Zombification

Spam appears everywhere on the Internet, from downloaded emails to server-based blogs, forums and social media communications. This article explores this notion of the living dead in the context of spam culture. How is spam actively and repetitively produced with different identities? I adopt the term ‘zombie’ to describe spam because, notably, the concept of zombies has been used extensively in popular culture and entertainment, such as films, games and literature to describe the phenomenon of mindless slaves. They are usually situated in an environment that has suffered a viral outbreak with contagious effects. Critiques have compared zombies to dead labour, such as the slavery in Haiti and the labour in the United States: that is, the exploitation of labour through the concept of alienation, from Marx’s theory, and labour practices in global capitalism. Within the context of spam production, as datafied phenomenon, this paper uses the figure of the zombie to describe the computational and network processes of spam automation, which I call ‘zombification’ — alluding to the broader topic of datafication and its consequences. The assumption here is that life once datafied is zombification.

The changing nature of spam 2.0

Spam 2.0 (or Web 2.0 Spam) is referred to as spam content that is hosted on Web 2.0 applications (blogs, forums, social networks etc.). Such spam differs from traditional spam as this is targeted at Web 2.0 applications and spreads through legitimate websites. The main problems with Spam 2.0 is spam websites get undeserved high ranking in search engines, damage the reputation of legitimate websites, wastes' valuable computing resources and deceives users resulting in proliferation of scam, fraud and other security attacks. Protecting the Internet against Spam 2.0 attacks is increasingly becoming important due to the potential threats it poses to the innocent web users. The paper contributes in this direction by attempting to understand the root cause of the problem, by investigating the changing nature of Spam 2.0. To understand this we setup an online discussion forum as a Honeypot to capture spam content. The collected data is analysed to identify trends within the spam corpus, which includes repetitiveness in the use of email addresses, patterns within email addresses, repetitiveness of forum posts, domains used for spamming, keywords and categories, origin of spam traffic. In the future we aim to use these trends in developing a preventive or early detection system that could predict future spam activities and would allow us to take pre-emptive actions to address them