Bots. Nick Monaco

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СКАЧАТЬ low-profile products. Some spambots function like crawlers, trawling the internet, looking for accessible comments sections to load up with spam or scraping webpages for email addresses to spam with emails. Examples of these crawler-type email scrapers include the ActiveAgent and RoverBot examples discussed in the previous section (Hayati et al., 2009; Leonard, 1997b pp. 140–148). Other spambots target social media sites, overloading users with malicious links or product promotion (Keelan et al., 2010). While spam is normally aimed at making money rather than disseminating political messaging, networks of social spambots can be reappropriated for political messaging with the flip of a switch (Monaco, 2019a; Thomas et al., 2012).

Cyborgs

The “cyborg” bot is a hybrid type of bot that does not fit perfectly into any of the previous categories. Cyborgs are a special form of social bot – automated accounts on social media that can be thought of as “bot-assisted human” or a “human-assisted bot” (Zi et al., 2010). However, the line between fully automated bot and cyborg bot is fuzzy, for it has “never been clear exactly how much automation makes a human user a cyborg, or how much human intervention is needed to make a bot a cyborg” (Gorwa & Guilbeault, 2018).

      Since cyborgs are partially controlled by humans, they leave different, less predictable activity signatures than normal, fully automated bots. For this reason, they are often able to slip through social media companies’ cybersecurity and bot detection algorithms. In the past few years, they have become increasingly common as a tool for political messaging (Woolley, 2020a, p. 85); for example, during the 2019 US Democratic presidential primary debates, one cyborg called the YangGang RT bot retweeted mentions of candidate Andrew Yang (Monaco, 2019b). Another recent form of cyborg political activism and campaigning is the “Volunteer botnet” – the willing temporary donation of one’s social media account to be used as a bot for political campaigning (Woolley & Monaco, 2020). We’ll cover cyborgs in greater depth in our chapter on political bots.

Zombies, or compromised-device bots

A relatively unfamiliar type of bot for the general public is the “zombie” device – any internet-connected device (computer, phone, fridge, smart TV, etc.) that has been hacked and is controlled by a malicious hacker. These “zombie” devices can become nodes in bot networks, sending out billions of spam emails per day or overloading target servers and websites in what is known as a distributed denial of service (DDoS) attack (Rodríguez-Gómez et al., 2013). Indeed, most DDoS attacks are carried out using botnets of compromised devices. This meaning of the term “bot” became common in the 2000s (Yang et al., 2014).

Lots of bots – botnets

      Automated agents often work in concert with one another in “botnets” (short for “bot networks”) – a network of computer programs that work together to accomplish the same goal. The networked bots’ functions need not be identical: often, the bots in a network perform complementary functions (Cresci, 2020). For example, imagine a small network of Twitter bots that promote the hashtag #TacoTuesday on Twitter. The network might have 100 bots split evenly into seeders and promoters, with the 50 seeder bots dedicated to sending out pre-composed tweets that include the hashtag #TacoTuesday and the remaining 50 promoter bots used to retweet and like posts from the seeders. None of the 100 bots necessarily need to follow each other in order to be considered a botnet – they only need to be working toward the same goal. This group of 100 bots is therefore a botnet, for they share the common goal of promoting #TacoTuesday.

Botnets are not necessarily networks of social bots, like our #TacoTuesday botnet. The word botnet is also used to designate a network of compromised devices – the zombie bots described above. When a hacker gains administrative access to a computer, it can use that computer to perform any task, often without the owner’s knowledge. (Here, we mean “computer” in the broadest sense: any internet-connected device capable of receiving and carrying out instructions.) When a large number of these compromised internet-connected devices are networked together, a single hacker has a surplus of computing power that they can use to do whatever they want: steal the computer owners’ private information, exploit the spare computing power to make money by mining cryptocurrencies (cryptojacking), or use them to crash targeted websites via distributed denial-of-service, or DDoS, attacks.

      DDoS attacks work by vastly overloading a website, driving so much traffic to it that its infrastructure collapses – imagine 10,000 cars all trying to get off of a one-lane highway exit at once, or a lecture hall of 1,000 students all asking the professor a question at the exact same time. These DDoS attacks have gotten larger and larger, driving larger and larger amounts of traffic to sites via botnets, because there is an enormous and growing pool of devices available for compromise: the rapidly growing Internet-of-Things (IoT). IoT is a term used to describe internet-connected devices that we may not traditionally think of as computers – DVD players, refrigerators, smart doorbells, laundry machines, TVs, cars, drones, baby monitors, etc. Because these internet-connected mundane household appliances are rarely designed with cybersecurity in mind, they are far too easy to compromise and turn into botnets. For example, in 2016, the Mirai botnet used over 400,000 internet-connected devices to bring down servers at the French web hosting service OVH and the web application company Dyn. The attack disrupted the services of several popular websites, including Amazon, Netflix, the New York Times, and Twitter. (Most of the compromised devices were hacked using a list of just 62 default usernames and passwords commonly used on IoT devices (United States Cybersecurity & Infrastructure Security Agency, 2016).)

Misnomers and Misuse

As the previous section illustrated, the term “bot” can have several possible meanings. However, the most common popular notion of the bot – that of the heavily argumentative troll account or inauthentic social media account operated by a human – is technically not necessarily an automated bot at all: these accounts are more correctly called “sock puppet” or “troll” accounts (Gorwa & Guilbeault, 2018). (Note that the meaning of the terms bot, troll, and sock puppet may differ significantly from language to language. For instance, in Polish, many speakers use “bot” and “troll” interchangeably to indicate a manipulative online social media account, whether automated or manually controlled (Gorwa, 2017a).)¹⁴

      We highlight these misuses and ambiguities in order to help the reader clearly understand what the term “bot” may mean when encountered in the wild. In this book, when we use the term bot, we will always be referring to a program that is partially or fully automated.

Important bot characteristics

      Finally, there are a range of bot characteristics that can be used to describe a bot’s behavior or evaluate its intentions (Maus, 2017).

       Transparency – does the bot clearly state that it is an automated agent, or does it attempt to hide its automation, playing itself off as human?

       Degree of automation – is the bot automated all of the time? Do some of its actions only occur with human intervention? Can a human operate the bot while it is also performing other operations autonomously? (These questions all relate to the relative “cyborg-ness” of the bot.)

       Coordination with other bots – does this bot operate as part of a botnet or with other deceptive human users?

       Interaction and passivity – does this bot interact with or engage with human users in any way (likes, retweets, shares, conversation, etc.)? Are other users aware that the bot is present in the online environment? Does it silently surveil or collect data on other users or websites?

       Intent – what is the goal of this СКАЧАТЬ