Biblio

The adherence of employees towards Information Security Policy (ISP) established in the organization is crucial in reducing information security risks. Some scholars have suggested that employees' compliance to ISP could be influenced by Information Security Culture (ISC) cultivated in the organization. Several studies on the impact of ISC towards ISP compliance have proposed different dimensions and factors associated to ISC with substantial differences in each finding. This paper is discussing an enhanced conceptual framework of ISP compliance behavior by addressing ISC as a multidimensional concept which consist of seven comprehensive dimensions. These new proposed ISC dimensions developed using all the key factors of ISC in literature and were aligned with the widely accepted concept of organizational culture and ISC. The framework also integrated with the most significant behavioral theory in this domain of study, which is Theory of Planned Behavior to provide more deep understanding and richer findings of the compliance behavior. This framework is expected to give more accurate findings on the relationships between ISC and ISP compliance behavior.

Continuously improving security on an information system requires unique combination of human aspect, policies, and technology. This acts as leverage for designing an access control management approach which avails only relevant parts of a system according to an end-users' scope of work. This paper introduces a framework for information security fundamentals at organizational and theoretical levels, to identify critical success factors that are vital in assessing an organization's security maturity through a model referred to as “information security digital divide maturity framework”. The foregoing is based on a developed conceptual framework for information security digital divide. The framework strives to divide system end-users into “specific information haves and have-nots”. It intends to assist organizations to continually evaluate and improve on their security governance, standards, and policies which permit access on the basis of each end-user's work scope. The framework was tested through two surveys targeting 90 end-users and 35 security experts.

The output of 3D volume segmentation is crucial to a wide range of endeavors. Producing accurate segmentations often proves to be both inefficient and challenging, in part due to lack of imaging data quality (contrast and resolution), and because of ambiguity in the data that can only be resolved with higher-level knowledge of the structure and the context wherein it resides. Automatic and semi-automatic approaches are improving, but in many cases still fail or require substantial manual clean-up or intervention. Expert manual segmentation and review is therefore still the gold standard for many applications. Unfortunately, existing tools (both custom-made and commercial) are often designed based on the underlying algorithm, not the best method for expressing higher-level intention. Our goal is to analyze manual (or semi-automatic) segmentation to gain a better understanding of both low-level (perceptual tasks and actions) and high-level decision making. This can be used to produce segmentation tools that are more accurate, efficient, and easier to use. Questioning or observation alone is insufficient to capture this information, so we utilize a hybrid capture protocol that blends observation, surveys, and eye tracking. We then developed, and validated, data coding schemes capable of discerning low-level actions and overall task structures.