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020 _a9783031121647
_9978-3-031-12164-7
024 7 _a10.1007/978-3-031-12164-7
_2doi
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_2bicssc
072 7 _aURY
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072 7 _aCOM083000
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_2thema
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082 0 4 _a005.824
_223
100 1 _aChoudhury, Ashish.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_978909
245 1 0 _aSecure Multi-Party Computation Against Passive Adversaries
_h[electronic resource] /
_cby Ashish Choudhury, Arpita Patra.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aXIII, 231 p. 85 illus., 50 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Distributed Computing Theory,
_x2155-1634
505 0 _aIntroduction -- Relevant Topics from Abstract Algebra -- Secret Sharing -- A Toy MPC Protocol -- The BGW Perfectly-Secure MPC Protocol for Linear Functions -- The BGW Perfectly-Secure MPC Protocol for Any Arbitrary Function -- Perfectly-Secure MPC in the Pre-Processing Model -- Perfectly-Secure MPC Tolerating General Adversaries -- Perfectly-Secure MPC for Small Number of parties -- The GMW MPC Protocol -- Oblivious Transfer.
520 _aThis book focuses on multi-party computation (MPC) protocols in the passive corruption model (also known as the semi-honest or honest-but-curious model). The authors present seminal possibility and feasibility results in this model and includes formal security proofs. Even though the passive corruption model may seem very weak, achieving security against such a benign form of adversary turns out to be non-trivial and demands sophisticated and highly advanced techniques. MPC is a fundamental concept, both in cryptography as well as distributed computing. On a very high level, an MPC protocol allows a set of mutually-distrusting parties with their private inputs to jointly and securely perform any computation on their inputs. Examples of such computation include, but not limited to, privacy-preserving data mining; secure e-auction; private set-intersection; and privacy-preserving machine learning. MPC protocols emulate the role of an imaginary, centralized trusted third party (TTP) that collects the inputs of the parties, performs the desired computation, and publishes the result. Due to its powerful abstraction, the MPC problem has been widely studied over the last four decades. In addition, this book: Includes detailed security proofs for seminal protocols and state-of-theart efficiency improvement techniques Presents protocols against computationally bounded as well as computationally unbounded adversaries Focuses on MPC protocols in the passive corruption model, presents seminal possibility and feasibility results, and features companion video lectures.
650 0 _aCryptography.
_91973
650 0 _aData encryption (Computer science).
_99168
650 0 _aData protection.
_97245
650 0 _aData protection
_xLaw and legislation.
_923450
650 0 _aComputer security.
_93970
650 0 _aComputer networks
_xSecurity measures.
_93969
650 1 4 _aCryptology.
_931769
650 2 4 _aSecurity Services.
_978910
650 2 4 _aData and Information Security.
_931990
650 2 4 _aPrivacy.
_935098
650 2 4 _aPrinciples and Models of Security.
_978911
650 2 4 _aMobile and Network Security.
_933624
700 1 _aPatra, Arpita.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_978912
710 2 _aSpringerLink (Online service)
_978913
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031121630
776 0 8 _iPrinted edition:
_z9783031121654
776 0 8 _iPrinted edition:
_z9783031121661
830 0 _aSynthesis Lectures on Distributed Computing Theory,
_x2155-1634
_978914
856 4 0 _uhttps://doi.org/10.1007/978-3-031-12164-7
912 _aZDB-2-SXSC
942 _cEBK
999 _c84680
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