LEADER 01751oam 2200421 a 450 001 9910697290003321 005 20230902162107.0 035 $a(CKB)5470000002386018 035 $a(OCoLC)649930569 035 $a(OCoLC)995470000002386018 035 $a(EXLCZ)995470000002386018 100 $a20100724d2010 ua 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIndicators of streamflow alteration, habitat fragmentation, impervious cover, and water quality for Massachusetts stream basins$b[electronic resource] /$fby Peter A. Weiskle ... [and others] ; prepared in cooperation with the Massachusetts Department of Conservation and Recreation 210 1$aReston, Va. :$cU.S. Dept. of the Interior, U.S. Geological Survey,$d2010. 215 $a1 online resource (x, 70 pages) $ccolor maps$eusers guide (6 pages) 225 1 $aScientific investigations report ;$v2006-5272 300 $aTitle from PDF title screen (viewed on July 25, 2010). 320 $aIncludes bibliographical references (pages 65-67). 410 0$aScientific investigations report ;$v2006-5272. 606 $aStream health$zMassachusetts 606 $aRivers$zMassachusetts 615 0$aStream health 615 0$aRivers 700 $aWeiskel$b Peter K$01401116 712 02$aMassachusetts.$bDepartment of Conservation and Recreation. 712 02$aGeological Survey (U.S.) 801 0$bGPO 801 1$bGPO 801 2$bGPO 906 $aBOOK 912 $a9910697290003321 996 $aIndicators of streamflow alteration, habitat fragmentation, impervious cover, and water quality for Massachusetts stream basins$93542098 997 $aUNINA LEADER 04671nam 22005895 450 001 996546841303316 005 20230711162349.0 010 $a3-031-34006-X 024 7 $a10.1007/978-3-031-34006-2 035 $a(CKB)27559408700041 035 $a(MiAaPQ)EBC30627421 035 $a(Au-PeEL)EBL30627421 035 $a(DE-He213)978-3-031-34006-2 035 $a(PPN)272257184 035 $a(EXLCZ)9927559408700041 100 $a20230711d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Protection in a Post-Pandemic Society$b[electronic resource] $eLaws, Regulations, Best Practices and Recent Solutions /$fedited by Chaminda Hewage, Yogachandran Rahulamathavan, Deepthi Ratnayake 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (246 pages) 311 $a9783031340055 327 $aChapter. 1. Post-Covid-19 Metaverse Cybersecurity and Data Privacy-Present and Future Challenges -- Chapter. 2. Keeping it Low-Key: Modern-day approaches to Privacy-Preserving Machine Learning -- Chapter. 3. Security Analysis of Android Hot Cryptocurrency Wallet Applications -- Chapter. 4. Exploring the Opportunities of Applying Digital Twins for Intrusion Detection in Industrial Control Systems of Production and Manufacturing ? A Systematic Review -- Chapter. 5. Securing Privacy During a World Health Emergency: Exploring How to Create a Balance Between the Need to Save the World and People?s Right to Privacy -- Chapter. 6. Federated Learning: Data privacy and cyber security in edge-based machine learning Mobile Malware Detection Using Consortium -- Chapter. 7. Emerging Computer Security Laws and Regulations across the Globe: A Comparison between Sri Lankan and Contemporary International Computer Acts -- Chapter. 8. Legal Considerations and Ethical Challenges of Artificial Intelligence on Internet of Things and Smart Cities. 330 $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. . 606 $aData protection?Law and legislation 606 $aData protection 606 $aFinancial risk management 606 $aPrivacy 606 $aData and Information Security 606 $aRisk Management 615 0$aData protection?Law and legislation. 615 0$aData protection. 615 0$aFinancial risk management. 615 14$aPrivacy. 615 24$aData and Information Security. 615 24$aRisk Management. 676 $a005.8 676 $a323.448 700 $aHewage$b Chaminda$01373670 701 $aRahulamathavan$b Yogachandran$01373671 701 $aRatnayake$b Deepthi$01373672 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996546841303316 996 $aData Protection in a Post-Pandemic Society$93404750 997 $aUNISA