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Nick Drnaso’s graphic novel Sabrina provides a powerful snapshot of online norms. The picture is not pretty. A young woman goes missing. Her grief-struck boyfriend cannot bear to stay in their home and escapes to a friend’s house. Her sister struggles with the pain of her loss. We learn that the woman’s neighbor, a misogynist loner, killed her and recorded the murder. Online, people clamor for the video. The execution video leaks and goes viral. The media hounds the woman’s sister and her boyfriend. A conspiracy theorist with a popular radio show argues that the murder is a deep-state hoax. He gins up a cyber mob to “investigate” what is really going on. A cyber mob descends. The woman’s family, boyfriend, and her boyfriend’s friend are smeared as crisis actors. They are barraged with death threats, and their personal information is posted far and wide. The attacks continue until a shooting massacre captures the conspiracy theorist’s attention. The cyber mob redirects its wrath at other mourners. The novel raises important questions about the interaction of human behavior, culture, and law in the digital age. What compels people to like, click, and share grotesque execution videos, conspiracy theories, and destructive falsehoods? We have always been drawn to information that resonates with us, but the online environment seems to supercharge human biases. Why? Platforms structure and shape online activity, so what are they doing about online abuse? Each and every one of us is ultimately responsible for liking, clicking, and sharing the destruction. How can we work to change our behavior?

The purpose of this paper is to discuss the design, application and findings of a case study in which the application of a machine learning algorithm is utilised to identify the grievances in Twitter in an Arabian context. To understand the characteristics of the Twitter users who expressed the identified grievances, data mining techniques and social network analysis were utilised. The study extracted a total of 23,363 tweets and these were stored as a data set. The machine learning algorithm applied to this data set was followed by utilising a data mining process to explore the characteristics of the Twitter feed users. The network of the users was mapped and the individual level of interactivity and network density were calculated. Findings The machine learning algorithm revealed 12 themes all of which were underpinned by the coalition of Arab countries blockade of Qatar. The data mining analysis revealed that the tweets could be clustered in three clusters, the main cluster included users with a large number of followers and friends but who did not mention other users in their tweets. The social network analysis revealed that whilst a large proportion of users engaged in direct messages with others, the network ties between them were not registered as strong. Borum (2011) notes that invoking grievances is the first step in the radicalisation process. It is hoped that by understanding these grievances, the study will shed light on what radical groups could invoke to win the sympathy of aggrieved people. In combination, the machine learning algorithm offered insights into the grievances expressed within the tweets in an Arabian context. The data mining and the social network analyses revealed the characteristics of the Twitter users highlighting identifying and managing early intervention of radicalisation.

This thesis concerns the possibility of deceiving cyberterrorists using defensive deception methods. As cyberspace today is a battleground for myriad cyber attacks and intrusions, it may only be a matter of time before terrorists choose to advance their deadly cause in cyberspace. We explore some of the questions raised regarding the threat of cyberterrorism by examining different perspectives, motivations, actors, targets, and how they may be confronted. One way is to draw from the lessons of deception and apply them against cyberterrorist attacks. Cyber deception applies in cyberspace just as well as deception in military battles. From the different categories of attackers that could perpetrate cyberterrorism, we examine the ways in which they may be deceived. Many of the methods and tools that cyberterrorists would use are similar to those used by other less malicious hackers, so we can plan specific deceptions to use against them in advance.

This study researches the varying threats that emanate from terrorists who carry their activity into the online arena. It examines several elements of this threat. First, it explores elements of virtual to virtual attacks. Second, it looks at threats against critical infrastructures that can be traced to online sources. Third, this thesis reports on ways that terrorists are using information technology such as the Internet for propaganda and communication purposes. Finally, it highlights the most crucial ways in which the United States government has responded to the problem. It concludes with a few recommendations for best practices for future engagement with varying aspects of cyberterrorism.

The US electricity infrastructure uses Industrial Control Systems (ICS) to oversee its operations. These systems are connected online for better efficiency, making them susceptible to cyberattacks. Current research has extensively addressed ICS vulnerabilities that can be exploited by cybercriminals. Vulnerabilities, however, are only one of the many factors influencing offender decision-making in cyberattacks. Furthermore, numerous conceptions of threats, vulnerabilities, and consequences exist, which further complicate ICS security assessments. This exploratory study therefore has two main goals. First, it seeks to compare industry and hacker perceptions on electricity ICS threats, vulnerabilities, and consequences. Second, it seeks to identify a broader set of factors that influence offender decision-making in ICS cyberattacks.

This thesis explores the nature of cyber security at the beginning of the 21st century. In the current security paradigm, security strategies based on anticipatory governance have become essential in the management of the constantly changing cyber security environment. Thus, this thesis aims to understand security strategies and governance introduced in the European region. The increased dependency on cyber space is visible in all public private sectors and governmental operations, as well as communications between groups and individuals. As a result, cyber attacks on public and private entities are increasing. This requires a security framework that is flexible and establishes different types of security cooperation to manage the widespread cyber risks. This is essential to the development of security strategies, governance forms, practices, and guidelines for enhancing resilience and preparedness towards cyber risks. Therefore, I am examining cyber security through the lenses of nodal governance and governmentality, which enables me to understand European cyber security strategies and governance forms developed by the Council of Europe, the European Union, and the North Atlantic Treaty Organization. To analyse existing strategies and governance forms, I have used two critical security schools, the Copenhagen School and the Paris School, which cover different aspects of the security agenda. The thesis develops a substantive analytical framework through two case studies, namely cyber security and cyber terrorism. The findings in this thesis identifies problem areas, such as the complexity of the nodal system, the legislative lacuna, reliance on different governance forms, transparency and accountability, and types of anticipatory governance and regulatory practices.