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Advanced Security Solutions for Multimedia
| Advanced Security Solutions for Multimedia |
| Autore | Ansari Irshad Ahmad |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Bristol : , : Institute of Physics Publishing, , 2021 |
| Descrizione fisica | 1 online resource (276 pages) |
| Altri autori (Persone) |
BajajVarun
SinhalRishi SharmaTarun Kumar NajafiEsmaeil ShahManan GohilJay PatelJay WuHanzhou AbazarMahdie |
| Collana | IOP Ebooks Series |
| Soggetto topico |
Data encryption (Computer science)
Digital watermarking |
| ISBN | 0-7503-4572-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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 -- 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.
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. 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 the patient's relatives -- 10.4.3 Benefit to the organization -- 10.5 Requirements for the service model. 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. 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. |
| Record Nr. | UNINA-9910915783003321 |
Ansari Irshad Ahmad
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| Bristol : , : Institute of Physics Publishing, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Intelligence in Cyber Security: Theories and Applications / / edited by Tushar Bhardwaj, Himanshu Upadhyay, Tarun Kumar Sharma, Steven Lawrence Fernandes
| Artificial Intelligence in Cyber Security: Theories and Applications / / edited by Tushar Bhardwaj, Himanshu Upadhyay, Tarun Kumar Sharma, Steven Lawrence Fernandes |
| Autore | Bhardwaj Tushar |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (144 pages) |
| Disciplina | 005.8 |
| Altri autori (Persone) |
UpadhyayHimanshu
SharmaTarun Kumar FernandesSteven Lawrence |
| Collana | Intelligent Systems Reference Library |
| Soggetto topico |
Computational intelligence
Engineering - Data processing Artificial intelligence Data protection Computational Intelligence Data Engineering Artificial Intelligence Data and Information Security |
| ISBN |
9783031285813
3031285816 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Comprehensive Review On Cloud Security Using Machine Learning Techniques -- Energy Enhanced Routing Protocol for Heterogeneous Networks using Artificial Intelligence -- Integration of Machine Learning with Cybersecurity: Applications and Challenges -- Deep Learning Approach for Detection of Fraudulent Credit Card Transactions. |
| Record Nr. | UNINA-9910747593203321 |
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Bhardwaj Tushar
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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