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Böcker av Lingyu Wang

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  • av Lingyu Wang
    2 100,-

    Digital forensics deals with the investigation of cybercrimes. With the growing deployment of cloud computing, mobile computing, and digital banking on the internet, the nature of digital forensics has evolved in recent years, and will continue to do so in the near future.This book presents state-of-the-art techniques to address imminent challenges in digital forensics. In particular, it focuses on cloud forensics, Internet-of-Things (IoT) forensics, and network forensics, elaborating on innovative techniques, including algorithms, implementation details and performance analysis, to demonstrate their practicality and efficacy. The innovations presented in this volume are designed to help various stakeholders with the state-of-the-art digital forensics techniques to understand the real world problems. Lastly, the book will answer the following questions: How do the innovations in digital forensics evolve with the emerging technologies? What are the newest challenges in the field of digital forensics?

  • - Application to Malicious Code Fingerprinting
    av Lingyu Wang, Djedjiga Mouheb, Mourad Debbabi, m.fl.
    1 870,-

    This book addresses automated software fingerprinting in binary code, especially for cybersecurity applications.

  • av Lingyu Wang, Mourad Debbabi, Makan Pourzandi, m.fl.
    1 210 - 1 606,-

    This book provides a comprehensive review of the most up to date research related to cloud security auditing and discusses auditing the cloud infrastructure from the structural point of view, while focusing on virtualization-related security properties and consistency between multiple control layers.

  • av Lingyu Wang, Sushil Jajodia & Anoop Singhal
    1 376 - 1 876,-

  • - From Data Publishing to Web Applications
    av Lingyu Wang & Wen Ming Liu
    1 556,-

    This book offers a novel approach to data privacy by unifying side-channel attacks within a general conceptual framework. Next, the book explores privacy-preserving traffic padding in Web applications, first via a model to quantify privacy and cost and then by introducing randomness to provide background knowledge-resistant privacy guarantee.

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