Key Roles of Viruses in Social Networks - Essay Example

Key Roles of Viruses in Social Networks KEY ROLES OF VIRUSES IN SOCIAL NETWORKS Social networks, especially those propagated online, are primarily grounded on real relationships happening in society. Therefore, computer virus writers are fast taking this fact as an advantage as they seek to propagate viral codes in online social networks (Özyer, 2013: p45). These instances have occurred in the recent past, such as the extensive computer virus attack on Facebook. Usually, these computer virus attacks lead to the compromise of numerous accounts that could include confidential and personal data and information. If a computer virus is able deceive social network participants through the choice of topics that interest them, propagation of the virus undergoes an exponential increase. By nature, online social networks are websites, platforms, or services built on the basis of relationships between people. The propagation of computer viruses on these networks has taken on significant security importance, especially because the interactive nature of social networks makes propagation faster than on traditional platforms (Özyer, 2013: p45). Computer virus writers are also able to form botnets, steal information, mount service denial attacks, profit, and propagate spam using computer viruses. In an online social network, the user is represented by their profile, which they use in the formation of virtual relationships and friendships (Özyer, 2013: p46). Therefore, they are able to add people they know socially in the real world as friends, while also deciding to be friends with others or not. As soon as two individuals accept each other’s social overtures, they can send and receive information to and from one another’s posts, although they may also restrict their accessibility to friends to a particular degree. However, for the purpose of this paper, it will be assumed that there is always a connection between the users and that they can send readable messages to one another. Fundamentally, majority of social network’s computer viruses work by exploiting the trust that users of the networks have between each other. For example, a social network user who has already been infected with a computer virus will send a message that contains the malicious links to other virtual friends. When the messages are received, users have different reactions with some following the provided link and executing the computer virus, while others may detect the danger posed by the message and deletes it sans executing it. It is, however, important to note that some computer viruses do not need the intervention of users for them to spread. In these specific forms of computer viruses like XSS or Cross Site Scripting types, the social network user will be infected by the virus because of a flaw in the application functions of the website (Özyer, 2013: p47). The social network graph regarding the propagation of computer viruses is characterized by the clustering coefficient to varying degrees. This effect of clustering coefficient appears to be linear on the speed of computer virus propagation on social networks (Barabási, 2012: p91). User factor or behaviour is also a significant influence on the propagation of computer viruses on social networks. This means that if the computer virus writers try to identify the topic of their posts based on techniques of social engineering that seek to arouse their victims’ interest, they can speed up the computer virus’ propagation. Finally, the reaction of the user is also critical in how the computer virus will propagate across the social network. Different types of computer viruses propagate in different ways, depending on how they were written. There are various types of computer viruses that propagate through social networks, including Cross Site Scripting or XSS, ClickJacking, and Trojan types. The first online social network virus attacked MySpace in the year 2005, exploiting vulnerability in cross-site scripting within the web application in MySpace (Barabási, 2012: p92). This caused an infection in twenty-four hours of approximately one million social network users. A cross site scripting computer virus, also known as an XSS worm, propagates as a malicious code automatically among website users as they attempt to infect other visitors and user progressively (Barabási, 2012: p92). This computer virus exploits the vulnerabilities in existence within the website to spread in the form of a viral code. This virus is important in social network security because of how it propagates itself. The first step involves the addition of a malicious payload to the social network users profile by the creator. After which, any subsequent visitor to the profile gets infected as well, and the malicious payload is attached to their user profile as a result of flaws in cross site scripting, which acts through exploitation of the AJAX (Barabási, 2012: p93). In this case, the profile of the visitor is transformed by the virus into a virulent profile that helps it to spread to new sources of infection. Trojan types are another class of important computer viruses that propagate on social networks, especially the Koobface type. Initially isolated in the year 1998, it applies self-directed propagation in social networks through the use of messages that have interesting topics that deceive the social network user (Marinescu et al, 2011: p16). For example, one message could redirect users to malicious sites using links on the social sites where the user is prompted to click on a download tab for what they pass off as a Flash Player update. If they go ahead to download the file and execute it, their computers are infected by the computer virus, which turns it into a botnet zombie. In addition, the profile that is infected will send messages attached to the profile to every one on their list in an attempt to find another vulnerable victim for the viral propagation (Marinescu et al, 2011: p16). The ClickJacking computer virus also plays a crucial role in social networks and is referred to as UI redressing and LikeJacking. This technique involves the creation of a website by the attacker, showing a fake video player from websites like YouTube, as well as other graphical baits that seek to persuade social network users to click on the play tab so as to view the video (Galloway & Thacker, 2013: p12). However, this computer virus is important for another role in that it acts as a covert Facebook like button, which can be used to increase the number of likes on a profile for profit and reputation gains. This virus uses UI redressing to hide the like button and what they like is displayed on the social network user’s profile, after which friends of the victim may be interested, in the like and click on it, to become a new infection source. In addition, this malicious computer virus may also be combined with the Trojan computer virus to create a hybrid (Galloway & Thacker, 2013: p13). ClickJacking and Trojan computer viruses require that the user intervenes before they are propagated and, thus, can be stopped if the user suspects them for what they are. They propagate in the same manner because malicious links are attached to the profiles of victims, following which the friends of these victims interact with it and propagate the computer virus. The clustering structure in computer virus graphs leads to reduction in the computer virus’ spread over social network, which allows for online social network users to implement good systems of monitoring so as to defend their profiles from the early stages of computer virus propagation (Galloway & Thacker, 2013: p13). This could lead to a new system of detection. In addition, computer viruses and their propagation are studied in order to teach users how to distinguish between benign and malicious virulent posts, which decrease the rate and speed of the virus propagation. This is because if the social network user clicks on a malicious website link on the network and proceeds to execute the computer virus, the speed of propagation increases (Galloway & Thacker, 2013: p14). Therefore, it is better for these events to be tracked, and official posts released to warn users about them. There have been recent intensive investigations into the role of computer virus propagation, in social networks, majority of which are based on the analysis of the spread of epidemics. Propagation of computer viruses in small-world-networks, propagation in scale-free network structures like mobile networks, IM networks, and e-mails have been of special importance (Harvey et al, 2011: p369). The first research covering online special networks involved the modelling of the cross-site scripting computer virus through the use susceptible, infected or SI models. In this model, every social network user can be susceptible to attack by a computer virus or infection by the same. Investigations into the roles played by computer viruses in social networks can also involve the use of simulated user activities and topologies. This is mainly used for investigation, into the roles of, cross-site scripting type computer virus propagation. While the likelihood of executing Trojan type computer viruses in online social networks has been investigated as well, this has not gone as far as to examine the roles they play. In recent research studies, a real network topology has also been used in conjunction with the application of realistic activities of the user. In this case, the activity of the user is of utmost importance in the propagation of computer viruses. A correlation-grounded system has also been proposed to mitigate the propagation of computer viruses in social networks based on the Flickr network (Harvey et al, 2011: p369). The trend of computer virus propagation and the roles that different computer viruses play can best be examined through simulations. In these simulations, the variables are changed to see how the propagation of the computer viruses changes. This allows for the study of clustering coefficient that is a major element of the social network graph regarding the propagation of computer viruses. In this case, the higher the degree of clustered networks, the slower the propagation of computer viruses. This is caused by an inner link structure of the graph representing social networks, of which the effect is an opportunity for them to countermeasure the early stages of computer virus spread. Simulation also occurs through a variance of executing probability and tracking the computer virus. Where the social network users follow links with malicious intent and have a higher probability of executing them, the sped of propagation increases exponentially. References Barabási, A.L., 2012. Linked: the new science of networks. Cambridge, Mass, Perseus Pub. Galloway, A. R. & Thacker, E., 2013. The exploit a theory of networks. Minneapolis, University of Minnesota Press. Harvey, C. G. Stewart, D. B. & Ewing, M. T., 2011. Forward or delete: What drives peer-to-peer message propagation across social networks? Journal of Consumer Behaviour. 10 (6), 365-372. Marinescu, M. De, S. & Carretero J., 2011. Leveraging social networks for understanding the evolution of epidemics. BMC Systems Biology. 5(3), 14-18 Özyer, T., 2013. The influence of technology on social network analysis and mining. Vienna, Springer. Read More