| Description |
1 online resource (258 p.) |
| Contents |
Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Preface -- Acknowledgments -- Chapter 1: Detection of Cross-Site Scripting and Phishing Website Vulnerabilities Using Machine Learning -- 1.1 Introduction -- 1.2 Related Work -- 1.3 Implementation -- 1.4 Phishing Websites Detection -- 1.4.1 Phishing Websites -- 1.4.2 Phishing Websites Detection Techniques -- 1.5 Implementation Flowchart ( Figure 1.2) -- 1.5.1 Dataset -- 1.5.2 Classifiers -- 1.6 Result and Discussion -- 1.7 Conclusion and Future Work -- References -- Conferences |
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Online Documents/Resources -- Chapter 2: A Review: Security and Privacy Defensive Techniques for Cyber Security Using Deep Neural Networks (DNNs) -- 2.1 Introduction -- 2.1.1 Pixel Restoration -- 2.1.2 Deep Dreaming -- 2.1.3 Image-Language Translations -- 2.1.4 Virtual Assistants -- 2.1.5 Fraud Detection -- 2.1.6 Automatic Handwriting -- 2.1.7 Healthcare -- 2.2 Related Work -- 2.3 Deep Learning Models for Cyber Security -- 2.3.1 Convolutional Neural Networks (Conv Nets) -- 2.3.2 Recurrent Neural Networks (RNNs) -- 2.3.3 Generative Adversarial Networks (GANs) |
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2.4 Cyber Attacks and Threats with Deep Neural Network -- 2.5 Conclusion -- References -- Chapter 3: DNA-Based Cryptosystem for Connected Objects and IoT Security -- 3.1 Introduction -- 3.2 Related Works -- 3.3 Theory and Background -- 3.3.1 Cryptography -- 3.3.2 DNA-Based Cryptography -- 3.3.3 Huffman Compression -- 3.4 Proposed Cryptosystem-Based DNA -- 3.4.1 Specifications Presentation -- 3.4.2 Encryption Process -- 3.4.2.1 Consideration for the Key Generation -- 3.4.2.2 Phases of Encryption Process -- 3.4.3 Decryption Process -- 3.4.4 Security Evaluation -- 3.4.4.1 Frequency Analysis |
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3.4.4.2 Encryption Key Security Analysis -- 3.4.4.3 Entropy of the Encryption Key -- 3.5 Cryptosystem Hardware Implementation -- 3.5.1 General Description of the Cryptosystem -- 3.5.2 Presentation of Used Components -- 3.5.2.1 Temperature and Humidity Sensor DHT11 -- 3.5.2.2 Communication Radio Module NRF24L01 -- 3.5.2.3 Mounting Principle (Transmitter/Receiver) -- 3.6 Human-Machine Interface (HMI) -- 3.6.1 Transfer of Data Acquired by Sensors -- 3.6.2 Visual Programming of the HMI -- 3.6.2.1 Splitting Data -- 3.6.2.2 Temperature Display -- 3.6.3 HMI Visualization -- 3.7 IoT-Based Supervision |
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3.7.1 FRED (Front End for Node-Red) -- 3.7.2 Visualization of HMI on the Cloud -- 3.8 Conclusion and Future Work -- Acknowledgment -- References -- Chapter 4: A Role of Digital Evidence: Mobile Forensics Data -- 4.1 Introduction -- 4.1.1 Technology as Digital Evidence -- 4.1.2 Digital Forensic -- 4.2 Related Works -- 4.3 Mobile Device Forensics -- 4.3.1 Types of Data Acquisition -- 4.4 Various Types of Mobile Evidence -- 4.4.1 SMS/MMS -- 4.4.2 Call Logs -- 4.4.3 Multimedia Data -- 4.4.4 Geolocation -- 4.4.5 Browser History -- 4.4.6 Device Application -- 4.5 Forensics Acquisition and Examination |
| Notes |
Description based upon print version of record |
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4.5.1 Creating Social Context |
| Subject |
Computer security.
|
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Computer crimes -- Investigation.
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Computer crimes -- Investigation
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Computer security
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| Form |
Electronic book
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| Author |
Tayal, Shubham
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Bhardwaj, Akashdeep
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Kumar, Manoj
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| ISBN |
9781000520590 |
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1000520595 |
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