An Unsupervised Approach for False Alarm Filtering in Rule-based NIDS

To detect malicious activities in a network, intrusion detection systems are used. Even though these solutions are widely deployed for this purpose they have one serious shortcoming which is the huge amount of false alarms that they are generating. Different measures are taken to tackle this problem such as manually changing the settings of the...

Investigating Target Selection and Financial Impact of Service Fraud: An empirical research into criminal activities on underground markets and their implications for businesses

A portion of the digital fraud occurring on the dark web comprises the illegal exchange of vouchers, coupons, and stolen accounts, defined in this research as service fraud. Despite its existence, this type of fraud had not been previously explored. This thesis employs a quantitative approach to examine which company characteristics influence...

Who is next?: Identifying characteristics of European banks that are key in influencing the target selection of banking malware.

The European financial sector is a frequent victim of banking malware leading to massive losses. It appears that not all customers’ banks are equally attractive targets among cybercriminals who deploy banking malware. This research established a comprehensive regression model explaining why certain banks are more attractive to cybercriminals....

Private and public information disclosure to improve cybersecurity: A field experiment to incentivise compliance with anti-spoofing best practices

Exploring effective notification mechanisms for infected IoT devices

Many Internet of Things (IoT) devices that are currently on the market lack security and therefore many of them got infected with malware to launch powerful distributed denial of service (DDoS) attacks. Notifications from Internet Service Providers (ISPs) to their customers play a crucial role in the fight to clean up the malware infected IoT...