Do Social Bots Dream of Electric Sheep? A Categorisation of Social Media Bot Accounts

So-called 'social bots' have garnered a lot of attention lately. Previous research showed that they attempted to influence political events such as the Brexit referendum and the US presidential elections. It remains, however, somewhat unclear what exactly can be understood by the term 'social bot'. This paper addresses the need to better understand the intentions of bots on social media and to develop a shared understanding of how 'social' bots differ from other types of bots. We thus describe a systematic review of publications that researched bot accounts on social media. Based on the results of this literature review, we propose a scheme for categorising bot accounts on social media sites. Our scheme groups bot accounts by two dimensions - Imitation of human behaviour and Intent.Comment: Accepted for publication in the Proceedings of the Australasian Conference on Information Systems, 201

Command & Control: Understanding, Denying and Detecting - A review of malware C2 techniques, detection and defences

In this survey, we first briefly review the current state of cyber attacks, highlighting significant recent changes in how and why such attacks are performed. We then investigate the mechanics of malware command and control (C2) establishment: we provide a comprehensive review of the techniques used by attackers to set up such a channel and to hide its presence from the attacked parties and the security tools they use. We then switch to the defensive side of the problem, and review approaches that have been proposed for the detection and disruption of C2 channels. We also map such techniques to widely-adopted security controls, emphasizing gaps or limitations (and success stories) in current best practices.Comment: Work commissioned by CPNI, available at c2report.org. 38 pages. Listing abstract compressed from version appearing in repor

Online Misinformation: Challenges and Future Directions

Misinformation has become a common part of our digital media environments and it is compromising the ability of our societies to form informed opinions. It generates misperceptions, which have affected the decision making processes in many domains, including economy, health, environment, and elections, among others. Misinformation and its generation, propagation, impact, and management is being studied through a variety of lenses (computer science, social science, journalism, psychology, etc.) since it widely affects multiple aspects of society. In this paper we analyse the phenomenon of misinformation from a technological point of view.We study the current socio-technical advancements towards addressing the problem, identify some of the key limitations of current technologies, and propose some ideas to target such limitations. The goal of this position paper is to reflect on the current state of the art and to stimulate discussions on the future design and development of algorithms, methodologies, and applications

Discovery of the Twitter Bursty Botnet

Many Twitter users are bots. They can be used for spamming, opinion manipulation and online fraud. Recently, we discovered the Star Wars botnet, consisting of more than 350,000 bots tweeting random quotations exclusively from Star Wars novels. The bots were exposed because they tweeted uniformly from any location within two rectangle-shaped geographic zones covering Europe and the USA, including sea and desert areas in the zones. In this chapter, we report another unusual behaviour of the Star Wars bots, that the bots were created in bursts or batches, and they only tweeted in their first few minutes since creation. Inspired by this observation, we discovered an even larger Twitter botnet, the Bursty botnet with more than 500,000 bots. Our preliminary study showed that the Bursty botnet was directly responsible for a large-scale online spamming attack in 2012. Most bot detection algorithms have been based on assumptions of “common” features that were supposedly shared by all bots. Our discovered botnets, however, do not show many of those features; instead, they were detected by their distinct, unusual tweeting behaviours that were unknown until now

Looking behind the text-to-be-seen: Analysing Twitter bots as electronic literature

This thesis focuses on showing how Twitter bots can be analysed from the viewpoint of electronic literature (e-lit) and how the analysis differs from evaluating other works of e-lit. Although formal research on electronic literature goes back some decades, there is still not much research discussing bots in particular. By examining historical and contemporary textual generators, seminal theories on reading and writing e-lit and botmakers’ practical notes about their craft, this study attempts to build an understanding of the process of creating a bot and the essential characteristics related to different kinds of bots. What makes the analysis of bots different from other textual generators is that the source code, which many theorists consider key in understanding works of e-lit, is rarely available for reading. This thesis proposes an alternative method for analysing bots, a framework for reverse-engineering the bot’s text generation procedures. By comparing the bot’s updates with one another, it is possible to notice the formulas and words repeated by the bot in order to better understand the authorial choices made in its design. The framework takes into account the special characteristics of different kinds of bots, focusing on grammar-based bots, which utilise fill-in-the-blank-type sentence structures to generate texts, and list-based bots, which methodically progress through large databases. From a survey of contemporary bots and earlier works of electronic and procedural literature, it becomes evident that understanding programming code is not essential for either analysing or creating bots: it is more important to understand the mechanisms of combinatory text generation and the author’s role in writing and curating the materials used. Bots and text generators also often raise questions of authorship. However, a review of their creation process makes it clear that human creativity is essential for the production of computer-generated texts. With bots, the writing of texts turns into a second-order creation, the writing of word lists, templates and rules, to generate the text-to-be-seen, the output for the reader to encounter.Tämä opinnäytetyö keskittyy esittelemään, kuinka Twitter-botteja on mahdollista analysoida elektronisen kirjallisuuden näkökulmasta ja kuinka niiden analyysi poikkeaa muiden elektronisen kirjallisuuden teosten tutkimisesta. Vaikka elektronisen kirjallisuuden tutkimusta on tehty joitain vuosikymmeniä, ei erityisesti botteihin keskittyvää tutkimusta ole juurikaan tuotettu. Tässä tutkimuksessa analysoidaan historiallisia ja nykyaikaisia tekstigeneraattoreita, elektronisen kirjallisuuden tutkijoiden teorioita teosten lukemisesta ja luomisesta sekä botin tekijöiden käytännön huomioita bottien kirjoittamisesta, joiden pohjalta luodaan kuva botin luomisprosessista ja erilaisiin botteihin liittyvistä ominaispiirteistä. Bottien lähdekoodi on harvoin vapaasti luettavissa, minkä vuoksi bottien analysointi eroaa merkittävästi muiden tekstigeneraattoreiden tutkimuksesta. Monet teoreetikot pitävät lähdekoodin lukemista olennaisena tapana analysoida elektronisen kirjallisuuden teoksia. Tämä opinnäytetyö esittelee vaihtoehtoisen tavan analysoida botteja. Botin tuottamien päivitysten vertailu keskenään auttaa näkemään botin lähdekoodissa käytetyt toistuvat kaavat sekä ymmärtämään tarkemmin botin tekstin tuottavia menetelmiä ja niihin liittyviä taiteellisia valintoja. Esitelty metodi ottaa huomioon erityyppisten bottien ominaispiirteet, keskittyen kaavapohjaisiin botteihin, jotka asettelevat yksittäisiä sanoja valmiisiin lausepohjiin, ja listapohjaisiin botteihin, jotka käyvät järjestelmällisesti läpi suuria tietokantoja. Tutkimuksessa läpikäytyjen vanhempien elektronisen ja proseduraalisen kirjallisuuden teosten ja nykyaikaisten bottien analyysin pohjalta voidaan päätellä, ettei bottien analysoiminen tai tekeminen vaadi ohjelmakoodin ymmärtämistä: on tärkeämpää, että botin lukija/tekijä ymmärtää prosessipohjaisen tekstitaiteen lainalaisuuksia sekä tekijän valintojen merkityksen käytettyjen materiaalien kirjoittamisessa ja kuratoinnissa. Botit ja tekstigeneraattorit kyseenalaistavat usein myös tekijyyden käsitteen. Niiden luomisprosessien analyysi osoittaa kuitenkin kiistattomasti, että tietokoneavusteinen tekstintuottaminen vaatii ihmisen luovuutta suunnitteluvaiheessa. Bottien tekemisessä kirjoittaminen vaihtuu toisen asteen luomiseksi, sanalistojen, lausepohjien ja sääntöjen kirjoittamiseksi, joiden pohjalta botti tuottaa lukijalle näytettävät tekstit, joita kuvataan otsikon termillä “the text-to-be-seen”

‘Conspiracy Machines’ - The Role of Social Bots during the COVID-19 ‘Infodemic’

The omnipresent COVID-19 pandemic gave rise to a parallel spreading of misinformation, also referred to as an ‘Infodemic’. Consequently, social media have become targets for the application of social bots, that is, algorithms that mimic human behaviour. Their ability to exert influence on social media can be exploited by amplifying misinformation, rumours, or conspiracy theories which might be harmful to society and the mastery of the pandemic. By applying social bot detection and content analysis techniques, this study aims to determine the extent to which social bots interfere with COVID19 discussions on Twitter. A total of 78 presumptive bots were detected within a sample of 542,345 users. The analysis revealed that bot-like users who disseminate misinformation, at the same time, intersperse news from renowned sources. The findings of this research provide implications for improved bot detection and managing potential threats through social bots during ongoing and future crises