Index

A

  • Abdulmutallab, Umar Farouk, 178
  • Administrators, locking out, 10
  • Adversaries, 47–68
    • adversarial machine learning (AML), 164–165
    • airline industry's response to hijacking, 175–179
    • botnets, 77
    • cybersecurity hygiene importance and, 63–66
    • defense against, 54–59
    • employees' compliance as response for, 62–63
    • employees' need for awareness of, 59–61
    • hackers' motivation, 30–33
    • hacking example, 1–8, 82
    • personal responsibility for protection from, 14–17
    • phishing by, 53, 60, 61, 156–158
    • proactive response for, 61–62
    • ransomware threat, 31
    • ransomware vs. WannaCry, 132–133
    • social engineering, example, 48–52
    • social engineering, types, 53–54
    • spectators and influence on outcome, 17–19
    • taking precautions against, 8–13
    • W.I.S.D.O.M., defined, 19–21
    • worms, 132–133
  • Advertising, paying directly for, 11–12
  • Airline industry, 169–185
    • culture of security vs. past practices, 172–175
    • hijacking issues of past, 175–179
    • as modern-day mundane routine, 169–171
    • reaction to safety problems in, 182–184
    • safety checks performed by, 179–182
  • Angelou, Maya, 124
  • Animal behavior, herd instinct and, 187–190
  • Apricorn, 29
  • Artificial intelligence (AI)
    • adversarial machine learning (AML), 164–165
    • detection tools, 10
    • to identify threats, 163–166
    • used in social engineering, 62
  • Audit, of third-party security practices, 144–145
  • Automation, cybersecurity industry and, 33–38
  • Automotive Edge Computing Consortium, 78
  • Autonomous cars, weaponizing, 78–79
  • Aviation Safety Network, 181
  • AWS, 81

B

  • Bed bug metaphor, 137–138
  • Behavioral ...

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