000			a
999			_c34017 _d34017
008			250606b xxu||||| |||| 00| 0 eng d
020			_a9783031654930 _c(hbk)
082			_a005.8 _bADI
100			_aAdir, Allon
245			_aHomomorphic encryption for data science (HE4DS)
260			_bspringer, _c2024 _aCham :
300			_axxi, 304 p. ; _bill., (some col.), _c25 cm
365			_b74.99 _c€ _d100.40
504			_aIncludes bibliographical references and index.
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			_aData encryption
650			_aComputer science
700			_aAharoni, Ehud
700			_aDrucker, Nir
700			_aLevy, Ronen
700			_aShaul, Hayim
700			_aSoceanu, Omri
942			_2ddc _cBK