Alexandra Dirksen

Bachelor's Thesis by Minela Becirovic

In recent years, data privacy and the usage of privacy-conscious applications have gained significant importance. With the implementation of security features like end-to-end encryption, applications like "Signal" offer strong security guarantees for their end-users.
In contrast to desktop or mobile applications, web-based applications are struggling to adopt client-side encryption due to various limitations. The risk of a data breach is increased when the web application uses JavaScript. This usage enables the execution of malicious JS code on the client-side where confidential data of the user resides unencrypted. This way an active JS attacker can access the user’s data without the user’s knowledge or consent.
One approach to deal with this issue is the idea of CryptoMembranes (CM). With the concept of CM, a new type of DOM element that enables native encryption on the client-side is introduced. By maintaining an encrypted and decrypted representation of confidential data on the client-side, the concept aims to provide strong protection against active JS attacks. As a result, only the user has access to the decrypted representation of the confidential data.
In this thesis, we will implement the CM concept as an extension for the Firefox browser. This way we practically evaluate to what extent the theoretical concept of the paper meets the defined privacy & security goals if implemented as a browser extension for legacy browsers.

Master's Thesis by Julius Platon

Cloud infrastructures, platforms, and services remain popular targets for attackers. In particular, public clouds are attractive due to their highly available and distributed nature. Within modern cloud and web-based applications, the need for secure storage of credentials such as cryptographic primitives and certificates grows. The responsibility for the protection and storage of such credentials implies a high complexity burden on the development process and an inherent fault-proneness. Recent cloud and development trends revolve around key management services (KMS), which are able to store credentials and provide high-level interfaces for clients. A primary target group of KMS is software developers, in order to relieve them from the large security burden of key storage and management.

KMS commonly utilize sophisticated hardware components, such as hardware security modules (HSM), in order to protect credentials such as cryptographic key material. The responsibility to protect credentials and remain available within heterogeneous cloud environments shifts the complexity burden from developers to cloud and KMS providers. The sensitive nature of KMS makes them highly attractive targets for attackers. Therefore, this thesis presents a threat model and a subsequent case study of four selected KMS solutions, namely Google KMS, AWS KMS, Azure Key Vault, and HashiCorp Vault. Within the threat model, occurring attacker types are presented and analyzed. As preliminaries of the threat model, the infrastructure, actors, and assets related to KMS are described. The threat model is complemented by the implementation of a prototype application for each KMS, in order to analyze insides such as security protocol details. After threat modeling, implementation, and elaboration of mitigations, an overview of results and a comparison of the selected KMS solutions follows. During the conclusion section, the contribution and future work are covered. Eventually, the output and key takeaways of the research are described.

Master's Thesis by Robin Heinbockel

The General Data Protection Regulation (GDPR) forms the legal basis for processing personal data of website users. There is a multitude of consent request implementations that are embedded in websites because website providers have to ask for consent before processing the user’s data since the GDPR came into effect in 2018. We present flaws in current implementations and derive goals towards user privacy and usability from the GDPR and related research.
We propose a shift of the consent implementation from the website to the browser for increased privacy control on the client’s side, called Native Cookie Consent (NCC). That means the browser is responsible for showing the consent dialog in a native window and executing the user’s preferences afterwards. NCC also includes a protocol to transmit cookie policies and the user’s preferences separate from the website content.

With our prototype implementation, we show that NCC has benefits over existing consent implementations: Authorities have to control a fraction of instances with an imple- mentation in the most popular browsers compared to the amount of website providers that currently provide the consent interface. Website providers and third parties have to disclose purposes for processing in their cookie policy and the user can choose their degree of consent per individual purpose and party. The browser blocks cookies that do not comply with the user’s consent preferences – and it blocks all cookies before the user expressed consent. Dark patterns in design and wording can be prevented with NCC through balanced design and plain language. We analyze the prototype in terms of functionality and usability and discuss extensions to further improve the implementation, including default settings to avoid the necessity to express the same preferences for each website. We conclude that NCC offers privacy and usability improvements compared to other GDPR consent request implementations.