Data sharing and data harvesting practices not only infringe the privacy rights of individuals but cause significant harms to others as well. Emissions of personally sensitive behavioural data are...Show moreData sharing and data harvesting practices not only infringe the privacy rights of individuals but cause significant harms to others as well. Emissions of personally sensitive behavioural data are leaked into the digital economy causing damage to social practices and destabilizing political and informational ecosystems. Data pollution is like industrial pollution, and environmental law suggestions can offer solutions to the problem. Will a Pigouvian tax on data extraction limit or constrain the negative externalities of data pollution? This explorative research aims to investigate whether a data pollution tax can operate as a regulatory instrument to curb data pollution and whether citizens support this measure. Do citizens support a data pollution tax designed so that harms to others, affecting their core human capabilities, will be taxed as a matter of principle? Suppose excessive (corporate) data sharing and extraction practices that cause harm to others will be taxed. Do individuals expect that persons and corporations will change their data transmission practices? Our survey findings show that (United States) citizens consider that harms caused by data pollution should be taxed. Respondents will also substantially decrease their data pollution behaviour once a tax is imposed. However, and to our surprise, our research findings also lay bare a possible ‘bad behaviour paradox’: the more significant the harm caused by some instances of data pollution, the less willing people are to change behaviour relative to the tax imposed.Show less
This report describes the results of the research in the context of the Master's degree in Cyber Security. This study researched the problem that public tenders contain information that can be...Show moreThis report describes the results of the research in the context of the Master's degree in Cyber Security. This study researched the problem that public tenders contain information that can be collected by hackers during their preparation for a cyber-attack. Adversaries can easily access this information and abuse it against the tendering organizations. Therefore, the main goal of this research is to establish guidelines aimed at identifying and reducing sensitive information in tenders, in order to prevent that malicious parties gather and use this information in the preparation of cyber-attacks against tendering organizations. To this end, the various concepts of open data, procurement, reconnaissance, cyber kill chain, and open source intelligence were examined. In addition, interviews were held to both identify the risks for tendering organizations due to the above identified problem and to evaluate on the established guidelines. The research results have shown that the information in tenders is public due to the principles on which the rules regarding tenders are based. This is to offer fair opportunities to companies to win contracts through tenders. Due to the public nature of information in tenders, the comparison can be made with the concept of open data. As a result, the risks inherent to open data, such as abuse by malicious parties, also apply to information in tenders.Further research into the reconnaissance activities of hackers has made it clear that hackers are looking for specific types of information in preparation for cyber-attacks. It has been determined through document analysis on real tenders and interviews with security professionals that these types of information occur in tenders. This means that malicious parties can use tenders to collect information about organizations that is relevant for the preparation of cyber-attacks, against the tendering organizations. As a result, the tendering organizations face risks with regard to the confidentiality, integrity and availability of company assets. In particular, the likelihood that such risks arise is increased because the information is easily accessible to malicious parties. In order to prevent this, guidelines have been established. These guidelines should be used in follow-up research where a final solution is created that implements the described functionalities of the guidelines. The established guidelines focus in particular on identifying and reducing information that is relevant to hackers in tenders, before the tenders are made public. In this way the risks for tendering organizations can be prevented because this information can no longer be collected by malicious parties. The likelihood of the identified risks occurring is reduced. In addition, techniques have been suggested for these guidelines on which they can be implemented.The techniques regular expressions, text mining, comparison with known information, optical character recognition, and image recognition are discussed. Furthermore, guidelines have also been established that focus on the practical side of a final solution and the fact that this solution must be used in an existing context: people, processes and organizations. The guidelines and the results of the study were evaluated in interviews with senior purchasers. From these interviews it can be concluded that a solution based on the guidelines is of added value in practice in order to reduce sensitive information in tenders and prevent risks for tendering organizations. The results of this research thus result in recommendations for follow-up research, where the aim is to create an automated solution based on the guidelines that have been established.Show less
Security operations centers prevent, detect, and respond to security alerts and incidents. The ongoing digitalization and expansion of digital information pose a serious concern for security...Show moreSecurity operations centers prevent, detect, and respond to security alerts and incidents. The ongoing digitalization and expansion of digital information pose a serious concern for security operations centers. This concern is whether or not security operations centers can process and analyze the multiple information from systems and devices to prevent and detect security alerts of incidents. This paper analyses using artificial intelligence within a security operations center to overcome this concern. In the analyses, the challenges of using artificial intelligence within an organization are taken into account. The theoretical possibilities,including the challenges, are compared against the current situation of Dutch governmental organizations. This results in a gap analysis that can support the organizations to identify the next steps to address the above-mentioned concern.Show less
