18 research outputs found

    Experimental Evaluation of Floating Car Data Collection Protocols in Vehicular Networks

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    The main objectives of the Intelligent Transportation Systems (ITS) vision is to improve road safety, traffic management, and mobility by enabling cooperative communication among participants. This vision requires the knowledge of the current state of the road traffic, which can be obtained by collecting Floating Car Data (FCD) information using Dedicated Short-Range Communication (DSRC) based on the IEEE 802.11p standard. Most of the existing FCD collection protocols have been evaluated via simulations and mathematical models, while the real-world implications have not been thoroughly investigated. This paper presents an open-source implementation of two state-of-the-art FCD collection algorithms, namely BASELINE and DISCOVER. These algorithms are implemented in an open-source vehicular prototyping platform and validated in a real-world experimental setup

    Softwarization of SCADA: Lightweight Statistical SDN-Agents for Anomaly Detection

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    The increasing connectivity of restricted areas suchas Critical Infrastructures (CIs) raises major security concernsfor Supervisory Control And Data Acquisition (SCADA) systems,which are deployed to monitor their operation. Given the impor-tance of an early anomaly detection, Intrusion Detection Systems(IDSs) are introduced in SCADA systems to detect malicious ac-tivities as early as possible. Agents or probes form the cornerstoneof any IDS by capturing network packets and extracting relevantinformation. However, IDSs are facing unprecedented challengesdue to the escalation in the number, scale and diversity of attacks.Software-Defined Network (SDN) then comes into play and canprovide the required flexibility and scalability. Building on that,we introduce Traffic Agent Controllers (TACs) that monitor SDN-enabled switches via OpenFlow. By using lightweight statisticalmetrics such as Kullback-Leibler Divergence (KLD), we are ableto detect the slightest anomalies, such as stealth port scans, evenin the presence of background traffic. The obtained metrics canalso be used to locate the anomalies with precision over 90%inside a hierarchical network topology

    Analysis of Bandwidth Attacks in a Bittorrent Swarm

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    Smartphones in a Microwave: Formal and Experimental Feasibility Study on Fingerprinting the Corona-Warn-App

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    Contact Tracing Apps (CTAs) have been developed to contain the coronavirus disease 19 (COVID-19) spread. By design, such apps invade their users' privacy by recording data about their health, contacts, and partially location. Many CTAs frequently broadcast pseudorandom numbers via Bluetooth to detect encounters. These numbers are changed regularly to prevent individual smartphones from being trivially trackable. However, the effectiveness of this procedure has been little studied. We measured real smartphones and observed that the German Corona-Warn-App (CWA) exhibits a device-specific latency between two subsequent broadcasts. These timing differences provide a potential attack vector for fingerprinting smartphones by passively recording Bluetooth messages. This could conceivably lead to the tracking of users' trajectories and, ultimately, the re-identification of users.Comment: accepted for publication at TRUSTBU

    Locust: Highly Concurrent DHT Experimentation Framework for Security Evaluations

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    Distributed Hash Table (DHT) protocols, such as Kademlia, provide a decentralized key-value lookup which is nowadays integrated into a wide variety of applications, such as Ethereum, InterPlanetary File System (IPFS), and BitTorrent. However, many security issues in DHT protocols have not been solved yet. DHT networks are typically evaluated using mathematical models or simulations, often abstracting away from artefacts that can be relevant for security and/or performance. Experiments capturing these artefacts are typically run with too few nodes. In this paper, we provide Locust, a novel highly concurrent DHT experimentation framework written in Elixir, which is designed for security evaluations. This framework allows running experiments with a full DHT implementation and around 4,000 nodes on a single machine including an adjustable churn rate; thus yielding a favourable trade-off between the number of analysed nodes and being realistic. We evaluate our framework in terms of memory consumption, processing power, and network traffic
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