On this page you will find an overview of privacy policies, and their assessment by the privacy board, for projects that are no longer current.
Privacy Policy | Privacy Policy Evaluation | Project description |
|---|---|---|
The IRMA application utilises a wide range of identity attributes published by authoritative bodies. Data about the user is encrypted and stored locally in the IRMA app on the user's phone. Overall, IRMA processes as little data as possible, enabling users to retain control of what identity information they reveal, share or use for verification purposes. We manage the central infrastructure that supports the decentralised system. An initial attribute is issued on the basis of the user's e-mail address. That enables the user to use, deactivate and restore the IRMA app. | ||
The aim of the RegCheck pilot is to determine the best way of automatically identifying suspect registrations. The longer-term goal of the work is to enable the identification of suspect registrations, for further investigation by our Support team. The suspect registrations targeted by RegCheck are registrations where the registrant has malicious intentions (e.g. phishing or setting up a fake webshop). Registrations that involve erroneous data, but appear to be legitimately motivated are outside the scope of the study. | ||
DEX is a system that provides more insight into the evolution of the .nl ecosystem and helps to tackle domain name abuse. DEX makes it easy to browse information about one or more domain names. It enables our Support team to investigate suspect domain names more effectively and more efficiently. Another valuable feature of DEX is the ability to identify other suspect domain names associated with a domain name linked to abuse. | ||
SIDN Labs is working on a prototype system for scanning websites for the use of trusted logos, such as the logos of banks, accreditation schemes and government entities. The ability to recognise such logos would be significant, since fraudsters use them to make their websites appear trustworthy. So, for example, the logo of a trusted entity may be used on a phishing site. The aims of the LogoMotive pilot are (a) to continue the development of SIDN's prototype logo detection system, (b) to gather information about the use of logos on websites linked to .nl domain names, and (c) to establish whether it is possible to automatically distinguish between malicious and benign logo use. | ||
Privacy Policy Evaluation SIDN-DNS Belgium Fake Webshop Intel Pilot | SIDN Labs is working on a prototype system for scanning websites for the use of trusted logos, such as the logos of banks, accreditation schemes and government entities. The ability to recognise such logos would be significant, since fraudsters use them to make their websites appear trustworthy. So, for example, the logo of a trusted entity may be used on a phishing site. The aims of the LogoMotive pilot are (a) to continue the development of SIDN's prototype logo detection system, (b) to gather information about the use of logos on websites linked to .nl domain names, and (c) to establish whether it is possible to automatically distinguish between malicious and benign logo use. | |
In this study, we want to measure and analyse NTP traffic on our TimeNL NTP servers. By doing so, we hope to learn more about the behaviour and performance of NTP clients, so that we can improve the resilience and security of our NTP service. | ||
JITTER is a prototype system that uses machine learning to generate warnings regarding domain names that may have been compromised, enabling the placement of malicious content (e.g. phishing content). The system facilitates the identification of abuse before the relevant domain names appear in abuse lists. | ||
COMAR was a project in which we investigated the possibility of automatically distinguishing between domain names registered by cybercriminals for malicious purposes, and legitimately registered domain names that had been hacked by exploiting vulnerabilities in web applications. The project was intended to yield results that registrars, ccTLD registries and others could use to optimise anti-abuse processes. | ||
Privacy Policy Evaluation Proactive recognition of domain abuse | MSc thesis project aimed at the identification of malicious domain name registrations. The project involved the analysis of information such as domain registration data. Its results were used in follow-up projects. | |
CyberSterk is a cybersecurity service we developed for SMEs. For the service to work properly, certain personal and other data had to be processed. | ||
In the Resolver Reputation project, we used ENTRADA to scan DNS query data for certain patterns associated with botnet clients, i.e. IP addresses at which infected systems were operating. Whenever suspicious behaviour involving a Dutch IP address was detected, we reported the address in question to the Abuse Information Exchange. | ||
The JTIE project was intended to facilitate the exchange of information about malicious domain names between us and the Fraud Help Desk. It involved the analysis of DNS traffic associated with suspect domain names, for example. | ||
An internship research project involving the analysis of ENTRADA data (DNS data) to identify patterns indicative of abuses such as phishing, IP spoofing and botnet activities. | ||
In 2017 and 2018, we partnered with NBIP to investigate the impact of DDoS attacks on the Dutch business community. NBIP provided us with data on DDoS attacks (IP addresses, times), and we combined that data with our own data to shed light on the attack contexts. | ||
For a 'lean' experiment with CyberSterk, we set up a test website with customer data collection functionality. The data in question consisted of potential customers' e-mail addresses. | ||
For research purposes, we exchanged abuse detection patterns with DK Hostmaster. Sharing the patterns meant that DK Hostmaster's data could be scanned for forms of abuse previously identified in our data, and vice versa. | ||
Privacy Policy Evaluation University of Amsterdam malware detection | Researchers from the University of Amsterdam attempted to use graph theory to identify previously unknown malware domain names. | |
This privacy policy covers data processing for the MINIONS project, in which data collected with honeypots was used to analyse the distribution of the Mirai botnet. | ||
Privacy Policy Evaluation Ransomware Deployment Analysis met Tesorion | The purpose of this project was to find a way of identifying networks infected with certain malware by monitoring DNS traffic. That involved analysing DNS queries about .nl domain names. |