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001471677 001__ 1471677
001471677 003__ OCoLC
001471677 005__ 20230908003309.0
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001471677 008__ 230714s2023\\\\sz\\\\\\ob\\\\000\0\eng\d
001471677 019__ $$a1390557906$$a1394922975
001471677 020__ $$a9783031340062$$qelectronic book
001471677 020__ $$a303134006X$$qelectronic book
001471677 020__ $$z3031340051
001471677 020__ $$z9783031340055
001471677 0247_ $$a10.1007/978-3-031-34006-2$$2doi
001471677 035__ $$aSP(OCoLC)1390187750
001471677 040__ $$aYDX$$beng$$erda$$cYDX$$dGW5XE$$dEBLCP$$dN$T$$dYDX
001471677 049__ $$aISEA
001471677 050_4 $$aK3264.C65$$bD38 2023
001471677 08204 $$a342.0858$$223/eng/20230724
001471677 24500 $$aData protection in a post-pandemic society :$$blaw regulations, best practices and recent solutions /$$cChaminda Hewage, Yogachandran Rahulamathavan, Deepthi Ratnayake, editors.
001471677 264_1 $$aCham, Switzerland  :$$bSpringer,$$c[2023]
001471677 300__ $$a1 online resource
001471677 336__ $$atext$$btxt$$2rdacontent
001471677 337__ $$acomputer$$bc$$2rdamedia
001471677 338__ $$aonline resource$$bcr$$2rdacarrier
001471677 504__ $$aIncludes bibliographical references.
001471677 5050_ $$aIntro -- Preface -- Contents -- About the Editors -- Post-Covid-19 Metaverse Cybersecurity and Data Privacy: Present and Future Challenges -- 1 Introduction -- 2 Previous Work -- 3 Research Challenges -- Cybersecurity -- Avatar Integrity -- Device Security -- Data Privacy -- Data Collection -- User Consent -- Direct Marketing -- Data Intermediaries -- Health -- Content Moderation -- Children -- User Education -- Economy -- Ownership -- Advertising -- Portability and Interoperability -- Transparency and Accountability: AI -- Laws and Regulation Landscape
001471677 5058_ $$aEU/UK General Data Protection Regulations -- Confidentiality -- Responsibility and Liability -- EU Digital Services Act -- Consistency -- Systematisation -- Consumers Vs Traders -- Transparency -- UK Online Safety Bill -- Big Tech Companies -- UK Two-Tier System: Liability -- Publishers -- Online Intermediaries -- Legal Clarity -- Discussion and Summary -- 4 Future Research Directions and Potential Solutions for Cybersecurity -- Avatar Integrity -- Security Protocols -- Cyber-Resilience -- Data Privacy -- Data Collection -- Metaverse: Open and Decentralised -- Data Protection Framework -- Health
001471677 5058_ $$aContent Moderation -- Children -- User Education -- Economy -- Ownership -- Advertising -- Data Portability and Interoperability -- Transparency and Accountability: Blockchain -- Laws and Regulation Landscape -- EU/UK General Data Protection Regulations -- Confidentiality -- Responsibility and Liability -- EU Digital Services Act -- Consistency -- Systematisation -- Consumer Vs Trader -- Transparency -- UK Online Safety Bill -- Big Tech Companies -- UK Two-Tier System: Liability -- Publishers -- Online Intermediaries -- Legal Clarity -- 5 Discussion -- 6 Conclusion -- Recommendations
001471677 5058_ $$aPolicy and Notification -- VDaaS: Notification, Consent, Policies, and Records System Update -- Data Provenance and Integrity -- Data Veracity and User Safety -- Cybersecurity -- AI Training Data -- Data Privacy -- Due Diligence and Best Practices -- Avatars -- User Consent and Age Verification -- Tokenization-Validation -- Limitations -- Conflict of Interest -- References -- Keeping it Low-Key: Modern-Day Approaches to Privacy-Preserving Machine Learning -- 1 Introduction -- 2 The Great Privacy Awakening -- 3 Attacks on ML Systems -- Data Access Attack -- Membership Inference Attack
001471677 5058_ $$aInput Inference Attack -- Parameter Inference Attack -- Property Inference Attack -- 4 Quantifying Privacy Risks in ML Systems -- Membership Inference -- Input Inference -- Parameter Inference -- Property Inference -- 5 Privacy-Preserving Machine Learning -- 6 Privacy-Preserving Techniques -- Differential Privacy -- Federated Learning -- Synthetic Data -- Data Condensation -- Auxiliary Techniques -- 7 Privacy and Responsible ML -- 8 Conclusion -- References -- Security Analysis of Android Hot Cryptocurrency Wallet Applications -- 1 Introduction -- Background/Context -- Research Focus and Purpose
001471677 506__ $$aAccess limited to authorized users.
001471677 520__ $$aThis book offers the latest research results and predictions in data protection with a special focus on post-pandemic society. This book also includes various case studies and applications on data protection. It includes the Internet of Things (IoT), smart cities, federated learning, Metaverse, cryptography and cybersecurity. Data protection has burst onto the computer security scene due to the increased interest in securing personal data. Data protection is a key aspect of information security where personal and business data need to be protected from unauthorized access and modification. The stolen personal information has been used for many purposes such as ransom, bullying and identity theft. Due to the wider usage of the Internet and social media applications, people make themselves vulnerable by sharing personal data. This book discusses the challenges associated with personal data protection prior, during and post COVID-19 pandemic. Some of these challenges are caused by the technological advancements (e.g., Artificial Intelligence (AI)/Machine Learning (ML) and ChatGPT). In order to preserve the privacy of the data involved, there are novel techniques such as zero knowledge proof, fully homomorphic encryption, multi-party computations are being deployed. The tension between data privacy and data utility drive innovation in this area where numerous start-ups around the world have started receiving funding from government agencies and venture capitalists. This fuels the adoption of privacy-preserving data computation techniques in real application and the field is rapidly evolving. Researchers and students studying/working in data protection and related security fields will find this book useful as a reference. .
001471677 588__ $$aDescription based on online resource; title from digital title page (viewed on August 18, 2023).
001471677 650_0 $$aData protection$$xLaw and legislation.
001471677 650_0 $$aData protection$$xGovernment policy.
001471677 650_0 $$aCOVID-19 Pandemic, 2020-$$xInfluence.
001471677 655_0 $$aElectronic books.
001471677 7001_ $$aHewage, Chaminda.
001471677 7001_ $$aRahulamathavan, Yogachandran.
001471677 7001_ $$aRatnayake, Deepthi.
001471677 77608 $$iPrint version:$$z3031340051$$z9783031340055$$w(OCoLC)1377655442
001471677 852__ $$bebk
001471677 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-34006-2$$zOnline Access$$91397441.1
001471677 909CO $$ooai:library.usi.edu:1471677$$pGLOBAL_SET
001471677 980__ $$aBIB
001471677 980__ $$aEBOOK
001471677 982__ $$aEbook
001471677 983__ $$aOnline
001471677 994__ $$a92$$bISE