这是最后一节课，这门课没有实验课，然后还只有6周的课时，实在是令人不满意，最后一节课五个话题
Criminology 犯罪学
Cybercriminology 网络犯罪学
Victimology 受害者学
Cybercriminal Profiling 网络犯罪分析介绍
Causation 原因，诱因
Criminology
Criminology is “the scientific study of the causes of crime, the scope of crime, the responses to crime by the public, media, social and political institutions, and criminal justice systems and the ways to control, mitigate and prevent crime” (Maras, 2017)
Cybercriminology
• The study of cybercrime through the lens of criminology 从犯罪学的角度来研究网络犯罪
• Applies and tests criminological theories to cybercrimes 应用和测试犯罪逻辑理论到网络犯罪
• Investigates the nature and extent of cybercrime 调查网络犯罪的本质和内容
• Evaluates efficacy of mechanisms for control, mitigation, prevention 评估控制消除预防机制的功效
• Still an immature field of investigation 仍然是一个不成熟的研究领域
• Blurred lines between traditional and cybercrime – what is not impacted by ICT today? 仍然是模糊不清的线在网络犯罪和传统之间
(e.g.: burglary – traditional crime however assisted by a social media post suggesting the occupant was on holiday).
Victimology 受害者学
• Physical characteristics 物理角色
• Behaviour prior, during and after a crime 犯罪前中厚的行为习惯
• Medial, psychological, criminal history
• Home, family, work
• Social life, friends, associates
• Explores how a victim knowingly 明知的 or unwittingly 糊里糊涂的 contributes to the victimisation (harm)
• Cybervictimology: study of online victimization
• Primary - direct target – owner of hacked account, secondary – indirect target – customer of company whose database is breached, tertiary victims – impact on society – rising prices as a result of digital piracy (Maras, 2017)
• Individuals, organisations, societies, nations
• Cybercrime can cause financial, professional, psychological, and social harm to the victim
• Cyberstalking victims report “abrupt changes in sleep and eating patterns, nightmares, hypervigilance, anxiety, helplessness, fear for safety” (Pittaro, 2007)
• Increased fear - influences behaviour (e.g.: fear of IT theft – less use of online transactions?)
• Can we use profiling to determine who might be a victim?
• Do demographics matter?
Victim Profiling is an attempt to identify common factors associated with cybercrime
• Gender
• Mixed research results
• Some research shows correlation others find age is not a statistically significant predictor (Ngo, 2011) – need to be more crime specific
• Females more likely victims of cyberstalking and cyberharassment
• Males more likely to be impacted by cyberfraud, cybertheft and scams (FBI, 2014)
• Age
• Mixed results again – specificity of crime?
• Individuals 40-59 yrs. old - more likely to experience online scams (FBI, 2015); Type of fraud changes results further
• Malware infection – age a good predictor – >youth 24
• Children <10 more likely to be targeted by online child sexual predators (IWF, 2020)
• Children 13 and 14 most targeted by online sexual exploitation (CEOP, 2013)
• Race
• Malware infection – Caucasians less likely to be victims than other races (Ngo, 2011)
• Interpersonal cybercrime – Caucasians more likely to be victims than other races
(cyberstalking, cyberharassment) (CEOP, 2014)
• Race has no impact (Hinjuda & Patchin, 2008)
• Marital/Relationship Status
• More mixed results
• No association to cyber victimization (Ngo, 2011)
• What about romance schemes, cyberstalking, cyberharassment? – other studies
contradict the above
• Education, Income, Employment
• Bad news if you are educated, wealthy, employed full time (Maras, 2017)
• Or maybe not employed full time (Ndubueze, 2003)
