منابع مشابه
Detecting Spam Bots in Online Social Networking Sites: A Machine Learning Approach
As online social networking sites become more and more popular, they have also attracted the attentions of the spammers. In this paper, Twitter, a popular micro-blogging service, is studied as an example of spam bots detection in online social networking sites. A machine learning approach is proposed to distinguish the spam bots from normal ones. To facilitate the spam bots detection, three gra...
متن کاملDetecting Social Spam Campaigns on Twitter
The popularity of Twitter greatly depends on the quality and integrity of contents contributed by users. Unfortunately, Twitter has attracted spammers to post spam content which pollutes the community. Social spamming is more successful than traditional methods such as email spamming by using social relationship between users. Detecting spam is the first and very critical step in the battle of ...
متن کاملMeasuring social spam and the effect of bots on information diffusion in social media
Bots have been playing a crucial role in online platform ecosystems, as efficient and automatic tools to generate content and diffuse information to the social media human population. In this chapter, we will discuss the role of social bots in content spreading dynamics in social media. In particular, we will first investigate some differences between diffusion dynamics of content generated by ...
متن کاملDetection of Spam Hosts and Spam Bots Using Network Flow Traffic Modeling
In this paper, we present an approach for detecting e-mail spam originating hosts, spam bots and their respective controllers based on network flow data and DNS metadata. Our approach consists of first establishing SMTP traffic models of legitimate vs. spammer SMTP clients and then classifying unknown SMTP clients with respect to their current SMTP traffic distance from these models. An entropy...
متن کاملDetecting Spam at the Network Level
Spam is increasingly a core problem affecting network security and performance. Indeed, it has been estimated that 80% of all email messages are spam. Content-based filters are a commonly deployed countermeasure, but the current research focus is now moving towards the early detection of spamming hosts. This paper investigates if spammers can be detected at the network level, based on just flow...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Revista Gestão Inovação e Tecnologias
سال: 2021
ISSN: 2237-0722,2237-0722
DOI: 10.47059/revistageintec.v11i2.1719