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ویرایش: نویسندگان: Erol Gelenbe (editor), Marija Jankovic (editor), Dionysios Kehagias (editor), Anna Marton (editor), Andras Vilmos (editor) سری: ISBN (شابک) : 3031093569, 9783031093562 ناشر: Springer سال نشر: 2022 تعداد صفحات: 145 زبان: English فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 11 مگابایت
در صورت تبدیل فایل کتاب Security in Computer and Information Sciences: Second International Symposium, EuroCybersec 2021, Nice, France, October 25–26, 2021, Revised Selected ... in Computer and Information Science) به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب امنیت در علوم کامپیوتر و اطلاعات: دومین سمپوزیوم بین المللی، EuroCybersec 2021، نیس، فرانسه، 25 تا 26 اکتبر 2021، منتخب اصلاح شده ... در علوم کامپیوتر و اطلاعات) نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
Preface Organization Contents AI and Quality of Service Driven Attack Detection, Mitigation and Energy Optimization: A Review of Some EU Project Results 1 Introduction 2 Improving the Security of Mobile Telephony 3 Security of the Trans-European Health Informatics Network 4 Contributions to the Security of the IoT 5 Conclusions References Application of a Human-Centric Approach in Security by Design for IoT Architecture Development 1 Introduction 1.1 Background 1.2 Digital Identity as Object of Cybersecurity Vulnerabilities 2 Approach for Improving Cyber Awareness Users When Working in Cyberspace and with IoT Devices’ Interface 2.1 Research Method 3 Results of the Study 4 Conclusion References An Empirical Evaluation of the Usefulness of Word Embedding Techniques in Deep Learning-Based Vulnerability Prediction 1 Introduction 2 Related Work 3 Theoretical Background 3.1 Vulnerability Prediction Based on Text-Mining 3.2 Word Embedding Vectors 4 Methodology 4.1 Dataset 4.2 Pre-processing 4.3 Word Embedding Vectors Training 4.4 Model Selection 4.5 Evaluation Metrics 5 Results and Discussion 6 Conclusion and Future Work References Correlation-Based Anomaly Detection for the CAN Bus 1 Introduction 2 Related Work 3 Anomaly Detection Algorithm 3.1 Attacker Model 3.2 Overview 3.3 Data Preprocessing 3.4 Model Training 3.5 Detection 4 Evaluation of the Algorithm 4.1 Testing 4.2 Validation 5 Conclusion and Future Work References Botnet Attack Detection with Incremental Online Learning 1 Introduction 1.1 Attack Detection with the Random Neural Network (RNN) 2 Auto-Associative Dense RNN Based Botnet Attack Detection with Online Incremental Training 3 Extracting Metrics from IoT Traffic 4 Experimental Results 5 Computation Time 6 Conclusions References Optimizing Energy Usage for an Electric Drone 1 Introduction 2 Diffusion Process for the Energy Depletion Process of the Drone 3 Energy Optimization for an UAV During Its Mission 4 Numerical Example 5 Conclusions References T-RAID: TEE-based Remote Attestation for IoT Devices 1 Introduction 2 Approaches to Remote Attestation 3 Overview of T-RAID 4 Remote Attestation Protocol 5 Integrity Checks 5.1 Process Listing 5.2 Memory Integrity Checks 5.3 File Integrity Checks 5.4 Network Checks 6 Evaluation and Discussion 7 Conclusions References Secure Authentication for Everyone! Enabling 2nd-Factor Authentication Under Real-World Constraints 1 Introduction 2 Background 2.1 The Data Breach Problem 2.2 Hardware Authenticators 2.3 FIDO 3 How to Solve the Data Breach Problem? 4 A Secure Mobile Authenticator for Everyone 4.1 Integration of the Authenticator into a Password Manager 5 Discussion 5.1 Authenticator Security 5.2 Comparison with OTP 6 Conclusion References Energy, QoS and Security Aware Edge Services 1 Introduction 2 Random Neural Networks for the Control of Computer Networks 2.1 The Goal of the Decision System 2.2 RNN Based Routing for Path Control 2.3 Energy 2.4 Security 3 Experiments and Results 3.1 Point-to-Point Transmission in Insecure Environment 3.2 Energy-efficient Access to the Edge 4 Conclusions References Mitigating the Massive Access Problem in the Internet of Things 1 Introduction 2 Review of Prior Work on MAP 2.1 Proactive Solutions 3 Mitigating MAP Using Queueing Theory and Diffusion Approximations 3.1 The Probability of Meeting Deadlines 3.2 Interarrival and Service Time Statistics 3.3 Using the Diffusion Approximation: 3.4 Numerical Results Concerning the Diffusion Analysis 3.5 Randomization of Data Generation Times (RGT) 3.6 Experimental Results Concerning RGT 3.7 The Quasi-Deterministic Transmission Policy (QDTP) 3.8 Experimental Results Concerning QDTP 4 Conclusions References Author Index