Our research addresses the question: What are the conditions of the UK's cyber threat landscape? In addressing this we focus on detectable, known and therefore potentially preventable cyber threats, specifically those that are identifiable by the types of malicious scanning activities they exhibit. We have chosen this approach for two reasons. First, as is evidenced herein, the vast majority of cyber threats affecting the lives and business endeavours of UK citizens are identifiable, preventable threats. Thus the potential exists to better improve UK cyber defence by improving how citizens are supported in preventing, detecting and responding to cyber threats. Achieving this requires an evidence base to inform policy makers. Second, it is potentially useful to build a quantifiable evidence base of the known threat space - that is to say detectable, identifiable and therefore potentially preventable cyber threats - to ascertain if this information may also be useful when attempting to detect the emergence of more novel cyber threats. This research presents an analysis of malicious internet scanning activity collected within the UK between 1st December 2020 and the 30th November 2021. The data was gathered via a custom automated system which collected and processed data from Greynoise, enriched this via Shodan, cross referencing it with data from the Office of National Statistics and proprietorial data on UK place names and geolocation.
翻译:我们的研究针对的问题有:英国网络威胁环境的条件是什么? 在解决这一问题时,我们注重可探测的、已知的和因此可能可预防的网络威胁,特别是由它们所展示的恶意扫描活动类型所识别的网络威胁。我们之所以选择这一方法,有两个原因。首先,正如本文所证明的那样,影响英国公民生命和商业努力的绝大多数网络威胁是可以识别的、可预防的威胁。因此,通过改进公民在预防、发现和应对网络威胁方面获得支持的方式,可以更好地改进英国网络防御。要实现这一目标,需要有一个证据库来通知决策者。第二,建立已知威胁空间的可量化证据库,即可检测、可识别和因此可能可预防的网络威胁,以确定在试图发现新的网络威胁时,这些信息是否也有用。这项研究分析了在2020年12月1日至2021年11月30日期间在联合王国境内收集的恶意互联网扫描活动。数据是通过一个定制自动化系统收集的,该系统通过Shodan收集并处理来自Greynoise的数据,通过Shodan加以补充,将这些数据与国家统计局的地理名称和地产数据相互参照。</s>