De-perimeterisation as a cycle: tearing down and rebuilding security perimeters

If an organisation wants to secure its IT assets, where should the security mechanisms be placed? The traditional view is the hard-shell model, where an organisation secures all its assets using a fixed security border: What is inside the security perimeter is more or less trusted, what is outside is not. Due to changes in technologies, business processes and their legal environments this approach is not adequate anymore.\ud This paper examines this process, which was coined de-perimeterisation by the Jericho Forum.\ud In this paper we analyse and define the concepts of perimeter and de-perimeterisation, and show that there is a long term trend in which de-perimeterisation is iteratively accelerated and decelerated. In times of accelerated de-perimeterisation, technical and organisational changes take place by which connectivity between organisations and their environment scales up significantly. In times of deceleration, technical and organisational security measures are taken to decrease the security risks that come with de-perimeterisation, a movement that we call re-perimeterisation. We identify the technical and organisational mechanisms that facilitate de-perimeterisation and re-perimeterisation, and discuss the forces that cause organisations to alternate between these two movements

The onus on us? Stage one in developing an i-Trust model for our users.

This article describes a Joint Information Systems Committee (JISC)-funded project, conducted by a cross-disciplinary team, examining trust in information resources in the web environment employing a literature review and online Delphi study with follow-up community consultation. The project aimed to try to explain how users assess or assert trust in their use of resources in the web environment; to examine how perceptions of trust influence the behavior of information users; and to consider whether ways of asserting trust in information resources could assist the development of information literacy. A trust model was developed from the analysis of the literature and discussed in the consultation. Elements comprising the i-Trust model include external factors, internal factors and user's cognitive state. This article gives a brief overview of the JISC funded project which has now produced the i-Trust model (Pickard et. al. 2010) and focuses on issues of particular relevance for information providers and practitioners

Generalized Costs of Travel by Solo and Pooled Ridesourcing vs. Privately Owned Vehicles, and Policy Implications

The emergence of “3 Revolutions” in transportation (automation, electrification and shared mobility) presents a range of questions regarding how consumers will travel in the future, and under what conditions there may be rapid adoption of various services. These include individual on-demand taxi-style services, shared mobility in pooled services, and use of public transit, all with or without drivers. There is now enough data and estimates on the costs of these service combinations, and in some cases ridership data, to consider how consumers are making choices and could do so in the future as things evolve. This project involved: (a) reviewing existing literature and data on consumer mode and vehicle choice; (b) developing new “generalized cost” estimates that combine monetary and non-monetary (e.g., hedonic) components of travel choice, notably incorporating value of time; and (c) conducting a comparison of monetary and generalized trip cost for a range of trip types across travel options in the near term (2020) and longer term (2030-35). Three main travel options were considered: privately owned vehicles, ridesourced solo trips, and ridesourced pooled trips. Consideration of internal combustion vs. battery electric and, in the longer term, automated technology was also core to the analysis. The trips considered include urban and suburban types in the San Francisco metro area, using actual trip characteristics. The results suggest that in the near-term, solo ridesourcing is likely to be perceived as significantly more expensive (in terms of monetary and time costs) than pooled ridesourcing or solo private vehicle trips except for those with a very high value of time. Solo ridesourcing does better in dense, slow, urban trips than in faster suburban trips. In the longer term, with automated driverless vehicles, solo ridesourcing could become the cheapest mode for many travelers in a range of situations. This report includes an initial consideration of the implications of these policies for affecting travel choices, presumably to push choices toward pooled ridesourcing as a sustainable option. VMT-based pricing, pricing that could be adjusted with vehicle occupancy, and parking-related approaches are described. A large price signal might be needed to shift travel, given some of the differences in generalized cost found in this analysis

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page