Arne Bochem

Secure and Authenticated Data Communication in Wireless Sensor Networks.

Securing communications in wireless sensor networks is increasingly important as the diversity of applications increases. However, even today, it is equally important for the measures employed to be energy efficient. For this reason, this publication analyzes the suitability of various cryptographic primitives for use in WSNs according to various criteria and, finally, describes a modular, PKI-based framework for confidential, authenticated, secure communications in which most suitable primitives can be employed. Due to the limited capabilities of common WSN motes, criteria for the selection of primitives are security, power efficiency and memory requirements. The implementation of the framework and the singular components have been tested and benchmarked in our testbed of IRISmotes.

Calculating the speed of vehicles using Wireless Sensor Networks

Speed measurement is an important issue for some types of Wireless Sensor Networks (WSN), especially for Vehicular Ad-hoc Networks (VANETs). However, calculating this value is error-prone and costly. This report intends to demonstrate the calculation of speed of an object without the use of any additional devices or sensor boards, only using Received Signal Strength Indication (RSSI) for localization of the vehicles and time calculation using synchronization. We implemented these methods in actual IRIS motes, and tested them. The results show that, while not perfectly accurate, our method proved to be reliable and close to the real speed. In addition, the results do not have any linear correlation in divergence of real speed and calculated speed, which means the system avoids systematic errors.

Smart parking system for vehicles

There are various regions of applications for wireless sensor networks (WSNs). In this demonstration, we are using a WSN to build an efficient and smart parking system for vehicles. Our application will use light sensors to automatically determine the use of parking spaces in a parking area and calculate billable parking time while also providing a useful overview of occupied and free parking spaces to vehicle operators. Such a system can provide increased driver comfort and reduce costs in parking space operation by allowing drivers to easily decide on where to park, while the used components only generate low costs for the operator.

Simple secure PKI-based scheme for wireless sensor networks

This paper describes a simple secure scheme for wireless sensor motes. The purpose of the proposed scheme is to securely exchange data among motes by using Public Key Infrastructure (PKI) with a central authority. Key pairs are pre-distributed and signed by the Certification Authority (CA). The subsequent communication between the motes utilizes symmetric cryptography for efficiency reasons. In the first phase the scheme has been modeled and simulated by TOSSIM simulator to validate and measure its performance. Afterwards, a practical test in our Test bed has been conducted. The initial results are presented in the following paper.

Tri-MCL: Synergistic Localization for Mobile Ad-Hoc and Wireless Sensor Networks

Localization is a highly important topic in wireless sensor networks as well as in many Internet of Things applications. Many current localization algorithms are based on the Sequential Monte Carlo Localization method (MCL), the accuracy of which is bounded by the radio range. High computational complexity in the sampling step is another issue of these approaches. We present Tri-MCL which significantly improves on the accuracy of the Monte Carlo Localization algorithm. To do this, we leverage three different distance measurement algorithms based on range-free approaches. Using these, we estimate the distances between unknown nodes and anchor nodes to perform more fine-grained filtering of the particles as well as for weighting the particles in the final estimation step of the algorithm. Simulation results illustrate that the proposed algorithm achieves better accuracy than the MCL and SA-MCL algorithms. Furthermore, it also exhibits high efficiency in the sampling step.

Improving energy efficiency of data communication in a hybrid PKI-based approach for WSNs

Securing communications in wireless sensor networks is increasingly important, as the diversity of applications increases. In this paper, we analyze the performance and power efficiency of bulk user data communications in a simple, secure PKI-based communication scheme employing a hybrid cryptographic approach. Detailed benchmarks of the involved cryptographic primitives are performed. The results are used to determine how the necessary computing ressources can be reduced from the current implementation, without compromising and even increasing security. At the same time, the special circumstances of the PKI-based framework on memory constrained sensor motes, such as IRIS or MICA2 motes, are considered. An improved set of cryptographic primitives is determined and implemented, improving execution speed and thus energy efficiency.

Poster abstract: Streamlined anomaly detection in web requests using recurrent neural networks

Web applications commonly provide a high attack surface. In todays world of high impact attacks, protecting them against both known and unknown attacks becomes more important than ever. We present an approach of machine learning based anomaly detection to flexibly detect anomalous requests. Our approach leverages long short-term memory (LSTM) neural networks to learn a detailed model of normal requests without requiring domain knowledge. Detection performance is flexible and can be adjusted depending on the requirements of a given use case. We evaluate our approach using the CSIC 2010 dataset of HTTP requests containing various types of attacks. After training on strictly normal, basically unprocessed data, we can successfully detect anomalous requests containing various types of attacks with high probability.

A privacy-preserving and power-efficient bicycle tracking scheme for theft mitigation

Bicycle theft is a big problem in places such as university towns, where bicycles offer one of the most cost-efficient and quick ways for students to move around. For example, 1,200 bicycles are stolen yearly in Göttingen, with more than 300,000 being reported as stolen in the whole of Germany during 2014. We present a power efficient architecture to track the locations of stolen bicycles using opportunistic communication with collection nodes placed in high traffic spots, that can be used to find stolen and lost bicycles. At the same time, the scheme is designed to prevent a loss of privacy for the owners of bicycles that have not been marked as stolen, while also reducing power usage during times where bicycles are under the control of their proper owners. We also show the feasibility of our approach using a simplified implementation using IRIS nodes, with a university campus serving as a testbed.

Received signal strength indication for movement detection

Wireless networks are spreading continuously, filling our homes and the world around us. By using a ZigBee network we will show that a person can be detected by analyzing the fluctuations of signal strength inside the network. The simplicity of our approach means that it could be extended to all wireless networks. This work shows both implications on privacy as well as promising advances in fields like home automation and smart devices by localizing people as they go about their daily lives.