overview of machine learning -- 9.2.1 Classification -- 9.2.2 Regression -- 9.2.3 Deep learning -- 9.3 Machine learning algorithms for multimedia security -- 9.4 Advantages of using ML based security mechanism for multimedia -- 9.5 Conclusion -- References -- Chapter 10 Assistive communication technology options for elderly care -- 10.1 Introduction -- 10.2 Cameras for patient monitoring in hospitals -- 10.2.1 Cameras for patient supervising in elderly care -- 10.2.2 Extending camera monitoring from the hospital to the home -- 10.2.3 Home-access video service as experienced by family members -- 10.2.4 Home-access video service as experienced by staff -- 10.2.5 New contexts and possibilities for camera surveillance in elderly care -- 10.3 Home-access monitoring and security -- 10.4 Benefits of the service -- 10.4.1 Benefit for the hospital patient -- 10.4.2 Benefit to "]
[{"$nulls":4},"the patient's relatives -- 10.4.3 Benefit to the organization -- 10.5 Requirements for the service model."]
[{"$nulls":4},"10.5.1 When is a home-access camera a facet of quality? -- 10.5.2 Conditions for practice -- 10.6 Security issues in networked health infrastructure -- 10.6.1 Information security at the strategic level -- 10.6.2 Different layers of security -- 10.6.3 Key elements of safe IT infrastructure in healthcare in the future -- 10.7 Deploying novel surveillance services in healthcare -- 10.7.1 Underlining the basics -- 10.7.2 Design cycles and relevant frames for design -- 10.7.3 Shared leadership -- 10.7.4 Challenges of innovation adaptation -- 10.7.5 New service models and translational design challenges -- 10.8 Conclusion -- References -- Chapter 11 Deep learning approach for scenario-based abnormality detection -- 11.1 Introduction -- 11.2 Literature study -- 11.3 Scenario understanding -- 11.3.1 Key frame extraction using instance segmentation -- 11.3.2 State full artifacts modelling -- 11.3.3 Action recognition and attention of key action -- 11.3.4 A hybrid model for spatio-temporal features -- 11.3.5 Classification and captioning -- 11.4 Abnormality detection -- 11.4.1 Natural abnormality translation -- 11.5 Datasets -- 11.6 Challenges -- 11.7 Trends and strengths -- 11.8 Conclusion -- References -- Chapter 12 Ear recognition for multimedia security -- 12.1 Introduction -- 12.1.1 Components of a biometric system -- 12.1.2 Modes of operation -- 12.1.3 Performance evaluation metrics -- 12.2 Ear recognition -- 12.3 Ear detection -- 12.4 Ear feature extraction -- 12.4.1 Multiresolution technique for feature extraction -- 12.4.2 Deep learning technique for feature extraction -- 12.4.3 Identification and verification experiments -- 12.5 Conclusion -- Acknowledgements -- References -- Chapter 13 Secure multimedia management: currents trends and future avenues -- 13.1 Introduction -- 13.2 Data collection and screening -- 13.3 Results."]
[{"$nulls":4},"13.3.1 General performance of selected publications -- 13.3.2 Performance of countries, institutions, and authors -- 13.3.3 Performance of journals, citations, and keywords -- 13.3.4 Factorial analysis -- 13.3.5 Co-citation network -- 13.3.6 Collaboration worldwide -- 13.4 Conclusion -- References."]
[null,null,null,"Sommario/riassunto","This book is particularly suited for those that bridge the academic world and industry, allowing readers to understand the security concerns in the multimedia domain by reviewing present and evolving security solutions, including machine learning applications, their limitations, and future research directions."]