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  <titleInfo>
    <title>Information Security Theory and Practice</title>
    <subTitle>14th IFIP WG 11.2 International Conference, WISTP 2024, Paris, France, February 29 – March 1, 2024, Proceedings</subTitle>
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    <namePart>Bouzefrane, Samia.</namePart>
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    <namePart>Sauveron, Damien.</namePart>
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    <dateIssued encoding="marc">2024</dateIssued>
    <edition>1st ed. 2024.</edition>
    <issuance>monographic</issuance>
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    <extent>X, 195 p. 65 illus., 46 illus. in color. online resource.</extent>
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  <abstract>This volume constitutes the refereed proceedings of the 14th IFIP WG 11.2 International Conference on Information Security Theory and Practices, WISTP 2024, held in Paris, France. The 12 full papers presented were carefully reviewed and selected from 30 submissions. The papers presented in this proceedings focus on emerging trends in security and privacy, including experimental studies of fielded systems while exploring the application of security technology, and highlighting successful system implementations.</abstract>
  <tableOfContents> -- SPAWN: Seamless Proximity-based Authentication by Utilizing the Existent WiFi Environment.  -- MQfilTTr: Strengthening Smart Home Privacy through MQTT Traffic Manipulation.  -- Combining Cryptography and Discrete-Event Systems to Study Sensor and Actuator Cyberattacks.  -- Towards Interconnected Quantum Networks: A Requirements Analysis.  -- A similarity approach for the classification of mitigations in public cybersecurity repositories into NIST-SP 800-53 catalog.  -- Top Cyber Threats: The rise of Ransomware.  -- Enhancing security in Blockchain enabled IoT networks empowered with zk -SNARKs and Physically Unclonable Functions.  -- Security Challenges and Countermeasures in Blockchain's Peer-to-Peer Architecture.  -- A Bitcoin-based Digital Identity Model for the Internet of Things.  -- Towards a Time-dependent Approach for User Privacy Expression and Enforcement.  -- Privacy preserving Federated Learning : A novel approach for combining Differential Privacy and Homomorphic Encryption.  -- Distributed Backdoor Attacks in Federated Learning Generated by Dynamic Triggers.</tableOfContents>
  <note type="statement of responsibility">edited by Samia Bouzefrane, Damien Sauveron.</note>
  <subject authority="lcsh">
    <topic>Data protection</topic>
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  <subject authority="lcsh">
    <topic>Cryptography</topic>
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  <subject authority="lcsh">
    <topic>Data encryption (Computer science)</topic>
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  <subject authority="lcsh">
    <topic>Computer networks</topic>
    <topic>Security measures</topic>
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  <subject authority="lcsh">
    <topic>Computer networks </topic>
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  <subject authority="lcsh">
    <topic>Application software</topic>
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  <subject>
    <topic>Data and Information Security</topic>
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  <subject>
    <topic>Cryptology</topic>
  </subject>
  <subject>
    <topic>Mobile and Network Security</topic>
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  <subject>
    <topic>Computer Communication Networks</topic>
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  <subject>
    <topic>Computer and Information Systems Applications</topic>
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      <title>Lecture Notes in Computer Science, 14625</title>
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  <identifier type="isbn">9783031603914</identifier>
  <identifier type="uri">https://doi.org/10.1007/978-3-031-60391-4</identifier>
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