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020 _a9783031654947
_9978-3-031-65494-7
024 7 _a10.1007/978-3-031-65494-7
_2doi
050 4 _aQA76.9.A25
050 4 _aJC596-596.2
072 7 _aURD
_2bicssc
072 7 _aCOM060040
_2bisacsh
072 7 _aURD
_2thema
100 1 _aAdir, Allon.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987278
245 1 0 _aHomomorphic Encryption for Data Science (HE4DS)
_h[electronic resource] /
_cby Allon Adir, Ehud Aharoni, Nir Drucker, Ronen Levy, Hayim Shaul, Omri Soceanu.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXXI, 304 p. 93 illus., 90 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPart I Introduction and Basic Homomorphic Encryption (HE) Concepts -- Chapter 1 Introduction to Data Science -- Chapter 2 Modern Homomorphic Encryption - Introduction -- Chapter 3 Modern HE - Security Models -- Chapter 4 Approaches for Writing HE Applications -- Part II Approximations -- Chapter 5 Approximation Methods Part I: A General Overview -- Chapter 6 Approximation Methods Part II: Approximations of Standard Functions -- Part III Packing Methods -- Chapter 7 SIMD Packing Part I: Basic Packing Techniques -- Chapter 8 SIMD Packing Part II – Tile Tensor Basics -- Chapter 9 SIMD Packing Part III: Advanced Tile Tensors -- Part IV Use Cases and Other Approaches -- Chapter 10 Privacy-Preserving Machine Learning with HE -- Chapter 11 Case Study: Neural Network.
520 _aThis book provides basic knowledge required by an application developer to understand and use the Fully Homomorphic Encryption (FHE) technology for privacy preserving Data-Science applications. The authors present various techniques to leverage the unique features of FHE and to overcome its characteristic limitations. Specifically, this book summarizes polynomial approximation techniques used by FHE applications and various data packing schemes based on a data structure called tile tensors, and demonstrates how to use the studied techniques in several specific privacy preserving applications. Examples and exercises are also included throughout this book. The proliferation of practical FHE technology has triggered a wide interest in the field and a common wish to experience and understand it. This book aims to simplify the FHE world for those who are interested in privacy preserving data science tasks, and for an audience that does not necessarily have a deep cryptographic background, including undergraduate and graduate-level students in computer science, and data scientists who plan to work on private data and models.
650 0 _aData protection
_xLaw and legislation.
_966490
650 0 _aCryptography.
_964299
650 0 _aData encryption (Computer science).
_958243
650 0 _aMachine learning.
_955059
650 0 _aComputer networks
_xSecurity measures.
_963949
650 1 4 _aPrivacy.
_966493
650 2 4 _aCryptology.
_966491
650 2 4 _aMachine Learning.
_955059
650 2 4 _aMobile and Network Security.
_966379
700 1 _aAharoni, Ehud.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987279
700 1 _aDrucker, Nir.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987280
700 1 _aLevy, Ronen.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987281
700 1 _aShaul, Hayim.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987282
700 1 _aSoceanu, Omri.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987283
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031654930
776 0 8 _iPrinted edition:
_z9783031654954
776 0 8 _iPrinted edition:
_z9783031654961
856 4 0 _uhttps://doi.org/10.1007/978-3-031-65494-7
912 _aZDB-2-CWD
912 _aZDB-2-SXPC
999 _c64839
_d64839