Browsing by Author "Clark, J. A."
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Item Open Access A deployment value model for intrusion detection sensors(Springer-verlag, 2010-02-18T00:00:00Z) Shaikh, S. A.; Chivers, H.; Nobles, P.; Clark, J. A.; Chen, H.The value of an intrusion detection sensor is often associated with its data collection and analysis features. Experience tells us such sensors fall under a range of different types and are diverse in their operational characteristics. There is a need to examine some of these characteristics to appreciate the value they add to intrusion detection deployments. This paper presents a model to determine the value derived from deploying sensors, which serves to be useful to analyse and compare intrusion detection deployments.Item Open Access Integrated models of livestock systems for climate change studies. 1. Grazing systems.(Blackwell Publishing Ltd, 2001-01-01T00:00:00Z) Parsons, David J.; Armstrong, A. C.; Turnpenny, J. R.; Matthews, A. M.; Cooper, K. C.; Clark, J. A.The potential impact of climate change by the year 2050 on British grazing livestock systems is assessed through the use of simulation models of farming systems. The submodels, consisting of grass production, livestock feeding, livestock thermal balance, the thermal balance of naturally ventilated buildings and a stochastic weather generator, are described. These are integrated to form system models for sheep, beef calves and dairy cows. They are applied to scenarios representing eastern (dry) lowlands, western (wet) lowlands and uplands. The results show that such systems should be able to adapt to the expected climatic changes. There is likely to be a small increase in grass production, possibly allowing an increase in total productivity in some cases.Item Open Access Integrated models of livestock systems for climate change studies. 2. Intensive systems.(Blackwell Publishing Ltd, 2001-01-01T00:00:00Z) Turnpenny, J. R.; Parsons, David J.; Armstrong, A. C.; Clark, J. A.; Cooper, K. C.; Matthews, A. M.The potential impact of climate change by the year 2050 on intensive livestock systems in Britain is assessed through the use of simulation models of farming systems. The submodels comprise livestock feeding, livestock thermal balance and the thermal balance of controlled environment buildings and a stochastic weather generator. These are integrated to form system models for growing pigs and broiler chickens. They are applied to scenarios typical of SE England, which is the warmest region of the country and represents the worst case. For both species the frequency of severe heat stress is substantially increased, with a consequent risk of mortality. To offset this, it would be necessary to reduce stocking densities considerably, or to invest in improved ventilation or cooling equipment. Other effects on production are likely to be small.Item Open Access Knowing who to watch: accumulating evidence of subtle attacks(2010-09-23T08:46:19Z) Chivers, H.; Clark, J. A.; Nobles, P.; Shaikh, S. A.; Chen, H.Insider attacks are often subtle and slow, or preceded by behavioral indicators such as organizational rule-breaking which provide the potential for early warning of malicious intent; both these cases pose the problem of identifying attacks from limited evidence contained within a large volume of event data collected from multiple sources over a long period. This paper proposes a scalable solution to this problem by maintaining long-term estimates that individuals or nodes are attackers, rather than retaining event data for post-facto analysis. These estimates are then used as triggers for more detailed investigation. We identify essential attributes of event data, allowing the use of a wide range of indicators, and show how to apply Bayesian statistics to maintain incremental estimates without global updating. The paper provides a theoretical account of the process, a worked example, and a discussion of its practical implications. The work includes examples that identify subtle attack behaviour in subverted network nodes, but the process is not network-specific and is capable of integrating evidence from other sources, such as behavioral indicators, document access logs and financial records, in addition to events identified by network monitoring.