Cyber Forensics and Investigation on Smart Devices: Volume 1
Beschreibung
This book offers comprehensive insights into digital forensics, guiding readers through analysis methods and security assessments. Expert contributors cover a range of forensic investigations on computer devices, making it an essential resource for professionals, scholars, and students alike. Chapter 1 explores smart home forensics, detailing IoT forensic analysis and examination of different smart home devices. Chapter 2 provides an extensive guide to digital forensics, covering its origin, objectives, tools, challenges, and legal considerations. Chapter 3 focuses on cyber forensics, including secure chat application values and experimentation. Chapter 4 delves into browser analysis and exploitation techniques, while Chapter 5 discusses data recovery from water-damaged Android phones with methods and case studies. Finally, Chapter 6 presents a machine learning approach for detecting ransomware threats in healthcare systems. With a reader-friendly format and practical case studies, this book equips readers with essential knowledge for cybersecurity services and operations. Key Features: Integrates research from various fields (IoT, Big Data, AI, and Blockchain) to explain smart device security. Uncovers innovative features of cyber forensics and smart devices. Harmonizes theoretical and practical aspects of cybersecurity. Includes chapter summaries and key concepts for easy revision. Offers references for further study. Readership: Professionals, apprentices, teachers, and scholars in cyber security and digital forensics programs.
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Inhalt
- Cover
- Title
- Copyright
- End User License Agreement
- Contents
- Foreword
- Preface
- List of Contributors
- Smart Home Forensics
- Lokaiah Pullagura1,*, Nalli Vinaya Kumari2 and Hemanta Kumar Bhuyan3
- 1. INTRODUCTION
- 2. RELATED WORK
- 3. SMART HOME LABS
- 3.1. Process of IoT Forensic Analysis
- 3.2. The Flow of the Process of IoT Forensic Analysis
- 3.2.1. Seizure and Identification
- 3.2.2. Extraction
- 3.2.3. Preservation
- 3.2.4. Analysis
- 3.2.5. Reconstruction
- 3.2.6. Reporting
- 4. FORENSIC ANALYSIS OF A SMART HOME
- 4.1. Lab for Intelligent Residences: An Initial Examination
- 4.2.1. Analyses of Media Streaming Players
- 4.2.2. Analysis of Smart Watches
- 4.2.3. Analyses of the Intelligent Hub
- 4.2.4. An Examination of Smart Doorbells and Smart Locks
- 4.2.5. Analyzing Applications for Network Security
- 4.2.6. Data Mining for the Smart Plug
- 4.2.7. Analyzing the Smart Cameras
- 4.2.8. Analysis of Smart Bulb
- 5. SCENARIOS FOR POSSIBLE SMART HOME THREATS
- CONCLUSION
- REFERENCES
- A Guide to Digital Forensic: Theoretical To Software Based Investigations
- Preeti1,*, Manoj Kumar1 and Hitesh Kumar Sharma1
- 1. INTRODUCTION
- 1.1. Origin of Digital Forensics
- 1.2. Objectives of Digital Forensics
- 2. DIGITAL FORENSICS AND ITS CURRENT ISSUES
- 2.1. Prominent Issues of Digital Forensics
- 2.1.1. Social Networking
- 2.1.2. The Growing Size of Storage
- 2.1.3. Mobile and Embedded Devices
- 2.1.4. Encryption of Course
- 2.1.5. Anti-Forensics
- 3. PHASES OF DIGITAL FORENSICS
- 3.1. Identification
- 3.2. Preservation
- 3.3. Analysis
- 3.4. Documentation
- 3.5. Presentation
- 4. DIFFERENT TYPES OF DIGITAL FORENSICS
- 4.1. Disk Forensics
- 4.2. Networks Forensics
- 4.3. Email Forensics
- 4.4. Malware Forensics
- 4.5. Database Forensics and Memory Forensics
- 4.6. Mobile Phone Forensics
- 5. TOOLS FOR DIGITAL FORENSIC ANALYSIS
- 5.1. EnCase
- 5.2. Sleuth Kit
- 5.3. FTK Toolkit
- 6. CYBERCRIME DIGITAL FORENSICS TOOLS
- 6.1. MemGator
- 6.2. First on Scene
- 6.3. Galleta
- 6.4. Ethreal
- 6.5. Pasco
- 6.6. Rifiuti
- 6.7. Network Mapper (Nmap)
- 7. USE CASES AND SOFTWARE IMPLICATIONS OF DIGITAL FORENSICS
- 7.1. FTK Forensic Toolkit
- 7.1.1. Applications
- 7.2. IBM Security QRadar
- 7.3. ExtraHop
- 7.3.1. Background
- 7.4. Parrot Security OS
- 7.4.1. System Basic Requirements
- 7.4.2. Features
- 7.5. Sleuth Kit (+Autopsy)
- 7.5.1. Applications
- 7.5.2. Features
- 8. DIGITAL FORENSICS CHALLENGES/ADVANTAGES/DISADVANT- AGES/APPLICATIONS
- 8.1. Challenges
- 8.1.1. Proof Oriented Design
- 8.1.2. Data View Inconsistency
- 8.1.3. Item Interpolation Mechanism
- 8.1.4. Run-Time Versus Execution
- 8.1.5. Digital Forensic Awareness
- 8.1.6. Technology Gap
- 8.1.7. Technology Versus tools
- 8.2. Pros of Digital Forensics
- 8.3. Cons of Digital Forensics
- 8.4. Applications of Digital Forensics
- 9. LEGITIMATE CONSIDERATIONS
- 9.1. Legal Consideration
- 10. ARTIFICIAL INTELLIGENCE AND ITS APPLICATION IN DIGITAL FORENSICS
- CONCLUSION
- REFERENCES
- Cyber Forensic: End-to-End Secure Chat Application Value Beyond Claimed Encryption Method
- Hepi Suthar1,2,*
- 1. INTRODUCTION
- 2. EXPERIMENT WORK
- 3. ADDITIONAL INSIGHT
- CONCLUSION
- REFERENCES
- Browser Analysis and Exploitation
- Tripti Misra1,*, Devakrishna C. Nair1, Prabhu Manikandan V1 and Abhishek K. Pradhan1
- 1. INTRODUCTION
- 2. LITERATURE REVIEW
- 3. POPULAR BROWSERS
- 3.1. The Chromium Project
- 3.2. Firefox
- 3.3. Safari
- 4. EXTRACTING INFORMATION FROM BROWSER SQLITE FILES
- 4.1. Parsing SQLITE Files
- 4.2. Using a Simple Python Script
- 4.2.1. Using "Db Browser for SQLite"
- 4.2.2. Web Browser Artifacts for Forensics
- 4.2.3. Extracting Encrypted Information from Chromium-based Browsers
- 4.2.4. Analyze Artifacts Found within the Extensible Storage Engine (ESE) Database Format
- 4.2.5. Examine Files Downloaded by Suspect
- 4.2.6. Determine URLs that Suspects typed, Clicked on, and Bookmarked (Check for Malicious URLs visited)
- 5. ISSUES IN BROWSER FORENSICS
- CONCLUDING REMARKS
- REFERENCES
- Data Recovery from Water-damaged Android Phones
- Ankit Vishnoi1,* and Varun Sapra2
- 1. INTRODUCTION
- 1.1. Phone Parts Damaged when dropped into the Water
- 1.2. What Should One Do If the Phone Gets Wet or Contacts Any Liquid?
- 1.2.1. Take Out Mobile from Water
- 1.2.2. Remove all Parts from Smartphones
- 2. LITERATURE REVIEW
- 3. DATA RECOVERY
- 3.1. Data Recovery using Google Drive
- 4. DATA RECOVERY FROM DAMAGED MOBILE
- 4.1. Case Study 1
- 4.1.1. The Evolution of Mobile Forensics at NIST
- 4.1.2. NIST Forensic Methods
- 4.2. Case Study 2
- 4.2.1. When is a Chip-Off Extraction to be Considered?
- 4.2.2. What kinds of Devices can a Chip-Off Extract?
- 4.3. Experimental Setup
- 4.4. Chip-off Method
- 5. RESULTS
- CONCLUSION
- REFERENCES
- Machine Learning Approach to Detect Ransomware Threats in Health Care Systems
- Varun Sapra1,*, Ankit Vishnoi2 and Luxmi Sapra3
- 1. INTRODUCTION
- 2. IMPACT OF CYBER THREATS ON MEDICAL DATA
- 2.1. Dataset Description
- 2.2. Related Work
- 3. PROPOSED DETECTION SYSTEM
- CONCLUSION
- REFERENCES
- Subject Index
- Back Cover
