相关论文: Bot Development for Social Engineering Attacks on …

We report the first, to the best of our knowledge, hand-in-hand collaboration between human rights activists and machine learners, leveraging crowd-sourcing to study online abuse against women on Twitter. On a technical front, we carefully…

The problem of detecting bots, automated social media accounts governed by software but disguising as human users, has strong implications. For example, bots have been used to sway political elections by distorting online discourse, to…

Social bots represent a new generation of bots that make use of online social networks (OSNs) as a command and control (C\&C) channel. Malicious social bots were responsible for launching large-scale spam campaigns, promoting low-cap…

There is a large amount of interest in understanding users of social media in order to predict their behavior in this space. Despite this interest, user predictability in social media is not well-understood. To examine this question, we…

The rapid growth of social media in recent years has fed into some highly undesirable phenomena such as proliferation of abusive and offensive language on the Internet. Previous research suggests that such hateful content tends to come from…

The impact of online social media on societal events and institutions is profound; and with the rapid increases in user uptake, we are just starting to understand its ramifications. Social scientists and practitioners who model online…

The ability to accurately predict cyber-attacks would enable organizations to mitigate their growing threat and avert the financial losses and disruptions they cause. But how predictable are cyber-attacks? Researchers have attempted to…

The arm race between spambots and spambot-detectors is made of several cycles (or generations): a new wave of spambots is created (and new spam is spread), new spambot filters are derived and old spambots mutate (or evolve) to new species.…

Automated social media accounts, known as bots, are increasingly recognized as key tools for manipulative online activities. These activities can stem from coordination among several accounts and these automated campaigns can manipulate…

Twitter bots are a controversial element of the platform, and their negative impact is well known. In the field of scientific communication, they have been perceived in a more positive light, and the accounts that serve as feeds alerting…

In recent years, people spend a lot of time on social networks. They use social networks as a place to comment on personal or public events. Thus, a large amount of information is generated and shared daily in these networks. Using such a…

A growing suite of research illustrates the negative impact of social media bots in amplifying harmful information with widespread social implications. Social bot detection algorithms have been developed to help identify these bot agents…

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…

We introduce a system for automatically generating warnings of imminent or current cyber-threats. Our system leverages the communication of malicious actors on the darkweb, as well as activity of cyber security experts on social media…

In recent years, there has been a huge increase in the number of bots online, varying from Web crawlers for search engines, to chatbots for online customer service, spambots on social media, and content-editing bots in online collaboration…

Twitter, a popular social network, presents great opportunities for on-line machine learning research. However, previous research has focused almost entirely on learning from passively collected data. We study the problem of learning to…

There has been much effort on studying how social media sites, such as Twitter, help propagate information in different situations, including spreading alerts and SOS messages in an emergency. However, existing work has not addressed how to…

Chatbots are used in many applications, e.g., automated agents, smart home assistants, interactive characters in online games, etc. Therefore, it is crucial to ensure they do not behave in undesired manners, providing offensive or toxic…

The rise of online aggression on social media is evolving into a major point of concern. Several machine and deep learning approaches have been proposed recently for detecting various types of aggressive behavior. However, social media are…

As Large Language Models (LLMs) become more sophisticated, there is a possibility to harness LLMs to power social media bots. This work investigates the realism of generating LLM-Powered social media bot networks. Through a combination of…