Search results for "spam"
showing 5 items of 5 documents
An asynchronous covert channel using spam
2012
AbstractCurrent Internet e-mail facilities are built onto the foundation of standard rules and protocols, which usually allow a considerable amount of “freedom” to their designers. Each of these standards has been defined based on a number of vendor specific implementations, in order to provide common inter-working procedures for cross-vendor communication. Thus, a lot of optional and redundant information is being exchanged during e-mail sessions, which is available to implement versatile covert channel mechanisms.This work exploits this possibility by presenting a simple but effective steganographic scheme that can be used to deploy robust secret communication through spam e-mails. This s…
SpADe: Multi-Stage Spam Account Detection for Online Social Networks
2022
In recent years, Online Social Networks (OSNs) have radically changed the way people communicate. The most widely used platforms, such as Facebook, Youtube, and Instagram, claim more than one billion monthly active users each. Beyond these, news-oriented micro-blogging services, e.g., Twitter, are daily accessed by more than 120 million users sharing contents from all over the world. Unfortunately, legitimate users of the OSNs are mixed with malicious ones, which are interested in spreading unwanted, misleading, harmful, or discriminatory content. Spam detection in OSNs is generally approached by considering the characteristics of the account under analysis, its connection with the rest of …
Twitter spam account detection by effective labeling
2019
In the last years, the widespread diffusion of Online Social Networks (OSNs) has enabled new forms of communications that make it easier for people to interact remotely. Unfortunately, one of the first consequences of such a popularity is the increasing number of malicious users who sign-up and use OSNs for non-legit activities. In this paper we focus on spam detection, and present some preliminary results of a system that aims at speeding up the creation of a large-scale annotated dataset for spam account detection on Twitter. To this aim, two different algorithms capable of capturing the spammer behaviors, i.e., to share malicious urls and recurrent contents, are exploited. Experimental r…
Assisted labeling for spam account detection on twitter
2019
Online Social Networks (OSNs) have become increasingly popular both because of their ease of use and their availability through almost any smart device. Unfortunately, these characteristics make OSNs also target of users interested in performing malicious activities, such as spreading malware and performing phishing attacks. In this paper we address the problem of spam detection on Twitter providing a novel method to support the creation of large-scale annotated datasets. More specifically, URL inspection and tweet clustering are performed in order to detect some common behaviors of spammers and legitimate users. Finally, the manual annotation effort is further reduced by grouping similar u…