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Information Security: Foundations, technologies and applications [Kõva köide]

Edited by (University of Kent, School of Engineering and Digital Arts, UK), Edited by (Lulea University of Technology, Department of Computer Science, Electrical and Space Engineering, Sweden)
  • Formaat: Hardback, 416 pages, kõrgus x laius: 234x156 mm
  • Sari: Security
  • Ilmumisaeg: 08-Jun-2018
  • Kirjastus: Institution of Engineering and Technology
  • ISBN-10: 1849199744
  • ISBN-13: 9781849199742
Teised raamatud teemal:
Information Security: Foundations, technologies and applicationsSuurem pilt
  • Formaat: Hardback, 416 pages, kõrgus x laius: 234x156 mm
  • Sari: Security
  • Ilmumisaeg: 08-Jun-2018
  • Kirjastus: Institution of Engineering and Technology
  • ISBN-10: 1849199744
  • ISBN-13: 9781849199742
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781849199742.html
The latest advances in computational methods have increased their scalability across a diverse range of applications and possible practical deployment. This book outlines the key emerging trends in computational methods, in terms of theories, algorithms and applications, for information security. Studies which couple computational theories and algorithms with real-time information security problems are combined with survey material which emphasizes the applications of computational methods in information security. It covers computing paradigms and technologies such as cryptography and cryptanalysis, biometrics-based identification and recognition, watermarking and steganography, software security assurance, physical and logical accesses, and cloud-based systems. It features applications to surveillance, e-health, e-government, e-business, financial services, computer forensics, privacy and trust, cybersecurity and defense.

Computational Methods in Information Security is a comprehensive review of cutting-edge algorithms, technologies, and applications, and provides new insights into a range of fundamentally important topics in the field. This up-to-date body of knowledge is essential reading for researchers and advanced students in information security and computing, and for professionals in sectors where information security is an issue.
Part I Theories and foundations 1(188)
1 Introduction to information security foundations and applications
3(10)
Ali Ismail Awad
1.1 Background
3(1)
1.2 The structure of this book
4(3)
1.2.1 Part I: Theories and foundations
4(2)
1.2.2 Part II: Technologies and applications
6(1)
References
7(6)
2 Information security foundation, theories and future vision
13(28)
Steven Furnell
2.1 Defining the problem
13(6)
2.2 Security threats and protection
19(7)
2.3 Appreciating the breadth of information security
26(6)
2.4 Future vision
32(5)
References
37(4)
3 Information systems security issues in the context of developing countries
41(16)
Devinder Thapa
Samar Fumudoh
Usha Vishwanathan
Abstract
41(1)
3.1 Introduction
41(2)
3.1.1 What is ISS?
42(1)
3.1.2 ISS in the context of developing countries
43(1)
3.2 Problem area
43(1)
3.3 Methodology
44(2)
3.3.1 Analysing the data
45(1)
3.4 Findings
46(4)
3.4.1 Legislation
46(1)
3.4.2 Policy
47(1)
3.4.3 Education
48(1)
3.4.4 Culture
49(1)
3.4.5 Dependencies
50(1)
3.5 Discussion
50(2)
3.6 Conclusion
52(1)
References
52(5)
4 Biometric systems, modalities and attacks
57(36)
Nathan Clarke
4.1 Introduction
57(1)
4.2 Biometric components and attributes
58(3)
4.3 Biometric performance characteristics
61(6)
4.4 Physiological biometric approaches
67(5)
4.4.1 Ear geometry
67(1)
4.4.2 Facial recognition
68(1)
4.4.3 Facial thermogram
69(1)
4.4.4 Fingerprint recognition
69(1)
4.4.5 Hand geometry
70(1)
4.4.6 Iris recognition
70(1)
4.4.7 Retinal recognition
71(1)
4.4.8 Vascular pattern recognition
71(1)
4.5 Behavioural biometric approaches
72(3)
4.5.1 Behavioural profiling
72(1)
4.5.2 Gait recognition
73(1)
4.5.3 Keystroke analysis
74(1)
4.5.4 Signature recognition
74(1)
4.5.5 Speaker recognition (or voice verification)
74(1)
4.6 Attacks against biometrics
75(4)
4.7 Multibiometrics
79(8)
4.7.1 Fusion
81(4)
4.7.2 Performance of multimodal systems
85(2)
4.8 Biometric standards
87(2)
4.9 Conclusions
89(1)
References
89(4)
5 Foundation of healthcare cybersecurity
93(28)
Jemal H. Abawajy
Abstract
93(1)
5.1 Introduction
93(2)
5.2 Health system architecture
95(6)
5.2.1 Healthcare infrastructure
95(1)
5.2.2 Healthcare dataset
96(1)
5.2.3 Data access infrastructure
97(1)
5.2.4 Privacy and security requirements
98(3)
5.3 Health data breach incidents
101(3)
5.3.1 Cyberattacks against health care
102(1)
5.3.2 Impact of cyberattacks
103(1)
5.4 Healthcare vulnerability landscape
104(3)
5.4.1 Medical device vulnerability
104(1)
5.4.2 Outsourcing vulnerabilities
105(1)
5.4.3 Software and hardware vulnerabilities
105(1)
5.4.4 End user vulnerability
106(1)
5.4.5 Business vulnerability
106(1)
5.5 Healthcare threat landscape
107(3)
5.5.1 Cyber threat
107(1)
5.5.2 Social engineering threat
107(1)
5.5.3 Employee threat
108(1)
5.5.4 Malicious software threats
108(1)
5.5.5 Mobile health technologies threats
109(1)
5.5.6 Managing vendor security threats
110(1)
5.6 Cybersecurity controls
110(4)
5.6.1 Regulatory authorities
111(1)
5.6.2 Healthcare data protection
111(1)
5.6.3 Planning for cybersecurity
112(2)
5.6.4 Cybersecurity policies
114(1)
5.7 Analysis of cyberattack impacts
114(3)
5.7.1 Revenue loss
114(1)
5.7.2 Financial impact on patients
115(1)
5.7.3 Regulatory costs
116(1)
5.7.4 Cost of downtime
116(1)
5.8 Conclusion
117(1)
Acknowledgment
118(1)
References
118(3)
6 Security challenges and solutions for e-business
121(28)
Anne James
Waleed Bulajoul
Yahaya Shehu
Yinsheng Li
Godwin Obande
Abstract
121(1)
6.1 Introduction
121(1)
6.2 Current security threats in e-commerce
122(4)
6.2.1 Denial of service
123(1)
6.2.2 Unauthorized access
123(1)
6.2.3 Spying attacks
124(1)
6.2.4 Summary of attacks and methods
125(1)
6.3 Current security solutions
126(3)
6.4 New developments in security for e-business
129(11)
6.4.1 Biometrics for authentication
129(2)
6.4.2 Parallelism to increase power and speed of defenses
131(4)
6.4.3 Data mining and machine learning to identify attacks
135(1)
6.4.4 Peer-to-peer security using blockchains
136(1)
6.4.5 Enterprise security modeling and security as a service
137(2)
6.4.6 User education and engagement
139(1)
6.5 Conclusion
140(1)
References
140(9)
7 Recent security issues in Big Data: from past to the future of information systems
149(24)
Julio Moreno
Manuel A. Serrano
Eduardo Fernandez-Medina
7.1 Introduction
149(1)
7.2 Big Data basis
150(4)
7.2.1 Big Data technologies
152(1)
7.2.2 MapReduce
153(1)
7.3 Main challenges in Big Data security
154(7)
7.3.1 Infrastructure security
154(1)
7.3.2 Data privacy
155(1)
7.3.3 Integrity and reactive security
156(1)
7.3.4 Availability
157(1)
7.3.5 Access control and cryptography
158(1)
7.3.6 Data management
158(1)
7.3.7 SGB framework
159(2)
7.4 Scientific community reaction against Big Data security challenges
161(5)
7.4.1 Cloud Security Alliance
161(1)
7.4.2 National Institute of Standards and Technology
162(2)
7.4.3 Information Systems Audit and Control Association
164(1)
7.4.4 Scientific community perspective
164(2)
7.5 Case of use: how to use Big Data for security
166(1)
7.6 Conclusions
167(1)
Acknowledgments
168(1)
References
168(5)
8 Recent advances in unconstrained face recognition
173(16)
Yunlian Sun
Massimo Tistarelli
8.1 Introduction
173(1)
8.2 Real-world databases
174(2)
8.2.1 LFW benchmark
174(1)
8.2.2 PubFig database
175(1)
8.2.3 YTF video database
175(1)
8.2.4 Point-and-shoot face recognition challenge
175(1)
8.2.5 MegaFace dataset
176(1)
8.2.6 IJB-A dataset
176(1)
8.3 Face representations
176(3)
8.3.1 Local appearance features
177(1)
8.3.2 Descriptors learned by encoding local microstructures
178(1)
8.3.3 Aggregation of local appearance features
178(1)
8.3.4 Features learned by deep neural networks
178(1)
8.4 Metric learning approaches
179(1)
8.5 Background information investigation
180(1)
8.6 Pose-invariant face recognition
181(1)
8.7 Performance evaluation
181(1)
8.8 Open issues
182(1)
8.8.1 Large-scale face recognition in real-world security scenarios
183(1)
8.8.2 Pose-invariant face recognition
183(1)
8.8.3 Age-invariant face recognition
183(1)
8.8.4 Dependence on large amount of labeled training data
183(1)
Acknowledgments
183(1)
References
183(6)
Part II Technologies and applications 189(204)
9 Hardware security: side-channel attacks and hardware Trojans
191(24)
Eslam Yahya
Yehea Ismail
9.1 Introduction
191(3)
9.2 Side-channel attacks and their countermeasures
194(12)
9.2.1 Power analysis attack
195(2)
9.2.2 Fault analysis attack
197(2)
9.2.3 Electromagnetic analysis
199(1)
9.2.4 Timing analysis attack
199(1)
9.2.5 Other attacks
200(1)
9.2.6 Asynchronous logic
200(4)
9.2.7 Low-power asynchronous AES core
204(2)
9.3 Malicious hardware: Trojans
206(3)
9.3.1 Hardware Trojan
206(1)
9.3.2 Classification of HT
207(1)
9.3.3 HT detection
208(1)
9.4 Summary
209(1)
References
210(5)
10 Cybersecurity: timeline malware analysis and classification
215(26)
Rafiqul Islam
10.1 Introduction
215(3)
10.1.1 Significance
216(1)
10.1.2 Problems
217(1)
10.2 Timeline malware analysis and classification
218(1)
10.3 Related work
219(1)
10.4 Malware sample collection
220(1)
10.4.1 The methodology
220(1)
10.4.2 Data collection
221(1)
10.5 Cumulative timeline analysis
221(11)
10.5.1 CTA data preprocessing
221(2)
10.5.2 CTA feature vector generation
223(9)
10.6 CTA malware detection method
232(2)
10.6.1 Environment
233(1)
10.6.2 Evaluation process
234(1)
10.7 Experiments and results
234(2)
10.7.1 Timeline classification results using FLF features
234(1)
10.7.2 Timeline classification results using PSI features
235(1)
10.7.3 Timeline classification results using dynamic features
235(1)
10.8 Conclusions and future work
236(1)
References
237(4)
11 Recent trends in the cryptanalysis of block ciphers
241(38)
Ahmed Abdelkhalek
Mohamed Tolba
Amr M. Youssef
11.1 Introduction and overview
241(3)
11.1.1 Symmetric cryptographic primitives
242(2)
11.2 Introduction to block ciphers
244(3)
11.2.1 Block ciphers definition
244(1)
11.2.2 Block ciphers' design
244(3)
11.3 Block ciphers' security
247(3)
11.3.1 Adversary's goal
247(1)
11.3.2 Attack models
248(2)
11.4 Attacks on block ciphers
250(14)
11.4.1 Differential cryptanalysis
251(1)
11.4.2 Linear cryptanalysis
252(1)
11.4.3 Differential-linear cryptanalysis
253(1)
11.4.4 Higher order differential cryptanalysis
253(1)
11.4.5 Truncated differential cryptanalysis
254(1)
11.4.6 Integral cryptanalysis
254(1)
11.4.7 Impossible differential cryptanalysis
255(1)
11.4.8 Zero-correlation cryptanalysis
256(1)
11.4.9 Basic Meet-in-the-Middle cryptanalysis
257(1)
11.4.10 3-Subset MitM technique
258(1)
11.4.11 Splice-and-cut technique
259(1)
11.4.12 Multidimensional MitM and generalized MitM cryptanalysis technique
260(1)
11.4.13 MitM with differential enumeration cryptanalysis
260(1)
11.4.14 Biclique cryptanalysis
261(1)
11.4.15 Unbalanced biclique cryptanalysis
262(1)
11.4.16 Invariant subspace cryptanalysis
263(1)
11.5 Summary
264(1)
References
264(15)
12 Image provenance inference through content-based device fingerprint analysis
279(32)
Xufeng Lin
Chang-Tsun Li
12.1 Introduction
279(1)
12.2 Why not digital watermark?
280(1)
12.3 Why not metadata?
280(2)
12.4 Device fingerprints
282(7)
12.4.1 Optical aberrations
282(2)
12.4.2 CFA and demosaicing
284(3)
12.4.3 Camera response function
287(1)
12.4.4 Quantization table
288(1)
12.4.5 Image thumbnail
288(1)
12.5 Sensor pattern noise
289(15)
12.5.1 Estimation of SPN
290(1)
12.5.2 Source device identification
291(3)
12.5.3 Device linking
294(1)
12.5.4 Source-oriented image clustering
295(4)
12.5.5 Image forgery detection
299(5)
12.6 Summary and outlook
304(1)
References
305(6)
13 EEG-based biometrics for person identification and continuous authentication
311(36)
Min Wang
Hussein A. Abbass
Jiankun Hu
13.1 Brain and brainwaves
311(9)
13.1.1 The human brain
312(1)
13.1.2 Brain activity recording techniques
313(2)
13.1.3 EEG sensors and distribution
315(1)
13.1.4 EEG rhythms and oscillations
316(1)
13.1.5 EEG analysis
317(3)
13.2 EEG as biometric identifiers
320(16)
13.2.1 Criteria
321(4)
13.2.2 Elicitation of brain response and the protocols
325(3)
13.2.3 Feature extraction
328(7)
13.2.4 Classification algorithms
335(1)
13.3 EEG biometrics for continuous authentication
336(4)
13.3.1 Authentication systems
336(1)
13.3.2 Multi-modal biometrics
337(2)
13.3.3 Fusion schemes
339(1)
13.3.4 EEG-based multi-modal continuous authentication
340(1)
13.4 Research directions and challenges
340(1)
References
341(6)
14 Data security and privacy in the Internet-of-Things
347(28)
Delphine Reinhardt
Damien Sauveron
14.1 Risks of IoT
349(2)
14.1.1 Examples of threats to security and privacy
349(2)
14.2 IoT challenges
351(2)
14.2.1 Resource constraints
351(1)
14.2.2 Device heterogeneity
351(1)
14.2.3 Mobility
352(1)
14.2.4 Heterogeneity of access levels
352(1)
14.2.5 Remote features
352(1)
14.2.6 Deployment environment
353(1)
14.2.7 Transparent deployment and lack of interfaces
353(1)
14.3 Security and privacy solutions for IoT
353(11)
14.3.1 Solutions for the IoT layer
354(1)
14.3.2 Solutions for the IoT communication layer
355(1)
14.3.3 Solutions for IoT services and applications layer
356(8)
14.4 Human factors in IoT security and privacy
364(1)
14.5 Summary
365(1)
References
366(9)
15 Information security algorithm on embedded hardware
375(18)
Raul Sanchez-Reillo
15.1 Introduction
375(1)
15.2 Classification of embedded systems
376(2)
15.2.1 Application specific integrated circuits
376(1)
15.2.2 Field programmable gate arrays
376(1)
15.2.3 Microprocessor-based embedded systems
377(1)
15.2.4 Single-board computers
377(1)
15.2.5 General purpose mobile platforms
378(1)
15.3 Security requirements and mechanisms
378(8)
15.3.1 Information exchange
379(4)
15.3.2 Storage security
383(2)
15.3.3 User- and service-related security
385(1)
15.3.4 Hardware vulnerabilities
385(1)
15.4 Implementation of security mechanisms in embedded systems
386(3)
15.4.1 Software-based implementations
386(1)
15.4.2 The use of a security co-processor
387(1)
15.4.3 Smart cards and common criteria
388(1)
15.5 Conclusion
389(1)
References
389(4)
Index 393
Ali Ismail Awad is an Associate Professor in the Department of Computer Science, Electrical and Space Engineering, Lulea University of Technology, Sweden. He is also an Assistant Professor in the Electrical Engineering Department, Faculty of Engineering, Al Azhar University, Qena, Egypt. He is an IEEE Senior Member, and his research interests include information security, with a focus on biometrics, pattern recognition and computer networks.



Michael Fairhurst is Professor of Computer Vision in the School of Engineering and Digital Arts at the University of Kent, UK. His research interests have a focus on the fundamental processes of image analysis and pattern recognition, with particular emphasis on applications in security and, especially, biometrics, and he is a Fellow of the IAPR. He is Editor-in-Chief of the IET Biometrics Journal and Series Editor of the IET Book Series on Advances in Biometrics.