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E-raamat: Cyber Security and Digital Forensics: Challenges and Future Trends [Wiley Online]

Edited by (Sandip Institute of Technology and Research Center, Nashik, Maharashtra, India), Edited by (Haiphong University, Vietnam), Edited by (Dwarkadas J. Sanghvi College of Engineering, Mumbai, Maharashtra, India), Edited by (Haldia Institute of Technology, India)
  • Formaat: 432 pages
  • Sari: Advances in Cyber Security
  • Ilmumisaeg: 04-Feb-2022
  • Kirjastus: Wiley-Scrivener
  • ISBN-10: 1119795664
  • ISBN-13: 9781119795667
Teised raamatud teemal:
  • Wiley Online
  • Hind: 237,89 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
Cyber Security and Digital Forensics: Challenges and Future TrendsSuurem pilt
  • Formaat: 432 pages
  • Sari: Advances in Cyber Security
  • Ilmumisaeg: 04-Feb-2022
  • Kirjastus: Wiley-Scrivener
  • ISBN-10: 1119795664
  • ISBN-13: 9781119795667
Teised raamatud teemal:
Wiley Online e-raamatudRohkem infot Wiley Online kohta
Raamatu kodulehekülg: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119795667
CYBER SECURITY AND DIGITAL FORENSICS Cyber security is an incredibly important issue that is constantly changing, with new methods, processes, and technologies coming online all the time. Books like this are invaluable to professionals working in this area, to stay abreast of all of these changes.



Current cyber threats are getting more complicated and advanced with the rapid evolution of adversarial techniques. Networked computing and portable electronic devices have broadened the role of digital forensics beyond traditional investigations into computer crime. The overall increase in the use of computers as a way of storing and retrieving high-security information requires appropriate security measures to protect the entire computing and communication scenario worldwide. Further, with the introduction of the internet and its underlying technology, facets of information security are becoming a primary concern to protect networks and cyber infrastructures from various threats.

This groundbreaking new volume, written and edited by a wide range of professionals in this area, covers broad technical and socio-economic perspectives for the utilization of information and communication technologies and the development of practical solutions in cyber security and digital forensics. Not just for the professional working in the field, but also for the student or academic on the university level, this is a must-have for any library.

Audience: Practitioners, consultants, engineers, academics, and other professionals working in the areas of cyber analysis, cyber security, homeland security, national defense, the protection of national critical infrastructures, cyber-crime, cyber vulnerabilities, cyber-attacks related to network systems, cyber threat reduction planning, and those who provide leadership in cyber security management both in public and private sectors
Preface xvii
Acknowledgment xxvii
1 A Comprehensive Study of Security Issues and Research Challenges in Different Layers of Service-Oriented IoT Architecture
1(44)
Ankur O. Bang
Udai Pratap Rao
Amit A. Bhusari
1.1 Introduction and Related Work
2(2)
1.2 IoT: Evolution, Applications and Security Requirements
4(6)
1.2.1 IoT and Its Evolution
5(1)
1.2.2 Different Applications of IoT
5(2)
1.2.3 Different Things in IoT
7(1)
1.2.4 Security Requirements in IoT
8(2)
1.3 Service-Oriented IoT Architecture and IoT Protocol Stack
10(14)
1.3.1 Service-Oriented IoT Architecture
10(1)
1.3.2 IoT Protocol Stack
11(1)
1.3.2.1 Application Layer Protocols
12(1)
1.3.2.2 Transport Layer Protocols
13(2)
1.3.2.3 Network Layer Protocols
15(1)
1.3.2.4 Link Layer and Physical Layer Protocols
16(8)
1.4 Anatomy of Attacks on Service-Oriented IoT Architecture
24(7)
1.4.1 Attacks on Software Service
24(1)
1.4.1.1 Operating System-Level Attacks
24(1)
1.4.1.2 Application-Level Attacks
25(1)
1.4.1.3 Firmware-Level Attacks
25(1)
1.4.2 Attacks on Devices
26(1)
1.4.3 Attacks on Communication Protocols
26(1)
1.4.3.1 Attacks on Application Layer Protocols
26(2)
1.4.3.2 Attacks on Transport Layer Protocols
28(1)
1.4.3.3 Attacks on Network Layer Protocols
28(2)
1.4.3.4 Attacks on Link and Physical Layer Protocols
30(1)
1.5 Major Security Issues in Service-Oriented IoT Architecture
31(4)
1.5.1 Application -- Interface Layer
32(1)
1.5.2 Service Layer
33(1)
1.5.3 Network Layer
33(1)
1.5.4 Sensing Layer
34(1)
1.6 Conclusion
35(10)
References
36(9)
2 Quantum and Post-Quantum Cryptography
45(14)
Om Pal
Manoj Jain
B.K. Murthy
Vinay Thakur
2.1 Introduction
46(1)
2.2 Security of Modern Cryptographic Systems
46(3)
2.2.1 Classical and Quantum Factoring of A Large Number
47(2)
2.2.2 Classical and Quantum Search of An Item
49(1)
2.3 Quantum Key Distribution
49(4)
2.3.1 BB84 Protocol
50(1)
2.3.1.1 Proposed Key Verification Phase for BB84
51(1)
2.3.2 E91 Protocol
51(1)
2.3.3 Practical Challenges of Quantum Key Distribution
52(1)
2.3.4 Multi-Party Quantum Key Agreement Protocol
53(1)
2.4 Post-Quantum Digital Signature
53(2)
2.4.1 Signatures Based on Lattice Techniques
54(1)
2.4.2 Signatures Based on Multivariate Quadratic Techniques
55(1)
2.4.3 Hash-Based Signature Techniques
55(1)
2.5 Conclusion and Future Directions
55(4)
References
56(3)
3 Artificial Neural Network Applications in Analysis of Forensic Science
59(14)
K.R. Padma
K.R. Don
3.1 Introduction
60(1)
3.2 Digital Forensic Analysis Knowledge
61(1)
3.3 Answer Set Programming in Digital Investigations
61(2)
3.4 Data Science Processing with Artificial Intelligence Models
63(1)
3.5 Pattern Recognition Techniques
63(2)
3.6 ANN Applications
65(1)
3.7 Knowledge on Stages of Digital Forensic Analysis
65(2)
3.8 Deep Learning and Modelling
67(1)
3.9 Conclusion
68(5)
References
69(4)
4 A Comprehensive Survey of Fully Homomorphic Encryption from Its Theory to Applications
73(18)
Rashmi Salavi
Dr. M. M. Math
Dr. U. P. Kulkarni
4.1 Introduction
73(3)
4.2 Homomorphic Encryption Techniques
76(3)
4.2.1 Partial Homomorphic Encryption Schemes
77(1)
4.2.2 Fully Homomorphic Encryption Schemes
78(1)
4.3 Homomorphic Encryption Libraries
79(4)
4.4 Computations on Encrypted Data
83(2)
4.5 Applications of Homomorphic Encryption
85(1)
4.6 Conclusion
86(5)
References
87(4)
5 Understanding Robotics through Synthetic Psychology
91(14)
Garima Saini
Dr. Shabnam
5.1 Introduction
91(1)
5.2 Physical Capabilities of Robots
92(3)
5.2.1 Artificial Intelligence and Neuro Linguistic Programming (NLP)
93(1)
5.2.2 Social Skill Development and Activity Engagement
93(1)
5.2.3 Autism Spectrum Disorders
93(1)
5.2.4 Age-Related Cognitive Decline and Dementia
94(1)
5.2.5 Improving Psychosocial Outcomes through Robotics
94(1)
5.2.6 Clients with Disabilities and Robotics
94(1)
5.2.7 Ethical Concerns and Robotics
95(1)
5.3 Traditional Psychology, Neuroscience and Future Robotics
95(2)
5.4 Synthetic Psychology and Robotics: A Vision of the Future
97(1)
5.5 Synthetic Psychology: The Foresight
98(1)
5.6 Synthetic Psychology and Mathematical Optimization
99(1)
5.7 Synthetic Psychology and Medical Diagnosis
99(2)
5.7.1 Virtual Assistance and Robotics
100(1)
5.7.2 Drug Discovery and Robotics
100(1)
5.8 Conclusion
101(4)
References
101(4)
6 An Insight into Digital Forensics: History, Frameworks, Types and Tools
105(22)
G. Maria Jones
S. Godfrey Winster
6.1 Overview
105(2)
6.2 Digital Forensics
107(1)
6.2.1 Why Do We Need Forensics Process?
107(1)
6.2.2 Forensics Process Principles
108(1)
6.3 Digital Forensics History
108(3)
6.3.1 1985 to 1995
108(1)
6.3.2 1995 to 2005
109(1)
6.3.3 2005 to 2015
110(1)
6.4 Evolutionary Cycle of Digital Forensics
111(1)
6.4.1 Ad Hoc
111(1)
6.4.2 Structured Phase
111(1)
6.4.3 Enterprise Phase
112(1)
6.5 Stages of Digital Forensics Process
112(3)
6.5.1 Stage 1 -- 1995 to 2003
112(1)
6.5.2 Stage II -- 2004 to 2007
113(1)
6.5.3 Stage III -- 2007 to 2014
114(1)
6.6 Types of Digital Forensics
115(3)
6.6.1 Cloud Forensics
116(1)
6.6.2 Mobile Forensics
116(1)
6.6.3 IoT Forensics
116(1)
6.6.4 Computer Forensics
117(1)
6.6.5 Network Forensics
117(1)
6.6.6 Database Forensics
118(1)
6.7 Evidence Collection and Analysis
118(1)
6.8 Digital Forensics Tools
119(4)
6.8.1 X-Ways Forensics
119(1)
6.8.2 SANS Investigative Forensics Toolkit -- SIFT
119(1)
6.8.3 EnCase
119(3)
6.8.4 The Sleuth Kit/Autopsy
122(1)
6.8.5 Oxygen Forensic Suite
122(1)
6.8.6 Xplico
122(1)
6.8.7 Computer Online Forensic Evidence Extractor (COFEE)
122(1)
6.8.8 Cellebrite UFED
122(1)
6.8.9 OSForeniscs
123(1)
6.8.10 Computer-Aided Investigative Environment (CAINE)
123(1)
6.9 Summary
123(4)
References
123(4)
7 Digital Forensics as a Service: Analysis for Forensic Knowledge
127(36)
Soumi Banerjee
Anita Patil
Dipti Jadhav
Gautam Borkar
7.1 Introduction
127(1)
7.2 Objective
128(1)
7.3 Types of Digital Forensics
129(32)
7.3.1 Network Forensics
129(13)
7.3.2 Computer Forensics
142(5)
7.3.3 Data Forensics
147(2)
7.3.4 Mobile Forensics
149(5)
7.3.5 Big Data Forensics
154(1)
7.3.6 IoT Forensics
155(2)
7.3.7 Cloud Forensics
157(4)
7.4 Conclusion
161(2)
References
161(2)
8 4S Framework: A Practical CPS Design Security Assessment & Benchmarking Framework
163(42)
Neel A. Patel
Dhairya A. Parekh
Yash A. Shah
Ramchandra Mangrulkar
8.1 Introduction
164(2)
8.2 Literature Review
166(4)
8.3 Medical Cyber Physical System (MCPS)
170(2)
8.3.1 Difference between CPS and MCPS
171(1)
8.3.2 MCPS Concerns, Potential Threats, Security
171(1)
8.4 CPSSEC vs. Cyber Security
172(1)
8.5 Proposed Framework
173(14)
8.5.1 4S Definitions
174(1)
8.5.2 4S Framework-Based CPSSEC Assessment Process
175(6)
8.5.3 4S Framework-Based CPSSEC Assessment Score Breakdown & Formula
181(6)
8.6 Assessment of Hypothetical MCPS Using 4S Framework
187(13)
8.6.1 System Description
187(1)
8.6.2 Use Case Diagram for the Above CPS
188(1)
8.6.3 Iteration 1 of 4S Assessment
189(6)
8.6.4 Iteration 2 of 4S Assessment
195(5)
8.7 Conclusion
200(1)
8.8 Future Scope
201(4)
References
201(4)
9 Ensuring Secure Data Sharing in IoT Domains Using Blockchain
205(18)
Tawseef Ahmed Teli
Rameez Yousuf
Dawood Ashrafkhan
9.1 IoT and Blockchain
205(6)
9.1.1 Public
208(1)
9.1.1.1 Proof of Work (PoW)
209(1)
9.1.1.2 Proof of Stake (PoS)
209(1)
9.1.1.3 Delegated Proof of Stake (DPoS)
210(1)
9.1.2 Private
210(1)
9.1.3 Consortium or Federated
210(1)
9.2 IoT Application Domains and Challenges in Data Sharing
211(3)
9.3 Why Blockchain?
214(2)
9.4 IoT Data Sharing Security Mechanism On Blockchain
216(3)
9.4.1 Double-Chain Mode Based On Blockchain Technology
216(1)
9.4.2 Blockchain Structure Based On Time Stamp
217(2)
9.5 Conclusion
219(4)
References
219(4)
10 A Review of Face Analysis Techniques for Conventional and Forensic Applications
223(18)
H. T. Chethana
Trisiladevi C. Nagavi
10.1 Introduction
224(1)
10.2 Face Recognition
225(4)
10.2.1 Literature Review on Face Recognition
226(2)
10.2.2 Challenges in Face Recognition
228(1)
10.2.3 Applications of Face Recognition
229(1)
10.3 Forensic Face Recognition
229(9)
10.3.1 Literature Review on Face Recognition for Forensics
231(2)
10.3.2 Challenges of Face Recognition in Forensics
233(2)
10.3.3 Possible Datasets Used for Forensic Face Recognition
235(1)
10.3.4 Fundamental Factors for Improving Forensics Science
235(2)
10.3.5 Future Perspectives
237(1)
10.4 Conclusion
238(3)
References
238(3)
11 Roadmap of Digital Forensics Investigation Process with Discovery of Tools
241(30)
Anita Patil
Soumi Banerjee
Dipti Jadhav
Gautam Borkar
11.1 Introduction
242(2)
11.2 Phases of Digital Forensics Process
244(2)
11.2.1 Phase I -- Identification
244(1)
11.2.2 Phase II -- Acquisition and Collection
245(1)
11.2.3 Phase III -- Analysis and Examination
245(1)
11.2.4 Phase IV -- Reporting
245(1)
11.3 Analysis of Challenges and Need of Digital Forensics
246(2)
11.3.1 Digital Forensics Process has following Challenges
246(1)
11.3.2 Needs of Digital Forensics Investigation
247(1)
11.3.3 Other Common Attacks Used to Commit the Crime
248(1)
11.4 Appropriateness of Forensics Tool
248(5)
11.4.1 Level of Skill
248(4)
11.4.2 Outputs
252(1)
11.4.3 Region of Emphasis
252(1)
11.4.4 Support for Additional Hardware
252(1)
11.5 Phase-Wise Digital Forensics Techniques
253(13)
11.5.1 Identification
253(1)
11.5.2 Acquisition
254(2)
11.5.3 Analysis
256(1)
11.5.3.1 Data Carving
257(2)
11.5.3.2 Different Curving Techniques
259(1)
11.5.3.3 Volatile Data Forensic Toolkit Used to Collect and Analyze the Data from Device
260(5)
11.5.4 Report Writing
265(1)
11.6 Pros and Cons of Digital Forensics Investigation Process
266(1)
11.6.1 Advantages of Digital Forensics
266(1)
11.6.2 Disadvantages of Digital Forensics
266(1)
11.7 Conclusion
267(4)
References
267(4)
12 Utilizing Machine Learning and Deep Learning in Cybesecurity: An Innovative Approach
271(24)
Dushyant Kaushik
Muskan Garg
Annu
Ankur Gupta
Sabyasachi Pramanik
12.1 Introduction
271(10)
12.1.1 Protections of Cybersecurity
272(2)
12.1.2 Machine Learning
274(2)
12.1.3 Deep Learning
276(2)
12.1.4 Machine Learning and Deep Learning: Similarities and Differences
278(3)
12.2 Proposed Method
281(2)
12.2.1 The Dataset Overview
282(1)
12.2.2 Data Analysis and Model for Classification
283(1)
12.3 Experimental Studies and Outcomes Analysis
283(6)
12.3.1 Metrics on Performance Assessment
284(1)
12.3.2 Result and Outcomes
285(1)
12.3.2.1 Issue 1: Classify the Various Categories of Feedback Related to the Malevolent Code Provided
285(1)
12.3.2.2 Issue 2: Recognition of the Various Categories of Feedback Related to the Malware Presented
286(1)
12.3.2.3 Issue 3: According to the Malicious Code, Distinguishing Various Forms of Malware
287(1)
12.3.2.4 Issue 4: Detection of Various Malware Styles Based on Different Responses
287(1)
12.3.3 Discussion
288(1)
12.4 Conclusions and Future Scope
289(6)
References
292(3)
13 Applications of Machine Learning Techniques in the Realm of Cybersecurity
295(22)
Koushal Kumar
Bhagwati Prasad Pande
13.1 Introduction
296(2)
13.2 A Brief Literature Review
298(2)
13.3 Machine Learning and Cybersecurity: Various Issues
300(4)
13.3.1 Effectiveness of ML Technology in Cybersecurity Systems
300(2)
13.3.2 Machine Learning Problems and Challenges in Cybersecurity
302(1)
13.3.2.1 Lack of Appropriate Datasets
302(1)
13.3.2.2 Reduction in False Positives and False Negatives
302(1)
13.3.2.3 Adversarial Machine Learning
302(1)
13.3.2.4 Lack of Feature Engineering Techniques
303(1)
13.3.2.5 Context-Awareness in Cybersecurity
303(1)
13.3.3 Is Machine Learning Enough to Stop Cybercrime?
304(1)
13.4 ML Datasets and Algorithms Used in Cybersecurity
304(6)
13.4.1 Study of Available ML-Driven Datasets Available for Cybersecurity
304(1)
13.4.1.1 KDD Cup 1999 Dataset (DARPA 1998)
305(1)
13.4.1.2 NSL-KDD Dataset
305(1)
13.4.1.3 ECML-PKDD 2007 Discovery Challenge Dataset
305(1)
13.4.1.4 Malicious URL's Detection Dataset
306(1)
13.4.1.5 ISOT (Information Security and Object Technology) Botnet Dataset
306(1)
13.4.1.6 CTU-13 Dataset
306(1)
13.4.1.7 M AWT Lab Anomaly Detection Dataset
307(1)
13.4.1.8 ADFA-LD and ADFA-WD Datasets
307(1)
13.4.2 Applications ML Algorithms in Cybersecurity Affairs
307(2)
13.4.2.1 Clustering
309(1)
13.4.2.2 Support Vector Machine (SVM)
309(1)
13.4.2.3 Nearest Neighbor (NN)
309(1)
13.4.2.4 Decision Tree
309(1)
13.4.2.5 Dimensionality Reduction
310(1)
13.5 Applications of Machine Learning in the Realm of Cybersecurity
310(3)
13.5.1 Facebook Monitors and Identifies Cybersecurity Threats with ML
310(1)
13.5.2 Microsoft Employs ML for Security
311(1)
13.5.3 Applications of ML by Google
312(1)
13.6 Conclusions
313(4)
References
313(4)
14 Security Improvement Technique for Distributed Control System (DCS) and Supervisory Control-Data Acquisition (SCADA) Using Blockchain at Dark Web Platform
317(18)
Anand Singh Rajawat
Romil Rawat
Kanishk Barhanpurkar
14.1 Introduction
318(4)
14.2 Significance of Security Improvement in DCS and SCADA
322(1)
14.3 Related Work
323(1)
14.4 Proposed Methodology
324(5)
14.4.1 Algorithms Used for Implementation
327(1)
14.4.2 Components of a Blockchain
327(1)
14.4.3 MERKLE Tree
328(1)
14.4.4 The Technique of Stack and Work Proof
328(1)
14.4.5 Smart Contracts
329(1)
14.5 Result Analysis
329(1)
14.6 Conclusion
330(5)
References
331(4)
15 Recent Techniques for Exploitation and Protection of Common Malicious Inputs to Online Applications
335(26)
Dr. Tun Myat Aung
Ni Ni Hla
15.1 Introduction
335(1)
15.2 SQL Injection
336(8)
15.2.1 Introduction
336(1)
15.2.2 Exploitation Techniques
337(1)
15.2.2.1 In-Band SQL Injection
337(1)
15.2.2.2 Inferential SQL Injection
338(2)
15.2.2.3 Out-of-Band SQL Injection
340(1)
15.2.3 Causes of Vulnerability
340(1)
15.2.4 Protection Techniques
341(1)
15.2.4.1 Input Validation
341(1)
15.2.4.2 Data Sanitization
341(1)
15.2.4.3 Use of Prepared Statements
342(1)
15.2.4.4 Limitation of Database Permission
343(1)
15.2.4.5 Using Encryption
343(1)
15.3 Cross Site Scripting
344(5)
15.3.1 Introduction
344(1)
15.3.2 Exploitation Techniques
344(1)
15.3.2.1 Reflected Cross Site Scripting
345(1)
15.3.2.2 Stored Cross Site Scripting
345(1)
15.3.2.3 DOM-Based Cross Site Scripting
346(1)
15.3.3 Causes of Vulnerability
346(1)
15.3.4 Protection Techniques
347(1)
15.3.4.1 Data Validation
347(1)
15.3.4.2 Data Sanitization
347(1)
15.3.4.3 Escaping on Output
347(1)
15.3.4.4 Use of Content Security Policy
348(1)
15.4 Cross Site Request Forgery
349(4)
15.4.1 Introduction
349(1)
15.4.2 Exploitation Techniques
349(1)
15.4.2.1 HTTP Request with GET Method
349(1)
15.4.2.2 HTTP Request with POST Method
350(1)
15.4.3 Causes of Vulnerability
350(1)
15.4.3.1 Session Cookie Handling Mechanism
350(1)
15.4.3.2 HTML Tag
351(1)
15.4.3.3 Browsers View Source Option
351(1)
15.4.3.4 GET and POST Method
351(1)
15.4.4 Protection Techniques
351(1)
15.4.4.1 Checking HTTP Referer
351(1)
15.4.4.2 Using Custom Header
352(1)
15.4.4.3 Using Anti-CSRF Tokens
352(1)
15.4.4.4 Using a Random Value for each Form Field
352(1)
15.4.4.5 Limiting the Lifetime of Authentication Cookies
353(1)
15.5 Command Injection
353(2)
15.5.1 Introduction
353(1)
15.5.2 Exploitation Techniques
354(1)
15.5.3 Causes of Vulnerability
354(1)
15.5.4 Protection Techniques
355(1)
15.6 File Inclusion
355(3)
15.6.1 Introduction
355(1)
15.6.2 Exploitation Techniques
355(1)
15.6.2.1 Remote File Inclusion
355(1)
15.6.2.2 Local File Inclusion
356(1)
15.6.3 Causes of Vulnerability
357(1)
15.6.4 Protection Techniques
357(1)
15.7 Conclusion
358(3)
References
358(3)
16 Ransomware: Threats, Identification and Prevention
361(28)
Sweta Thakur
Sangita Chaudhari
Bharti Joshi
16.1 Introduction
361(3)
16.2 Types of Ransomwares
364(10)
16.2.1 Locker Ransomware
364(1)
16.2.1.1 Reveton Ransomware
365(1)
16.2.1.2 Locky Ransomware
366(1)
16.2.1.3 CTB Locker Ransomware
366(1)
16.2.1.4 TorrentLocker Ransomware
366(1)
16.2.2 Crypto Ransomware
367(1)
16.2.2.1 PC Cyborg Ransomware
367(1)
16.2.2.2 OneHalf Ransomware
367(1)
16.2.2.3 GPCode Ransomware
367(1)
16.2.2.4 CryptoLocker Ransomware
368(1)
16.2.2.5 CryptoDefense Ransomware
368(1)
16.2.2.6 Crypto Wall Ransomware
368(1)
16.2.2.7 TeslaCrypt Ransomware
368(1)
16.2.2.8 Cerber Ransomware
368(1)
16.2.2.9 Jigsaw Ransomware
369(1)
16.2.2.10 Bad Rabbit Ransomware
369(1)
16.2.2.11 WannaCry Ransomware
369(1)
16.2.2.12 Petya Ransomware
369(1)
16.2.2.13 Gandcrab Ransomware
369(1)
16.2.2.14 Rapid Ransomware
370(1)
16.2.2.15 Ryuk Ransomware
370(1)
16.2.2.16 Lockergoga Ransomware
370(1)
16.2.2.17 PewCrypt Ransomware
370(1)
16.2.2.18 Dhrama/Crysis Ransomware
370(1)
16.2.2.19 Phobos Ransomware
371(1)
16.2.2.20 Malito Ransomware
371(1)
16.2.2.21 LockBit Ransomware
371(1)
16.2.2.22 GoldenEye Ransomware
371(1)
16.2.2.23 REvil or Sodinokibi Ransomware
371(1)
16.2.2.24 Nemty Ransomware
371(1)
16.2.2.25 Nephilim Ransomware
372(1)
16.2.2.26 Maze Ransomware
372(1)
16.2.2.27 Sekhmet Ransomware
372(1)
16.2.3 MAC Ransomware
372(1)
16.2.3.1 KeRanger Ransomware
373(1)
16.2.3.2 Go Pher Ransomware
373(1)
16.2.3.3 FBI Ransom Ransomware
373(1)
16.2.3.4 File Coder
373(1)
16.2.3.5 Patcher
373(1)
16.2.3.6 ThiefQuest Ransomware
374(1)
16.2.3.7 Keydnap Ransomware
374(1)
16.2.3.8 Bird Miner Ransomware
374(1)
16.3 Ransomware Life Cycle
374(2)
16.4 Detection Strategies
376(2)
16.4.1 UNEVIL
376(1)
16.4.2 Detecting File Lockers
376(1)
16.4.3 Detecting Screen Lockers
377(1)
16.4.4 Connection-Monitor and Connection-Breaker Approach
377(1)
16.4.5 Ransomware Detection by Mining API Call Usage
377(1)
16.4.6 A New Static-Based Framework for Ransomware Detection
377(1)
16.4.7 White List-Based Ransomware Real-Time Detection Prevention (WRDP)
378(1)
16.5 Analysis of Ransomware
378(2)
16.5.1 Static Analysis
379(1)
16.5.2 Dynamic Analysis
379(1)
16.6 Prevention Strategies
380(1)
16.6.1 Access Control
380(1)
16.6.2 Recovery After Infection
380(1)
16.6.3 Trapping Attacker
380(1)
16.7 Ransomware Traits Analysis
380(4)
16.8 Research Directions
384(1)
16.9 Conclusion
384(5)
References
384(5)
Index 389
Mangesh M. Ghonge, PhD, is currently working at Sandip Institute of Technology and Research Center, Nashik, Maharashtra, India. He authored or co-authored more than 60 published articles in prestigious journals, book chapters, and conference papers. He is also the author or editor of ten books and has organized and chaired many national and international conferences.

Sabyasachi Pramanik, PhD, is an assistant professor in the Department of Computer Science and Engineering, Haldia Institute of Technology, India. He earned his doctorate in computer science and engineering from the Sri Satya Sai University of Technology and Medical Sciences, Bhopal, India. He has many publications in various reputed international conferences, journals, and online book chapter contributions and is also serving as the editorial board member of many international journals. He is a reviewer of journal articles in numerous technical journals and has been a keynote speaker, session chair and technical program committee member in many international conferences. He has authored a book on wireless sensor networks and is currently editing six books for multiple publishers, including Scrivener Publishing.

Ramchandra Mangrulkar, PhD, is an associate professor in the Department of Computer Engineering at SVKMs Dwarkadas J. Sanghvi College of Engineering, Mumbai, Maharashtra, India. He has published 48 papers and 12 book chapters and presented significant papers at technical conferences. He has also chaired many conferences as a session chair and conducted various workshops and is also a ICSI-CNSS Certified Network Security Specialist. He is an active member on boards of studies in various universities and institutes in India.

Dac-Nhuong Le, PhD, is an associate professor and associate dean at Haiphong University, Vietnam. He earned his MSc and PhD in computer science from Vietnam National University, and he has over 20 years of teaching experience. He has over 50 publications in reputed international conferences, journals and online book chapter contributions and has chaired numerous international conferences. He has served on numerous editorial boards for scientific and technical journals and has authored or edited over 15 books by various publishers, including Scrivener Publishing.
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