Secure Software Systems Group


    Ransomware Detection with Machine Learning

    Data has become more critical than ever in today's digital transformation era. The amount of data we produce daily is astonishing — every day, hundreds of millions of people are taking photos, making videos,  and exchanging messages. Given such trends,  the importance of database security is hard to overestimate: The rapid growth of the data volume stored in the databases in cloud environments and enterprise data centers makes them attractive attack targets. ❯ More

    eSano- An eHealth Platform for Internet- and Mobile-based Interventions

    Internet- and mobile-based interventions (IMIs) can help improve health care by offering location- and time-independent services. ❯ More

    Smarter Contracts - Vulnerability Detection using Deep Neural Networks

    Smart Contracts are computer programs that execute on a blockchain. The nature of blockchains allows one to run Smart Contracts in a trustless and decentralized environment. In this project, we demonstrate the effectiveness of Deep Neural Networks in the domain of Smart Contract vulnerability detection. ❯ More

    Private AI Collaborative Research Institute

    Intel, in collaboration with Avast and Borsetta, launched the Private AI Collaborative Research Institute to advance and develop technologies in privacy and trust for decentralized AI.  ❯ More

    Privacy – Mobile Contact Discovery

    Contact discovery allows users of mobile messengers to conveniently connect with people in their address book.  In this work, we demonstrate that severe privacy issues exist in currently deployed contact discovery methods.  ❯ More

    TraceCORONA - Anonymous contact tracing for pandemic response

    TraceCORONA is designed to be not only a tracing app, but a system concept that allows the TraceCORONA tracing component as well as other possible tracing apps to integrate into a secure health platform for private healthcare-related services over a well-defined secure interface.  ❯ More

    (Federated) Machine Learning for Risk Detection on Mobile Platforms

    The importance of security and protection of private information on mobile devices has increased in recent years due to the widespread use of these devices. This lead to the intensive use of mobile platforms for security-critical tasks, such as online banking, mobile payments, healthcare applications or business-related activities. On another hand, mobile platforms became attractive attack targets, since they store and process a significant amount of security-critical information, such as authentication credentials, payment information, and access tokens.  ❯ More

    SIMPL: Secure Internet of Things Management Platform

    The proliferation of IoT devices is increasing at a fast pace,whether for private or business use. However, despite their growing popularity, their safe operation is often not guaranteed. To tackle the security challenges of modern IoT environments, the German Federal Ministry of Education and Research is funding the SIMPL project in order to support research in this area.  ❯ More