Since March 2019, I’m a researcher and Ph.D. Student at Klaus Wehrle’s Chair of Communication and Distributed Systems at RWTH Aachen University after I graduated with an M.Sc. in Computer Science in September 2018 and received my B.Sc. in 2016. More precisely, I’m part of the Security and Privacy Group.
Currently, my research interests focus on but are not limited to Network Security for Industrial Networks.
M.Sc. in Computer Science, 2018
RWTH Aachen University
B.Sc. in Computer Science, 2016
RWTH Aachen University
💾 We released our OPC UA assessment modules for Metasploit.
Due to increasing digitalization, formerly isolated industrial networks, e.g., for factory and process automation, move closer and closer to the Internet, mandating secure communication. However, securely setting up OPC UA, the prime candidate for secure industrial communication, is challenging due to a large variety of insecure options. To study whether Internet-facing OPC UA appliances are configured securely, we actively scan the IPv4 address space for publicly reachable OPC UA systems and assess the security of their configurations. We observe problematic security configurations such as missing access control (on 24% of hosts), disabled security functionality (24%), or use of deprecated cryptographic primitives (25%) on in total 92% of the reachable deployments. Furthermore, we discover several hundred devices in multiple autonomous systems sharing the same security certificate, opening the door for impersonation attacks. Overall, in this paper, we highlight commonly found security misconfigurations and underline the importance of appropriate configuration for security-featuring protocols.
More and more traditional services, such as malware detectors or collaboration services in industrial scenarios, move to the cloud. However, this behavior poses a risk for the privacy of clients since these services are able to generate profiles containing very sensitive information, e.g., vulnerability information or collaboration partners. Hence, a rising need for protocols that enable clients to obtain knowledge without revealing their requests exists. To address this issue, we propose a protocol that enables clients (i) to query large cloud-based knowledge systems in a privacy-preserving manner using Private Set Intersection and (ii) to subsequently obtain individual knowledge items without leaking the client’s requests via few Oblivious Transfers. With our preliminary design, we allow clients to save a significant amount of time in comparison to performing Oblivious Transfers only.