The Behavioral Roots of Information Systems Security:Exploring Key Factors Related to Unethical IT Use

Unethical information technology (IT) use, related to activities such as hacking, software piracy, phishing, and spoofing, has become a major security concern for individuals, organizations, and society in terms of the threat to information systems (IS) security. While there is a growing body of work on this phenomenon, we notice several gaps, limitations, and inconsistencies in the literature. In order to further understand this complex phenomenon and reconcile past findings, we conduct an exploratory study to uncover the nomological network of key constructs salient to this phenomenon, and the nature of their interrelationships. Using a scenario-based study of young adult participants, and both linear and nonlinear analyses, we uncover key nuances of this phenomenon of unethical IT use. We find that unethical IT use is a complex phenomenon, often characterized by nonlinear and idiosyncratic relationships between the constructs that capture it. Overall, ethical beliefs held by the individuals, along with economic, social, and technological considerations are found to be relevant to this phenomenon. In terms of practical implications, these results suggest that multiple interventions at various levels may be required to combat this growing threat to IS security

Using 2D Hierarchical Heavy Hitters to Investigate Binary Relationships

This chapter presents VHHH: a visual data mining tool to compute and investigate hierarchical heavy hitters (HHHs) for two-dimensional data. VHHH computes the HHHs for a two-dimensional categorical dataset and a given threshold, and visualizes the HHHs in the three dimensional space. The chapter evaluates VHHH on synthetic and real world data, provides an interpretation alphabet, and identifies common visualization patterns of HHHs

An Ontological Framework for Decision Support

In the last few years, ontologies have been successfully exploited by Decision Support Systems (DSSs) to support some phases of the decisionmaking process. In this paper, we propose to employ an ontological representation for all the content both processed and produced by a DSS in answering requests. This semantic representation supports the DSS in the whole decisionmaking process, and it is capable of encoding (i) the request, (ii) the data relevant for it, and (iii) the conclusions/suggestions/decisions produced by the DSS. The advantages of using an ontology-based representation of the main data structure of a DSS are many: (i) it enables the integration of heterogeneous sources of data available in the web, and to be processed by the DSS, (ii) it allows to track, and to expose in a structured form to additional services (e.g., explanation or case reuse services), all the content processed and produced by the DSS for each request, and (iii) it enables to exploit logical reasoning for some of the inference steps of the DSS decision-making process. The proposed approach have been successfully implemented and exploited in a DSS for personalized environmental information, developed in the context of the PESCaDO EU project

Elbe DSS: A Planning Support System for Strategic River Basin Planning

The German part of the Elbe River and its basin are characterized by multiple problems and objectives that call for strategic management based on an integrated approach. In August 2002, the region suffered a catastrophic flood with loss of lives and damage amounting to over 9 billion Euro. During the summer months, because of low flows, shipping along the river is problematic, which considerably reduces the economic transport capacity of the river. Several areas along the river act as a habitat for rare plant and animal species and have been designated as nature reserves. The output of diffuse and point sources of pollution in the river basin must be controlled in order to comply with standards of the EU Water Framework Directive (EU 2000)

Intelligent Advisor Agents in Distributed Environments

The chapter presents a Distributed Expert System based on a multi-agent-architecture. The system is composed of a community of intelligent conversational agents playing the role of specialized advisors for the government of a virtual town, inspired to the SimCity game. The agents are capable to handle strategic decision under uncertainty conditions. They interact in natural language with their owners, obtain information on the current status of the town and give suggestions about the best strategies to apply in order to govern the town