A Physically Unclonable Function (PUF) is a unique and stable physical characteristic of a piece of hardware, which emerges due to variations in the hardware fabrication processes. Prior works have demonstrated that PUFs are a promising cryptographic primitive that can enable secure key storage, hardware-based device authentication and identification. So far, most PUF constructions have required an addition of new hardware or an FPGA implementation for their operation. Recently, intrinsic PUFs, which can be found in commodity devices, have been investigated. Unfortunately, most of them suffer from the drawback that they can only be accessed at boot time. This paper focuses on a new class of run-time accessible, decay-based, intrinsic DRAM PUFs in commercial off-the-shelf systems, which requires no additional hardware or FPGAs. In order to enable secure key storage using DRAM PUFs, this work presents a new Helper Data System (HDS) specifically tailored to the properties of the decay process inherent to DRAM cells. The decay-based DRAM PUF and the new HDS are evaluated on commodity off-the-shelf devices to demonstrate their practicality. Furthermore, a novel lightweight protocol is presented that allows for mutual authentication.

In this work, we present the first systematic study of data remanence effects on an intrinsic Static Random Access Memory Physical Unclonable Function (SRAM PUF) implemented on a commercial off-the-shelf (COTS) device in the temperature range between –110 degrees Celsius and –40 degrees Celsius. Based on our experimental results, we propose a new type of attack against intrinsic SRAM PUFs, which takes advantage of data remanence effects exhibited due to low temperatures. We demonstrate that this attack is highly resistant to memory erasure techniques and can be used to manipulate the cryptographic keys produced by the SRAM PUF. Finally, we also discuss and assess potential countermeasures against the attack we propose.

Interconnected embedded devices are increasingly used in various scenarios, including industrial control, building automation, or emergency communication. As these systems commonly process sensitive information or perform safety critical tasks, they become appealing targets for cyber attacks. A promising technique to remotely verify the safe and secure operation of networked embedded devices is remote attestation. However, existing attestation protocols only protect against software attacks, or show limited scalability and robustness. In this paper, we present the first scalable attestation protocol that detects physical attacks. Based on the assumption that physical attacks require an adversary to capture and disable devices for a noticeable amount of time, our protocol identifies devices with compromised hardware and software. Compared to existing solutions, our protocol reduces communication complexity and runtimes by orders of magnitude, precisely identifies compromised devices, and is robust against failures or network disruptions. We show the security of our protocol and evaluate its scalability and robustness. Our results demonstrate that our protocol is highly efficient in well-connected networks and operates robust in disruptive and very dynamic network topologies.

Model transformations play an essential role in many aspects of model-driven development. By-demonstration approaches provide a user-friendly tool for specifying reusable model transformations. Here, a modeler performs the model transformation only once by hand and an executable transformation is automatically derived. Such a transformation is characterized by the set of pre- and postconditions that are required to be satisfied prior and after the execution of the transformation. However, the automatically derived conditions are usually too restrictive or incomplete and need to be refined manually to obtain the intended model transformation.