Biblio

The development of future cyber terrorism scenarios is a key component in building a more comprehensive understanding of cyber threats that are likely to emerge in the near-to mid-term future. While developing concepts of likely new, emerging digital technologies is an important part of this process, this article suggests that understanding the psychological and social forces involved in cyber terrorism is also a key component in the analysis and that the synergy of these two dimensions may produce more accurate and detailed future cyber threat scenarios than either analytical element alone.

South Africa's lead-users predilections to tinker and innovate mobile banking services is driven by various constructs. Advanced technologies have made mobile banking services easy to use, attractive and beneficial. While this is welcome news to many, there are concerns that when lead-users tinker with these services, information security risks are exacerbated. The aim of this article is to present an insightful understanding of the demand-side predilections of South Africa's lead-users in such contexts. We assimilate the theories of Usage Control, (UCON), the Theory of Technology Acceptance Model (TAM), and the Theory of Perceived Risk (TPP) to explain predilections over technology. We demonstrate that constructs derived from these theories can explain the general demand-side predilection to tinker with mobile banking services. A quantitative approach was used to test this. From a sample of South African banking lead-users operating in Gauteng province of South Africa, data was collected and analysed with the help of a software package. We found unexpectedly that, lead-users predilections to tinker with mobile banking services was inhibited by perceived risk. Moreover, male lead-users were more domineering in the tinkering process than female lead-users. The implication for this is discussed and explained in the main body of work.

Conventional wisdom is that the textbook view describes reality, and only bad people (not good people trying to get their jobs done) break the rules. And yet it doesn't, and good people circumvent.
 

Phishing is an act of technology-based deception that targets individuals to obtain information. To minimize the number of phishing attacks, factors that influence the ability to identify phishing attempts must be examined. The present study aimed to determine how individual differences relate to performance on a phishing task. Undergraduate students completed a questionnaire designed to assess impulsivity, trust, personality characteristics, and Internet/security habits. Participants performed an email task where they had to discriminate between legitimate emails and phishing attempts. Researchers assessed performance in terms of correctly identifying all email types (overall accuracy) as well as accuracy in identifying phishing emails (phishing accuracy). Results indicated that overall and phishing accuracy each possessed unique trust, personality, and impulsivity predictors, but shared one significant behavioral predictor. These results present distinct predictors of phishing susceptibility that should be incorporated in the development of anti-phishing technology and training.

The huge amount of user log data collected by search engine providers creates new opportunities to understand user loyalty and defection behavior at an unprecedented scale. However, this also poses a great challenge to analyze the behavior and glean insights into the complex, large data. In this paper, we introduce LoyalTracker, a visual analytics system to track user loyalty and switching behavior towards multiple search engines from the vast amount of user log data. We propose a new interactive visualization technique (flow view) based on a flow metaphor, which conveys a proper visual summary of the dynamics of user loyalty of thousands of users over time. Two other visualization techniques, a density map and a word cloud, are integrated to enable analysts to gain further insights into the patterns identified by the flow view. Case studies and the interview with domain experts are conducted to demonstrate the usefulness of our technique in understanding user loyalty and switching behavior in search engines.
 

User authentication depends largely on the concept of passwords. However, users find it difficult to remember alphanumerical passwords over time. When user is required to choose a secure password, they tend to choose an easy, short and insecure password. Graphical password method is proposed as an alternative solution to text-based alphanumerical passwords. The reason of such proposal is that human brain is better in recognizing and memorizing pictures compared to traditional alphanumerical string. Therefore, in this paper, we propose a conceptual framework to better understand the user performance for new high-end graphical password method. Our proposed framework is based on hybrid approach combining different features into one. The user performance experimental analysis pointed out the effectiveness of the proposed framework.
 

Computing systems today have a large number of security configuration settings that enforce security properties. However, vulnerabilities and incorrect configuration increase the potential for attacks. Provable verification and simulation tools have been introduced to eliminate configuration conflicts and weaknesses, which can increase system robustness against attacks. Most of these tools require special knowledge in formal methods and precise specification for requirements in special languages, in addition to their excessive need for computing resources. Video games have been utilized by researchers to make educational software more attractive and engaging. Publishing these games for crowdsourcing can also stimulate competition between players and increase the game educational value. In this paper we introduce a game interface, called NetMaze, that represents the network configuration verification problem as a video game and allows for attack analysis. We aim to make the security analysis and hardening usable and accurately achievable, using the power of video games and the wisdom of crowdsourcing. Players can easily discover weaknesses in network configuration and investigate new attack scenarios. In addition, the gameplay scenarios can also be used to analyze and learn attack attribution considering human factors. In this paper, we present a provable mapping from the network configuration to 3D game objects.
 

Despite all the current controversies, the success of the email service is still valid. The ease of use of its various features contributed to its widespread adoption. In general, the email system provides for all its users the same set of features controlled by a single monolithic policy. Such solutions are efficient but limited because they grant no place for the concept of usage which denotes a user's intention of communication: private, professional, administrative, official, military. The ability to efficiently send emails from mobile devices creates new interesting opportunities. We argue that the context (location, time, device, operating system, access network...) of the email sender appears as a new dimension we have to take into account to complete the picture. Context is clearly orthogonal to usage because a same usage may require different features depending of the context. It is clear that there is no global policy meeting requirements of all possible usages and contexts. To address this problem, we propose to define a correspondence model which for a given usage and context allows to derive a correspondence type encapsulating the exact set of required features. With this model, it becomes possible to define an advanced email system which may cope with multiple policies instead of a single monolithic one. By allowing a user to select the exact policy coping with her needs, we argue that our approach reduces the risk-taking allowing the email system to slide from a trusted one to a confident one.

Phishing continues to remain a lucrative market for cyber criminals, mostly because of the vulnerable human element. Through emails and spoofed-websites, phishers exploit almost any opportunity using major events, considerable financial awards, fake warnings and the trusted reputation of established organizations, as a basis to gain their victims' trust. For many years, humans have often been referred to as the `weakest link' towards protecting information. To gain their victims' trust, phishers continue to use sophisticated looking emails and spoofed websites to trick them, and rely on their victims' lack of knowledge, lax security behavior and organizations' inadequate security measures towards protecting itself and their clients. As such, phishing security controls and vulnerabilities can arguably be classified into three main elements namely human factors (H), organizational aspects (O) and technological controls (T). All three of these elements have the common feature of human involvement and as such, security gaps are inevitable. Each element also functions as both security control and security vulnerability. A holistic framework towards combatting phishing is required whereby the human feature in all three of these elements is enhanced by means of a security education, training and awareness programme. This paper discusses the educational factors required to form part of a holistic framework, addressing the HOT elements as well as the relationships between these elements towards combatting phishing. The development of this framework uses the principles of design science to ensure that it is developed with rigor. Furthermore, this paper reports on the verification of the framework.

Distributed Denial of Service (DDoS) attacks are one of the most important threads in network systems. Due to the distributed nature, DDoS attacks are very hard to detect, while they also have the destructive potential of classical denial of service attacks. In this study, a novel 2-step system is proposed for the detection of DDoS attacks. In the first step an anomaly detection is performed on the destination IP traffic. If an anomaly is detected on the network, the system proceeds into the second step where a decision on every user is made due to the behaviour models. Hence, it is possible to detect attacks in the network that diverges from users' behavior model.

While automated methods are the first line of defense for detecting attacks on webservers, a human agent is required to understand the attacker's intent and the attack process. The goal of this research is to understand the value of various log fields and the cognitive processes by which log information is grouped, searched, and correlated. Such knowledge will enable the development of human-focused log file investigation technologies. We performed controlled experiments with 65 subjects (IT professionals and novices) who investigated excerpts from six webserver log files. Quantitative and qualitative data were gathered to: 1) analyze subject accuracy in identifying malicious activity; 2) identify the most useful pieces of log file information; and 3) understand the techniques and strategies used by subjects to process the information. Statistically significant effects were observed in the accuracy of identifying attacks and time taken depending on the type of attack. Systematic differences were also observed in the log fields used by high-performing and low-performing groups. The findings include: 1) new insights into how specific log data fields are used to effectively assess potentially malicious activity; 2) obfuscating factors in log data from a human cognitive perspective; and 3) practical implications for tools to support log file investigations.

Information system developers and administrators often overlook critical security requirements and best practices. This may be due to lack of tools and techniques that allow practitioners to tailor security knowledge to their particular context. In order to explore the impact of new security methods, we must improve our ability to study the impact of security tools and methods on software and system development. In this paper, we present early findings of an experiment to assess the extent to which the number and type of examples used in security training stimuli can impact security problem solving. To motivate this research, we formulate hypotheses from analogical transfer theory in psychology. The independent variables include number of problem surfaces and schemas, and the dependent variable is the answer accuracy. Our study results do not show a statistically significant difference in performance when the number and types of examples are varied. We discuss the limitations, threats to validity and opportunities for future studies in this area.