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Max Maurer
Counteracting Phishing through HCI: Detecting Attacks and Warning Users
PhD thesis, Faculty of Mathematics, Computer Science and Statistics, University of Munich, 2013.

Computer security is a very technical topic that is in many cases hard to grasp for the average user. Especially when using the Internet, the biggest network connecting computers globally together, security and safety are important. In many cases they can be achieved without the user's active participation: securely storing user and customer data on Internet servers is the task of the respective company or service provider, but there are also a lot of cases where the user is involved in the security process, especially when he or she is intentionally attacked. Socially engineered phishing attacks are such a security issue were users are directly attacked to reveal private data and credentials to an unauthorized attacker. These types of attacks are the main focus of the research presented within my thesis.

I have a look at how these attacks can be counteracted by detecting them in the first place but also by mediating these detection results to the user. In prior research and development these two areas have most often been regarded separately, and new security measures were developed without taking the final step of interacting with the user into account. This interaction mainly means presenting the detection results and receiving final decisions from the user. As an overarching goal within this thesis I look at these two aspects united, stating the overall protection as the sum of detection and "user intervention".

Within nine different research projects about phishing protection this thesis gives answers to ten different research questions in the areas of creating new phishing detectors (phishing detection) and providing usable user feedback for such systems (user intervention): The ten research questions cover five different topics in both areas from the definition of the respective topic over ways how to measure and enhance the areas to finally reasoning about what is making sense. The research questions have been chosen to cover the range of both areas and the interplay between them. They are mostly answered by developing and evaluating different prototypes built within the projects that cover a range of human-centered detection properties and evaluate how well these are suited for phishing detection. I also take a look at different possibilities for user intervention (e.g. how should a warning look like? should it be blocking or non-blocking or perhaps even something else?). As a major contribution I finally present a model that combines phishing detection and user intervention and propose development and evaluation recommendations for similar systems. The research results show that when developing security detectors that yield results being relevant for end users such a detector can only be successful in case the final user feedback already has been taken into account during the development process.