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E-grāmata: Cybersecurity and Cognitive Science

Edited by (School of Psychology, Bond University, Robina, Queensland, Australia)
  • Formāts: EPUB+DRM
  • Izdošanas datums: 27-May-2022
  • Izdevniecība: Academic Press Inc
  • Valoda: eng
  • ISBN-13: 9780323906968
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Cybersecurity and Cognitive SciencePalielināt
  • Formāts: EPUB+DRM
  • Izdošanas datums: 27-May-2022
  • Izdevniecība: Academic Press Inc
  • Valoda: eng
  • ISBN-13: 9780323906968
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Cybersecurity and Cognitive Science provides the reader with multiple examples of interactions between cybersecurity, psychology and neuroscience. Specifically, reviewing current research on cognitive skills of network security agents (e.g., situational awareness) as well as individual differences in cognitive measures (e.g., risk taking, impulsivity, procrastination, among others) underlying cybersecurity attacks. Chapters on detection of network attacks as well as detection of cognitive engineering attacks are also included. This book also outlines various modeling frameworks, including agent-based modeling, network modeling, as well as cognitive modeling methods to both understand and improve cybersecurity.
  • Outlines cognitive modeling within cybersecurity problems
  • Reviews the connection between intrusion detection systems and human psychology
  • Discusses various cognitive strategies for enhancing cybersecurity
  • Summarizes the cognitive skills of efficient network security agents, including the role of situational awareness
Contributors xi
I Social engineering, security, and cyber attacks
1 Social engineering attacks and defenses in the physical world vs. cyberspace: A contrast study
Rosana Montanez
Adham Atyabi
Shouhuai Xu
1 Introduction
3(4)
2 Terminology and methodology
7(3)
3 Characterizing social engineering attack model, techniques, and defenses in the physical world
10(7)
4 Characterizing social engineering attack model, techniques, and defenses in cyberspace
17(14)
5 Contrast analysis
31(2)
6 Conclusions
33(10)
Acknowledgments
34(1)
References
34(9)
2 A dual integrated dynamic intrusion detection system (DID-IDS) for protection against network and social engineering attacks
Abubakar Bello
Hany Alashwal
Ahmed A. Moustafa
1 Introduction
43(1)
2 Detection of information system and social engineering intrusion attacks
44(1)
3 Prior computer system intrusion detection systems
45(1)
4 Prior social engineering intrusion detection methods
45(1)
5 A new dual integrated dynamic intrusion detection system (DID-IDS)
46(5)
References
48(3)
3 Working from home users at risk of COVID-19 ransomware attacks
Anthony An Duong
Abubakar Bello
Alana Maurushat
1 Introduction
51(2)
2 Overview of ransomware
53(4)
3 Challenges and issues with ransomware
57(3)
4 Ransomware attack vectors
60(4)
5 Existing defense mechanism and control gaps
64(3)
6 Mitigation model against ransomware
67(13)
7 Regular and consistent data backup
80(1)
8 Conclusion
81(8)
References
83(6)
4 Individual differences in cyber security behavior using personality-based models to predict susceptibility to sextortion attacks
Veronica Power
Abubakar Bello
1 Introduction
89(1)
2 Social engineering and cyber sextortion
90(3)
3 Personality-based models
93(3)
4 Current study
96(1)
5 Method
97(4)
6 Results
101(7)
7 Discussion
108(3)
8 Conclusion
111(4)
References
111(4)
5 Deconstructing security and privacy issues: The development of a logic for capturing mismorphisms
Vijay H. Kothari
Prashant Anantharaman
Sean W. Smith
1 Introduction
115(3)
2 A brief background on semiotics
118(2)
3 A semiotic model for mismorphisms
120(1)
4 Beyond semiotic triads
121(1)
5 A logic for mismorphisms
122(4)
6 A preliminary catalog of mismorphisms
126(4)
7 Future work
130(3)
8 Conclusion
133(6)
References
133(6)
II Behavioral studies of cybersecurity
6 Are you anonymous? Social-psychological processes of hacking groups
John McAlaney
1 Introduction
139(1)
2 Context
140(2)
3 Social identity
142(2)
4 Interpersonal perception
144(2)
5 Group processes
146(5)
6 Informed decision making
151(1)
7 Conclusion
152(5)
References
152(5)
7 On the relation between hacking and autism or autistic traits: A systematic review of the scientific evidence
Jennifer Wagner
Samuela Bolgan
Elena Rusconi
1 Introduction
157(13)
2 Methods
170(1)
3 Results
171(18)
4 Conclusions and future directions
189(8)
References
192(4)
Further reading
196(1)
8 An introduction to cyberbullying
Peter J.R. Macaulay
Lucy R. Betts
James Stiller
Blerina Kellezi
1 A brief overview of traditional bullying
197(1)
2 The emergence of digital technologies and cyberbullying
198(1)
3 Definitional issues of cyberbullying
199(4)
4 Unique features of cyberbullying
203(2)
5 The different forms of cyberbullying
205(1)
6 The prevalence of cyberbullying
206(1)
7 The impact of cyberbullying
207(1)
8 Conclusion
208(7)
References
209(6)
9 The impact of cyberbullying across the lifespan
Lucy R. Betts
1 Introduction
215(3)
2 The impact of involvement in cyberbullying during the elementary years
218(1)
3 The impact of involvement in cyberbullying during adolescence
219(6)
4 The impact of involvement in cyberbullying during emerging adulthood
225(1)
5 The impact of involvement in cyberbullying during adulthood
226(2)
6 Challenges associated with understanding the impact of cyberbullying
228(1)
7 Conclusion
229(6)
References
230(5)
10 Cyber situational awareness issues and challenges
Ulrik Franke
Annika Andreasson
Henrik Artman
Joel Brynielsson
Stefan Varga
Niklas Vilhelm
1 Introduction
235(3)
2 The technological perspective
238(6)
3 The socio-cognitive perspective
244(3)
4 The organizational perspective
247(2)
5 Reasoning about adversarial behavior
249(5)
6 Research directions
254(1)
7 Conclusions
255(1)
Acknowledgments
256(1)
Appendix A Interview methodology
256(11)
References
259(8)
11 Development and application of the Information Security Core Human Error Causes (IS-CHEC) technique
Mark Evans
Ying He
Leandros Maglaras
Helge Janicke
1 Introduction
267(2)
2 IS-CHEC technique
269(20)
3 General discussion
289(2)
4 Conclusions and future work
291(8)
References
292(7)
III Machine learning and modeling applications to cybersecurity
12 Machine learning for the security of healthcare systems based on Internet of Things and edge computing
Devrim Unal
Shada Bennbaia
Ferhat Ozgur Catak
1 Big data in health care
299(5)
2 Privacy-preserving machine learning
304(7)
3 Securing IoMT from ML-based attacks
311(10)
Acknowledgments
318(1)
References
318(3)
13 Lying trolls: Detecting deception and text-based disinformation using machine learning
Alex V. Mbaziira
Maha F. Sabir
Micheline Al Harrack
1 Introduction
321(1)
2 Related work
322(2)
3 Methodology
324(8)
4 Results and analysis
332(4)
5 Conclusion
336(3)
References
337(2)
14 Modeling the effects of network size in a deception game involving honeypots
Harsh Katakwar
Shashank Uttrani
Palvi Aggarwal
Varun Dutt
1 Introduction
339(3)
2 Deception game
342(1)
3 Experiment
343(2)
4 Results
345(2)
5 The IBL model
347(3)
6 Discussion
350(7)
References
353(4)
15 Computational modeling of decisions in cyber-security games in the presence or absence of interdependence information
Zahid Maqbool
V.S. Chandrasekhar Pammi
Varun Dutt
1 Introduction
357(3)
2 Background
360(1)
3 Experiment
361(1)
4 Results
362(1)
5 The IBL model
363(2)
6 Execution of IBL model in the security game
365(1)
7 Results
366(1)
8 Discussion
367(2)
9 Conclusion
369(2)
Acknowledgment
369(1)
References
369(2)
Index 371
Dr. Ahmed Moustafa is the Head of School of Psychology and Professor of Psychology and Computational Modeling at Bond University, Australia. He obtained his BSc in Mathematics and Computer Science at Cairo University, Egypt, and his PhD in Cognitive Science at the University of Lafayette, USA. Dr. Moustafa specializes in computational and neuropsychological studies of addiction, schizophrenia, Parkinsons disease, PTSD, depression, and Alzheimers disease. He is the Editor-in-Chief of Discover Psychology (Springer) and has edited ten books, including Elseviers Cognitive, Clinical, and Neural Aspects of Drug Addiction; The Psychology and Neuroscience of Impulsivity; Cognitive and Behavioral Dysfunction in Schizophrenia; Mental Health Effects of COVID-19; Alzheimers Disease; Cybersecurity and Cognitive Science; Big Data in Psychiatry and Neurology; The Nature of Depression; and Social Cognition in Psychosis.
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