Visible to the public Biblio

Filters: Author is Henze, Martin  [Clear All Filters]
2020-03-23
Hiller, Jens, Pennekamp, Jan, Dahlmanns, Markus, Henze, Martin, Panchenko, Andriy, Wehrle, Klaus.  2019.  Tailoring Onion Routing to the Internet of Things: Security and Privacy in Untrusted Environments. 2019 IEEE 27th International Conference on Network Protocols (ICNP). :1–12.
An increasing number of IoT scenarios involve mobile, resource-constrained IoT devices that rely on untrusted networks for Internet connectivity. In such environments, attackers can derive sensitive private information of IoT device owners, e.g., daily routines or secret supply chain procedures, when sniffing on IoT communication and linking IoT devices and owner. Furthermore, untrusted networks do not provide IoT devices with any protection against attacks from the Internet. Anonymous communication using onion routing provides a well-proven mechanism to keep the relationship between communication partners secret and (optionally) protect against network attacks. However, the application of onion routing is challenged by protocol incompatibilities and demanding cryptographic processing on constrained IoT devices, rendering its use infeasible. To close this gap, we tailor onion routing to the IoT by bridging protocol incompatibilities and offloading expensive cryptographic processing to a router or web server of the IoT device owner. Thus, we realize resource-conserving access control and end-to-end security for IoT devices. To prove applicability, we deploy onion routing for the IoT within the well-established Tor network enabling IoT devices to leverage its resources to achieve the same grade of anonymity as readily available to traditional devices.
2019-11-04
Serror, Martin, Henze, Martin, Hack, Sacha, Schuba, Marko, Wehrle, Klaus.  2018.  Towards In-Network Security for Smart Homes. Proceedings of the 13th International Conference on Availability, Reliability and Security. :18:1-18:8.

The proliferation of the Internet of Things (IoT) in the context of smart homes entails new security risks threatening the privacy and safety of end users. In this paper, we explore the design space of in-network security for smart home networks, which automatically complements existing security mechanisms with a rule-based approach, i. e., every IoT device provides a specification of the required communication to fulfill the desired services. In our approach, the home router as the central network component then enforces these communication rules with traffic filtering and anomaly detection to dynamically react to threats. We show that in-network security can be easily integrated into smart home networks based on existing approaches and thus provides additional protection for heterogeneous IoT devices and protocols. Furthermore, in-network security relieves users of difficult home network configurations, since it automatically adapts to the connected devices and services.

2017-05-30
Henze, Martin, Hiller, Jens, Schmerling, Sascha, Ziegeldorf, Jan Henrik, Wehrle, Klaus.  2016.  CPPL: Compact Privacy Policy Language. Proceedings of the 2016 ACM on Workshop on Privacy in the Electronic Society. :99–110.

Recent technology shifts such as cloud computing, the Internet of Things, and big data lead to a significant transfer of sensitive data out of trusted edge networks. To counter resulting privacy concerns, we must ensure that this sensitive data is not inadvertently forwarded to third-parties, used for unintended purposes, or handled and stored in violation of legal requirements. Related work proposes to solve this challenge by annotating data with privacy policies before data leaves the control sphere of its owner. However, we find that existing privacy policy languages are either not flexible enough or require excessive processing, storage, or bandwidth resources which prevents their widespread deployment. To fill this gap, we propose CPPL, a Compact Privacy Policy Language which compresses privacy policies by taking advantage of flexibly specifiable domain knowledge. Our evaluation shows that CPPL reduces policy sizes by two orders of magnitude compared to related work and can check several thousand of policies per second. This allows for individual per-data item policies in the context of cloud computing, the Internet of Things, and big data.