Occupational Fraud Detection Through Visualization

Occupational fraud affects many companies worldwide causing them economic loss and liability issues towards their customers and other involved entities. Detecting internal fraud in a company requires significant effort and, unfortunately cannot be entirely prevented. The internal auditors have to process a huge amount of data produced by diverse systems, which are in most cases in textual form, with little automated support. In this paper, we exploit the advantages of information visualization and present a system that aims to detect occupational fraud in systems which involve a pair of entities (e.g., an employee and a client) and periodic activity. The main visualization is based on a spiral system on which the events are drawn appropriately according to their time-stamp. Suspicious events are considered those which appear along the same radius or on close radii of the spiral. Before producing the visualization, the system ranks both involved entities according to the specifications of the internal auditor and generates a video file of the activity such that events with strong evidence of fraud appear first in the video. The system is also equipped with several different visualizations and mechanisms in order to meet the requirements of an internal fraud detection system

Dynamic Geospatial Spectrum Modelling: Taxonomy, Options and Consequences

Much of the research in Dynamic Spectrum Access (DSA) has focused on opportunistic access in the temporal domain. While this has been quite useful in establishing the technical feasibility of DSA systems, it has missed large sections of the overall DSA problem space. In this paper, we argue that the spatio-temporal operating context of specific environments matters to the selection of the appropriate technology for learning context information. We identify twelve potential operating environments and compare four context awareness approaches (on-board sensing, databases, sensor networks, and cooperative sharing) for these environments. Since our point of view is overall system cost and efficiency, this analysis has utility for those regulators whose objectives are reducing system costs and enhancing system efficiency. We conclude that regulators should pay attention to the operating environment of DSA systems when determining which approaches to context learning to encourage

Security Provisioning in Cloud Environments using Dynamic Expiration Enabled Role based Access Control Model

In cloud environment the role based access control (RBAC) system model has come up with certain promising facilities for security communities. This system has established itself as highly robust, powerful and generalized framework for providing access control for security management. There are numerous practical applications and circumstances where the users might be prohibited to consider respective roles only at certain defined time periods. Additionally, these roles can be invoked only on after pre-defined time intervals which depend on the permission of certain action or event. In order to incarcerate this kind of dynamic aspects of a role, numerous models like temporal RBAC (TRBAC) was proposed, then while this approach could not deliver anything else except the constraints of role enabling. Here in this paper, we have proposed robust and an optimum scheme called Dynamic expiration enabled role based access control (DEERBAC) model which is efficient for expressing a broad range of temporal constraints. Specifically, in this approach we permit the expressions periodically as well as at certain defined time constraints on roles, user-role assignments as well as assignment of role-permission. According to DEERBAC model, in certain time duration the roles can be further restricted as a consequence of numerous activation constraints and highest possible active duration constraints. The dominant contributions of DEERBAC model can the extension and optimization in the existing TRBAC framework and its event and triggering expressions. The predominant uniqueness of this model is that this system inherits the expression of role hierarchies and Separation of Duty (SoD) constraints that specifies the fine-grained temporal semantics. The results obtained illustrates that the DEERBAC system provides optimum solution for efficient user-creation, role assignment and security management framework in cloud environment with higher user count and the simultaneous rolepermission,