Cybersecurity has become one of the most pressing issues facing society today. In particular, cybercriminals often congregate within online communities to exchange knowledge and assets. As a result, there has been a strong interest in recent years in developing a deeper understanding on cybercriminal behaviors, the global cybercriminal supply chain, emerging threats, and various other cybersecurity-related activities. However, few works in recent years have focused on identifying, collecting, and analyzing cybercriminal contents. Despite the high societal impact of cybercriminal community research, only a few studies have leveraged these rich data sources in their totality, and those that do often resort to manual data collection and analysis techniques. In this dissertation, I address two broad research questions: 1) In what ways can I advance cybersecurity as a science by scrutinizing the contents of online cybercriminal communities? and 2) How can I make use of computational methodologies to identify, collect, and analyze cybercriminal communities in an automated and scalable manner? To these ends, the dissertation comprises four essays. The first essay introduces a set of computational methodologies and research guidelines for conducting cybercriminal community research. To this point, there has been no literature establishing a clear route for non-technical and non-security researchers to begin studying such communities. The second essay examines possible motives for prolonged participation by individuals within cybercriminal communities. The third essay develops new neural network language model (NNLM) capabilities and applies them to cybercriminal community data in order to understand hacker-specific language evolution and to identify emerging threats. The last essay focuses on developing a NNLM-based framework for identifying information dissemination among varying international cybercriminal populations by examining multilingual cybercriminal forums. These essays help further establish cybersecurity as a science.

Botnets, networks of hundreds to millions of computers, controlled by one or more individuals, increasingly play a part in cybercrimes, with astonishing results. The access of a botnet gives the controller abilities of a large majority of all the cyberattacks over the internet, and with the possibility of buying a complete botnet, this opens the market to nontechnical criminals. The Darknet and the market it provides, enable the buyers to buy and trade everything from botnets and malware to complete schemes.   The increase in cybercriminal activities and organizations has been alarmingly high in recent years, and no wonder, when criminals just need to invest a small amount of money to gain potentially millions of dollars without any advance knowledge of computer science, and with only a slight chance of getting caught due to the anonymity of the internet and botnets.   Based on a literature review combined with a critically reflective analysis of a selection of information about botnets from other sources available on the internet, this paper has identified some of the main types of organizations used in cybercrime and their operations as well as basic information about botnets, the players and stakeholders in this area, the theft and schemes used by botnets and the online money laundering service involved.

This study proposes that individual personality characteristics and behavioral triggering effects come together to motivate online victimization. It draws from psychology’s current understanding of personality traits, attribution theory, and criminological research. This study combines the current computer deviancy and hacker taxonomies with that of the Dark Triad model of personality mapping. Each computer deviant behavior is identified by its distinct dimensions of cyber-criminal behavior (e.g., unethical hacking, cyberbullying, cyberstalking, and identity theft) and analyzed against the Dark Triad personality factors (i.e., narcissism, Machiavellianism, and psychopathy). The goal of this study is to explore whether there are significant relationships among the Dark Triad personality traits and specific cyber-criminal behaviors within social network sites (SNSs). The study targets offensive security engineers and computer deviants from specific hacker conferences and from websites that discuss or promote computer deviant behavior (e.g., hacking). Additional sampling is taken from a general population of SNS users. Using a snowball sampling method, 235 subjects completed an anonymous, self-report survey that includes items measuring computer deviance, personality traits, and demographics. Results yield that there was no significant relationship between Dark Triad and cyber-criminal behaviors defined in the perceived hypotheses. The final chapter of the study summarizes the results and discusses the mechanisms potentially underlying the findings. In the context of achieving the latter objective, exploratory analyses are incorporated and partly relied upon. It also includes a discussion concerning the implications of the findings in terms of providing theoretical insights on the Dark Triad traits and cyber-criminal behaviors more generally.

Recent trends in social network services (SNS) have taken the rates of personal information sharing, storage and processing to an unprecedented level, which yield both benefits and undesirable consequences for their users. SNS is being exploited by criminals to fraudulently obtain information from unsuspecting users. User’s awareness of privacy protection has been far left behind by the increasing and popularizing utilization of social network services (SNS), the privacy security problems will become one of the important factors influencing the healthy development of social network service industry. This study was designed to collect data and produce knowledge about the security awareness of WeChat users (i.e., randomly selected from all over China), their preferences and their experience of using WeChat while facing security issues as well as the perspectives of how people perceive a specific security problems, in order to find out what factors influence user's security awareness. In order to carefully conduct the research process and explain the empirical findings, seven principles of interpretive field research and protection motivation theory is adopted as core theoretical foundation. Participants were asked to provide information about and their personal views of questions from their different experience and value. Eight persons interviewed for our research and their responses confirmed our objectives of the study. As a result, six factors are indentified in related to WeChat user’s security awareness. PMT helps to explain and understand that how six indentified concepts influence behaviour intention and security awareness of user.

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In recent times, due to the development of information technology,a new form of crime called informational crimes has developed. in relation to this new type of crime, a special criminal law was issued, whose purpose is to prevent and punish illegal activities that affect computer systems and datas, secret communications, and other legal goods that are affected withthis type of crime, such as equity, public faith and sexual freedom. / En los últimos tiempos, producto del desarrollo de las tecnologías informáticas se ha ido desarrollando una nueva forma de criminalidad denominada delitos informativos. en relación a esta nueva forma delictiva, se ha emitido una Ley penal especial cuya finalidad es prevenir y sancionar las conductas ilícitas que afectan los sistemas y datos informáticos, así como el secreto de las comunicaciones, y los demás bienes jurídicos que resulten afectados con esta modalidad delictiva, como son el patrimonio, la fe pública y la libertad sexual.