# The Privacy Flag Observatory: A Crowdsourcing Tool for Real Time Privacy Threats Evaluation
## 2 Related Works  
The need for a systematic monitoring of cyber attack trends is well documented in numerous works (see, e.g., [6]). A large body of academic publications, as well as a significant number of technical reports and white papers from governmental agencies and the private sector, focuses on the application of technical, legal and human safeguards to enhance citizens' privacy and security in the cyberspace [7]. As the scope of digital security and privacy is very broad, in our work, we focus on monitoring platforms and, in particular, observatories for collecting, archiving, analyzing and presenting security and privacy-related information to the broader public. Our aim is to raise awareness and promote best practices. Therefore, our work's goals differ from the majority of real-time security monitoring platforms that are described as _Security Operation Centers_ (SOCs). SOCs operate in the context of Managed Services from various cybersecurity vendors and aim at highlighting imminent threats, issuing early warnings and taking the appropriate measures when needed. Their goal, however, is not to evaluate the existing applications with respect to appropriate privacy and security metrics in order to educate and protect users in the long term (see [8, 9]). Thus, the Privacy Flag observatory, as all the other observatories,is not designed to detect ongoing cyberthreats, although it can, but, rather, to follow the trends on the adoption of privacy and security aware technologies. Closest to our work is the Mozilla Observatory ([[https://observatory.mozilla.org](https://observatory.mozilla.org)]([https://observatory.mozilla.org](https://observatory.mozilla.org)), accessed on 30 November 2022), which analyzes websites for various security issues. The Mozilla Observatory focuses on the use of cryptographic technologies for real-time data encryption in the web. Additionally, this observatory performs various other checks including cookies, Cross-Origin Resource Sharing (CORS), Content Security Policy (CSP) and X-XSS-Protection. However, it does not take into account the risk of obsolete and deprecate technologies while it does not contain modules to assess the mobile applications which access the website. Nevertheless, the Mozilla Observatory is a mature and robust framework which has assessed millions of websites and helped more than 300,000 web administrators to address various privacy and security issues in their websites. Another important observatory is the Qualys SSL Pulse. It performs very analytical and focused investigation of SSL/TLS protocols of websites and can identify possible vulnerabilities that lead to attacks such as BEAST, Heartbleed, POODLE and CRIME, which will be discussed later in more detail. The Qualys SSL Pulse provides detailed statistics and summary reports with respect to the usage of the TLS protocol [10]. The Alexa company was known for its extensive data collection on every aspect of web activity. One of the outcomes of this undertaking was the accumulation of a vast dataset, known as the _Alexa Million_, containing technical data on the encryption methods of hundreds of thousands of websites. Although this dataset is no longer updated, it is still available in several repositories. Together with the Mozilla Observatory and the Qualys SSL Labs, the Alexa dataset has helped numerous researchers in obtaining the necessary data for their investigations (see, e.g., [11, 12, 13]). Furthermore, this dataset has also facilitated several high-impact research works (see [12]). Another remarkable effort was the design of the Cyber Threat Observatory for Computer Emergency Response Teams (CERT) [14]. This observatory combines several useful components in a unified framework. These elements include security advisories, Common Vulnerabilities and Exposures (CVEs), Indicators of Compromise (IoCs), social media aggregation and even chat/messaging functionality for direct communication among CERT members.