ObjectivesReview the evidence provided by victim surveys in order to provide a rough estimate of the personal crime prevalence of the main types of cybercrime.MethodsWe performed a search in databases, searched online, and contacted several Offices for National Statistics in Europe and selected surveys that provided information about individual victims of crime which were representative for a general population. Six types of cybercrime have been distinguished, namely online shopping fraud, online fraud banking/payment, other cyber fraud (such as advanced fee fraud), cyber threats/harassment, malware, and hacking. For every survey the questions on cybercrime are presented and the crime prevalence estimates are compared.ResultsNine surveys were included. Annual crime prevalence rates ranged from 1 to 3% for online shopping fraud, from less than 1 to 2% for online banking/payment fraud. Less than 1% of the population is a victim of other types of fraud and a maximum of 3% of the population experiences some sort of online bullying such as stalking (1%) or threatening (1%). 1–6% is a victim of hacking. The estimates for being a victim of malware range from 2 to 15%. For all offences it cannot be estimated how much of the differences are due to variation in methods and questioning between the studies or real differences between countries or change over time.ConclusionsAs yet there have been very few well performed randomised sampled studies on cybercrime amongst the general population. Cybercrime prevalence (and its trend) can only be well measured if the questions are frequently updated and adequately address new aspects of cybercrime. To adequately monitor cybercrime in the future it is advisable to develop some fairly abstract main categories that are of durable validity, whilst allowing for up-to-date illustrations. Furthermore, ideally the questioning in the ongoing surveys in the different countries should be standardised and there should be a uniform categorisation of the different cyber offences. A screening question in order to permit more accurate dating is essential to reduce telescoping bias. Surveys should ask about the impact on or damage to the victims.

中文翻译：

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欧洲网络犯罪的受害者：受害者调查回顾

目的审查受害者调查提供的证据，以便粗略估计主要网络犯罪类型的人身犯罪发生率。方法我们在数据库中进行搜索，在线搜索并与欧洲国家统计局联系，并选择了一些调查来提供代表一般人口的个别犯罪受害者的信息。区分了六种网络犯罪，分别是在线购物欺诈，在线欺诈银行/付款，其他网络欺诈（例如预付费欺诈），网络威胁/骚扰，恶意软件和黑客攻击。对于每项调查，都会提出有关网络犯罪的问题，并对犯罪发生率的估计值进行比较。结果包括九项调查。在线购物欺诈的年犯罪率介于1％至3％之间，从不到1％到2％（用于在线银行/付款欺诈）。不到1％的人口是其他类型欺诈行为的受害者，最多3％的人口遭受某种在线欺凌行为，例如跟踪（1％）或威胁（1％）。1–6％是黑客攻击的受害者。估计是恶意软件的受害者的范围为2％到15％。对于所有犯罪，无法估计多少差异是由于研究之间方法和问题的差异，国家之间的实际差异或随着时间的变化而造成的。结论迄今为止，在网络犯罪中，进行网络犯罪的随机抽样研究很少人口。只有对问题进行经常更新并充分解决网络犯罪的新问题，才能很好地衡量网络犯罪的发生率（及其趋势）。为了在将来充分监视网络犯罪，建议开发一些具有持久有效性的相当抽象的主要类别，同时允许提供最新插图。此外，理想情况下，应在不同国家进行的调查中对提问进行标准化，并对不同的网络犯罪进行统一的分类。为了允许更精确的约会，筛选问题对于减少伸缩性偏见是必不可少的。调查应询问对受害者的影响或损害。理想情况下，应该对不同国家/地区正在进行的调查提出的疑问进行标准化，并且应对不同的网络犯罪进行统一的分类。为了允许更精确的约会，筛选问题对于减少伸缩性偏见是必不可少的。调查应询问对受害者的影响或损害。理想情况下，应该对不同国家/地区正在进行的调查提出的疑问进行标准化，并且应对不同的网络犯罪进行统一的分类。为了允许更精确的约会，筛选问题对于减少伸缩性偏见是必不可少的。调查应询问对受害者的影响或损害。