Related papers: Analysing the fall 2020 Emotet campaign
The major aim of this paper is to explain the data poisoning attacks using label-flipping during the training stage of the electroencephalogram (EEG) signal-based human emotion evaluation systems deploying Machine Learning models from the…
We study the effects of campaigning, where the society is partitioned into voter clusters and a diffusion process propagates opinions in a network connecting the clusters. Our model is very powerful and can incorporate many campaigning…
This paper's main goal is to provide an attacker's point of view on data poisoning assaults that use label-flipping during the training phase of systems that use electroencephalogram (EEG) signals to evaluate human emotion. To attack…
The world's digital transformation has influenced not only the way we do business, but also the way we perform daily activities. In fact, the past Presidential elections in the United States as well as those in Great Britain (Brexit) and in…
Adversarial interactions against politicians on social media such as Twitter have significant impact on society. In particular they disrupt substantive political discussions online, and may discourage people from seeking public office. In…
The growing number of Internet of Things (IoT) devices makes it imperative to be aware of the real-world threats they face in terms of cybersecurity. While honeypots have been historically used as decoy devices to help…
Explainable Multimodal Emotion Recognition (EMER) is an emerging task that aims to achieve reliable and accurate emotion recognition. However, due to the high annotation cost, the existing dataset (denoted as EMER-Fine) is small, making it…
Autonomous driving has rapidly developed and shown promising performance due to recent advances in hardware and deep learning techniques. High-quality datasets are fundamental for developing reliable autonomous driving algorithms. Previous…
It has been widely recognized that automated bots may have a significant impact on the outcomes of national events. It is important to raise public awareness about the threat of bots on social media during these important events, such as…
In the domain of Vehicular Ad hoc Networks (VANETs), where the imperative of having a real-world malicious detector capable of detecting attacks in real-time and unveiling their perpetrators is crucial, our study introduces a system with…
The proliferation of hate speech and offensive comments on social media has become increasingly prevalent due to user activities. Such comments can have detrimental effects on individuals' psychological well-being and social behavior. While…
Clickbait is deceptive text that can manipulate web browsing, creating an information gap between a link and target page that literally baits a user into clicking. Clickbait detection continues to be well studied, but analyses of clickbait…
Botnet detection based on machine learning have witnessed significant leaps in recent years, with the availability of large and reliable datasets that are extracted from real-life scenarios. Consequently, adversarial attacks on machine…
Recent attacks encouraged public interest in physical security for railways. Knowing about and learning from previous attacks is necessary to secure against them. This paper presents a structured data set of physical attacks against…
This paper proposes an agent-based simulation of a presidential election, inspired by the French 2017 presidential election. The simulation is based on data extracted from polls, media coverage, and Twitter. The main contribution is to…
Since previous studies on open-domain targeted sentiment analysis are limited in dataset domain variety and sentence level, we propose a novel dataset consisting of 6,013 human-labeled data to extend the data domains in topics of interest…
The prevalence of coordinated information campaigns in social media platforms has significant negative consequences across various domains, including social, political, and economic processes. This paper proposes a multifaceted framework…
The weaponization of digital communications and social media to conduct disinformation campaigns at immense scale, speed, and reach presents new challenges to identify and counter hostile influence operations (IOs). This paper presents an…
We describe a case study in the use of the Structured Process for Information Campaign Enhancement (SP!CE, version 2.1) to evaluate influence campaigns present in the 2nd round of the Brazilian presidential election in 2022 October. SP!CE…
With its lenient moderation policies and long-standing associations with potentially unlawful activities, Telegram has become an incubator for problematic content, frequently featuring conspiratorial, hyper-partisan, and fringe narratives.…