000 04218nam a22006495i 4500
001 978-981-99-9614-8
003 DE-He213
005 20240423130304.0
007 cr nn 008mamaa
008 240103s2024 si | s |||| 0|eng d
020 _a9789819996148
_9978-981-99-9614-8
024 7 _a10.1007/978-981-99-9614-8
_2doi
050 4 _aTK7885-7895
050 4 _aTK5105.5-5105.9
072 7 _aUK
_2bicssc
072 7 _aCOM067000
_2bisacsh
072 7 _aUK
_2thema
082 0 4 _a621.39
_223
082 0 4 _a004.6
_223
245 1 0 _aEmerging Information Security and Applications
_h[electronic resource] :
_b4th International Conference, EISA 2023, Hangzhou, China, December 6–7, 2023, Proceedings /
_cedited by Jun Shao, Sokratis K. Katsikas, Weizhi Meng.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXII, 185 p. 48 illus., 35 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 _aCommunications in Computer and Information Science,
_x1865-0937 ;
_v2004
505 0 _aPtbStolen: Pre-trained Encoder Stealing Through Perturbed Samples -- Towards Efficient Universal Adversarial Attack on Audio Classification Models: A Two-step Method -- Privacy-Preserving Authenticated Federated Learning Scheme for Smart Healthcare System -- A Systematic Method for Constructing ICT Supply Chain Security Requirements -- Pairing Compression on Some Elliptic Curves with Subgroups of Embedding Degree 6 and its Applications to Pairing-based Cryptography -- Enhancing Chinese Named Entity Recognition with Disentangled Expert Knowledge -- Deep Neural Network Model over Encrypted Data -- Privacy Protection Mechanism for Fair Federated Learning -- Chinese Named Entity Recognition within the Electric Power Domain -- Adversarial Sampling Attacks and Defense in DNS Data Exfiltration -- CONNECTION: COvert chaNnel NEtwork attaCk Through bIt-rate mOdulatioN.
520 _aThis volume constitutes the proceedings presented at the 4th International Conference on Emerging Information Security and Applications, EISA 2023, held in Hangzhou, China, in December 2023. The 11 full papers presented in this volume were thoroughly reviewed and selected from the 35 submissions. The topics of the book are related but not limited to cyber intelligence techniques, multimedia security, blockchain and distributed ledger technology, malware and unwanted software, vulnerability analysis and reverse engineering, usable security and privacy, intrusion detection and prevention, authentication and access control, anonymity and privacy, cryptographic protection, digital forensics, cyber physical systems security, adversarial learning, security measurement, security management and policies, hardware and physical security.
650 0 _aComputer engineering.
650 0 _aComputer networks .
650 0 _aCryptography.
650 0 _aData encryption (Computer science).
650 0 _aArtificial intelligence.
650 0 _aData protection.
650 0 _aComputer networks
_xSecurity measures.
650 1 4 _aComputer Engineering and Networks.
650 2 4 _aCryptology.
650 2 4 _aArtificial Intelligence.
650 2 4 _aData and Information Security.
650 2 4 _aMobile and Network Security.
700 1 _aShao, Jun.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aKatsikas, Sokratis K.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aMeng, Weizhi.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819996131
776 0 8 _iPrinted edition:
_z9789819996155
830 0 _aCommunications in Computer and Information Science,
_x1865-0937 ;
_v2004
856 4 0 _uhttps://doi.org/10.1007/978-981-99-9614-8
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c187031
_d187031