1,720,962 research outputs found
Fake News Spreaders Profiling through Behavioural Analysis Notebook for PAN at CLEF 2020
No full textThe growth of social media and the people interconnection led to the digitalization of communication. Nowadays the most influential politicians or scientific communicators use the media to disseminate news or decisions. However, such communications media can be used maliciously to spread the so-called fake-news in order to polarise public opinion or to deny scientific theories. It is therefore important to develop intelligent and accurate techniques in order to identify the spreading of fake-news. In this paper, we describes the methodology regarding our participation in the PAN@CLEF Profiling Fake News Spreaders on Twitter competition. We propose a supervised Machine-Learning (ML) based framework to profile fake-news spreaders. Our method relies on the combination of Big Five personality and stylometric features. Finally, we evaluate our framework detection capabilities and performance with different ML models on a tweeter dataset in both English and Spanish languages
ALISI: A lightweight identification system based on Iroha
No full textGiven their ubiquity, modern Internet of Things (IoT) devices represent a dangerous attack surface for hackers. These devices are strongly heterogeneous by manufacturer, application field, geographic area of deployment, security requirements, and computational performances. This vulnerability problem is more important in the Industrial Internet of Things (IIoT) scenario, where systems are critical for plant processes, such as power grids and water distribution. In this paper, we present ALISI: A Lightweight Identification System based on Iroha, a blockchain-based identification platform conceived for IoT and IIoT systems. The blockchain technology provides a global identification standard, following a distributed approach in order to collaborate and share responsibilities and costs to gain first-class security features. Our scheme handles the performance issues typical of the blockchain systems using a hybrid on-chain and off-chain approach, achieving low response time and small load on the single device
MiniV2G: An Electric Vehicle Charging Emulator
No full textThe impact of global warming and the imperative to limit climate change have stimulated the need to develop new solutions based on renewable energy sources. One of the emerging trends in this endeavor are Electric Vehicles (EVs), which use electricity instead of traditional fossil fuels as a power source, relying on the Vehicle-To-Grid (V2G) paradigm. The novelty of such a paradigm requires careful analysis to avoid malicious attempts. An attacker can exploit several surfaces, such as the remote connection between the Distribution Grid and Charging Supply or the authentication system between the charging Supply Equipment and the Electric Vehicles. However, V2G architecture's high cost and complexity in implementation can restrain this field's research capability. In this paper, we approach this limitation by proposing MiniV2G, an open-source emulator to simulate Electric Vehicle Charging (EVC) built on top of Mininet and RiseV2G. MiniV2G is particularly suitable for security researchers to study and test real V2G charging scenarios. MiniV2G can reproduce with high fidelity a V2G architecture to easily simulate an EV charging process. Finally, we present a MiniV2G application and show how MiniV2G can be used to study V2G communication and develop attacks and countermeasures that can be applied to real systems. Since we believe our tool can help research in this field, we also made it freely available
OpenScope-sec: An ADS-B Simulator to Support the Security Research
Full text linkAutomatic Dependent Surveillance-Broadcast (ADS-B) protocol is employed in air-ground communication systems to replace legacy radar-based air traffic control systems. However, despite being a recent technology, ADS-B communication does not include security measures. This exposes the communication to potential threats, including message spoofing or fake aircraft generation. To cope with such a security lack, the security community is actively proposing innovative solutions to protect ADS-B communication. However, testing and evaluating security frameworks is complex due to the limited number of simulators and the impossibility of conducting real-world experiments. In this paper, we present an OpenScope-sec an ADS-B simulator to support the security research and the implementation of novel anomaly detection systems. Our simulator extends the existing ADS-B simulator tools with the possibility of implementing a wider range of attacks. The list of attacks included is based on a preliminary..
SENECAN: Secure KEy DistributioN OvEr CAN Through Watermarking and Jamming
Full text linkThe Control Area Network (CAN) represents the standard bus for intra-vehicular networks communication. Unfortunately, CAN was not designed to be a secure protocol. Communications over CAN do not take advantage of any security feature (e.g., cryptography and authentication), raising different vulnerabilities in critical applications. This lack of security is even more emphasized in recent CAN networks, which integrate remote connection capabilities (e.g., Bluetooth and WiFi). This insecurity-by-design led to the development of specific mechanisms to patch CAN vulnerabilities. Many proposed solutions rely on implementing optimized cryptographic primitives and assume that the cryptographic keys were previously shared among the different nodes during the production phase, omitting the issue related to keys distribution and update. We propose SENECAN, a solution that combines watermarking and wired jamming to secure the CAN bus's key distribution. Our solution leverages intentional interference and spread spectrum watermarking to achieve security properties such as confidentiality, integrity, authentication, and anti-replay. Compared to other works, SENECAN does not require any modification of the CAN protocol and system architecture. Instead, it requires an additional CAN transceiver and an initial transmission overhead. Finally, we tested the effectiveness and functioning of the SENECAN distribution schema in a real CAN environment
A Statistical Analysis Framework for ICS Process Datasets
Full text linkIn recent years, several schemes have been proposed to detect anomalies and attacks on Cyber-Physical Systems (CPSs) such as Industrial Control Systems (ICSs). Based on the analysis of sensor data, unexpected or malicious behavior is detected. Those schemes often rely on (implicit) assumptions on temporally stable sensor data distributions and invariants between process values. Unfortunately, the proposed schemes often perform not optimally with Recall scores lower than 70% (e.g., missing 3 alarms every 10 anomalies) for some ICS datasets, with unclear root issues. In this work, we propose a general framework to check whether a given ICS dataset has specific properties (stable sensor distributions in normal operations, potentially state-dependent), which then allows to determine whether certain Anomaly Detection approaches can be expected to perform well. We apply our framework to three datasets showing that the behavior of actuators and sensors are very different between Training set and Test set. In addition, we present high-level guides to consider when designing an Anomaly Detection System
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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