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.
1. Chapter 8 : An introduction to cyberbullying - p. Page 192 2. Chapter 9 : The impact of cyberbullying across the lifespan - p. Page 209 3. Chapter 10 : Cyber situational awareness issues and challenges - p. Page 230 4. Chapter 11 : Development and application of the Information Security Core Human Error Causes (IS-CHEC) technique - p. Page 259 5. Chapter 12 : Machine learning for the security of healthcare systems based on Internet of Things and edge computing* - p. Page 292 6. Chapter 13 : Lying trolls: Detecting deception and text-based disinformation using machine learning - p. Page 318 7. Chapter 14 : Modeling the effects of network size in a deception game involving honeypots - p. Page 337 8. Chapter 15 : Computational modeling of decisions in cyber-security games in the presence or absence of interdependence information - p. Page 353 9. Index - p. Page 369
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.
1. Chapter 8 : An introduction to cyberbullying - p. Page 192 2. Chapter 9 : The impact of cyberbullying across the lifespan - p. Page 209 3. Chapter 10 : Cyber situational awareness issues and challenges - p. Page 230 4. Chapter 11 : Development and application of the Information Security Core Human Error Causes (IS-CHEC) technique - p. Page 259 5. Chapter 12 : Machine learning for the security of healthcare systems based on Internet of Things and edge computing* - p. Page 292 6. Chapter 13 : Lying trolls: Detecting deception and text-based disinformation using machine learning - p. Page 318 7. Chapter 14 : Modeling the effects of network size in a deception game involving honeypots - p. Page 337 8. Chapter 15 : Computational modeling of decisions in cyber-security games in the presence or absence of interdependence information - p. Page 353 9. Index - p. Page 369
