Electromagnetic Fault Injection (EMFI) has become an established technique for fault injection in embedded systems. EMFI has several advantages compared to other fault injection techniques and its effectiveness has been proven in practice. Currently, the application of non-trivial EMFI experiments is limited by the high cost of advanced lab equipment and therefore unavailable for broader security research. We propose AutoPulse, a cost-effective and complete EMFI research platform based on commercial 3D printer hardware and publish the project documentation and software as open source. We show that our platform significantly reduces the cost of EMFI in practice and conduct a comprehensive literature survey to conclude that our platform specifications are sufficient to attack even modern SoCs with high clock rates. We evaluate AutoPulse by characteriizing the ESP32 micro controller and reproducing an EMFI attack on the execution pipeline. Our key observations imply that the publication of faults and attacks requires careful assessment of the parameter space and the commonly published fault maps strongly depend on process parameters that should be specified.

The ability of neural networks to universally approximate any function enables them to learn relationships between arbitrary kinds of data. This offers great potential in information security topics such as protocol reverse engineering (PRE), which has seen little usage of neural networks (NNs) so far. In this paper, we provide a novel approach for implementing PRE with solely NNs, demonstrating a simple yet effective reverse engineering of text-based protocols. This approach is modular by design and allows for the exchange of neural network models at any step with better performing models. The architectures used include a convolutional neural network (CNN), an autoencoder (AE), a generative adversarial net (GAN), a long short-term memory (LSTM), and a self-organizing map (SOM). All of these models combine for a new protocol reverse engineering approach. The results show that the widespread application layer protocols HTTP and FTP can successfully be mimicked by artificial intelligen

A registration of identities is necessary in a wide array of systems, from online forums to smart environments. While pseudonyms are, in most cases, sufficient, mechanisms must be put in place to prevent malicious adversaries from registering great numbers of sybil identities. Preventing such sybil attacks becomes an especially significant challenge when the existence of a trusted party cannot be assumed. Several countermeasures against sybil attacks on decentralized systems have been proposed that are based on leveraging information from the social graph between participating users. While promising, existing solutions typically require knowledge of the complete social graph, which is a privacy issue, or are tailored towards specific applications like distributed hash tables. In this paper, we propose an approach for registering general-purpose pseudonyms in a completely decentralized manner while keeping social relationships private. Joining users collect confirmations from a fraction of already registered users while being aware only of their own neighbors in the social graph. Using the presented SybilHedge algorithm, sybil attackers are limited in the number of confirmations they can collect. We present an evaluation of the algorithm and discuss its practical application.

Today's street traffic is still largely inefficient. Overburdened roads lead to congestions, accidents, and unnecessary pollution. The increasing interconnection of traffic participants into the Internet of Vehicles (IoV) has tremendous potential for improving this issue. Cooperative route planning, e.g., is a concept for optimizing vehicular routing on a global scale by gathering data about planned routes from interconnected vehicles. As in other IoV applications, the benefits of such a system come at the cost of an increased privacy risk for participating users. Published routes include both the current and the planned future locations of drivers and passengers-all highly sensitive pieces of information. In the scope of this paper, we demonstrate how cooperative route planning can be realized with strong privacy guarantees without significant cuts in utility or cost. According to our knowledge, this is the first work to consider in this issue. We propose a scheme by which vehicles can publish their intent to pass at specific waypoints at approximate times in an anonymous fashion. While providing complete unlinkability of published intentions to individual users, our scheme is protected against abuse, with misbehaving (i.e., lying) users quickly losing their right to participate.

The deployment of smart metering provides an immense amount of data for power grid operators and energy providers. By using this data, a more efficient and flexible power grid can be realized. However, this data also raises privacy concerns since it contains very sensitive information about customers. In this paper, we present Elderberry, a peer-to-peer protocol that enables near real-time smart metering while preserving the customer's privacy. By forming small groups of cooperating smart meters, their consumption traces are anonymized before being aggregated and sent to the grid operator. Through aggregation, Elderberry realizes efficient monitoring of large numbers of smart meters. It reaches this goal without computationally complex cryptography and adds only little communication overhead.

For smart traffic applications like dynamic route planning, communication between traffic participants is of high importance. Traditional approaches rely on centralized, server-based communication architectures, which raises scalability and privacy concerns. To address these problems, we proposed OverDrive, an overlay-based geocast service that is applicable in smart traffic scenarios and not prone to the shortcomings of centralized designs. Here, we present an interactive demonstrator of the OverDrive protocol that visualizes OverDrive's neighborhood structures and routing approach in a realistic and highly mobile traffic scenario. Our demonstrator is realized as an extension to the overlay simulation framework OverSim.

Following a constant rise in the complexity and scale of peer-to-peer networks, researchers have looked at biological phenomena in order to develop self-organized, adaptive, and robust management systems. Our focus is on distributed swarm intelligence mechanisms that mimic the behavior of social insects to solve problems such as overlay management, routing, task allocation, and resource discovery. A central problem in the validation of novel networking solutions is their empirical evaluation under different conditions. Whereas existing network simulation platforms lack specific support for ant-inspired protocols (like transparent agent migration), dedicated frameworks for bio-inspired systems fail to implement accurate network models. To bridge this gap, we introduce a framework with support for bio-inspired techniques and realistic network underlay simulation based on Over Sim. To validate our work, we describe the implementation of several swarm-based protocols and we provide some measurements of the simulation performance.

A fundamental problem in studying peer-to-peer networks is the evaluation of new protocols. This commonly involves both the simulation of the protocol in a large-scale network as well as the testing of the protocol in connection with real applications in networks like PlanetLab. To facilitate these tasks we have developed the overlay simulation framework OverSim. It is designed to fulfill a number of requirements that have been partially neglected by existing simulation frameworks.

Decentralized voice over IP networks are a promising alternative to classical server-based SIP networks especially in disaster areas or areas without centralized infrastructure. This paper presents P2PNS, a secure distributed name service for P2P SIP. P2PNS can be used to resolve SIP AoRs to contact URIs without using DNS or centralized SIP servers. The name service provides several security mechanisms to efficiently prevent identity theft and to ensure the uniqueness of SIP AoRs in a completely decentralized and untrusted network. The proposed two-stage name resolution mechanism allows to efficiently handle frequent IP address changes. Because P2PNS provides a generic name service it is not limited to P2PS1P but can also be used e.g. to build a distributed DNS system.

Security is a common problem in completely decentralized peer-to-peer systems. Although several suggestions exist on how to create a secure key-based routing protocol, a practicable approach is still unattended. In this paper we introduce a secure key-based routing protocol based on Kademlia that has a high resilience against common attacks by using parallel lookups over multiple disjoint paths, limiting free nodeld generation with crypto puzzles and introducing a reliable sibling broadcast. The latter is needed to store data in a safe replicated way. We evaluate the security of our proposed extensions to the Kademlia protocol analytically and simulate the effects of multiple disjoint paths on lookup success under the influence of adversarial nodes.