Conceptualizing human resilience in the face of the global epidemiology of cyber attacks

Computer security is a complex global phenomenon where different populations interact, and the infection of one person creates risk for another. Given the dynamics and scope of cyber campaigns, studies of local resilience without reference to global populations are inadequate. In this paper we describe a set of minimal requirements for implementing a global epidemiological infrastructure to understand and respond to large-scale computer security outbreaks. We enumerate the relevant dimensions, the applicable measurement tools, and define a systematic approach to evaluate cyber security resilience. From the experience in conceptualizing and designing a cross-national coordinated phishing resilience evaluation we describe the cultural, logistic, and regulatory challenges to this proposed public health approach to global computer assault resilience. We conclude that mechanisms for systematic evaluations of global attacks and the resilience against those attacks exist. Coordinated global science is needed to address organised global ecrime

Policy Design for Controlling Set-Point Temperature of ACs in Shared Spaces of Buildings

Air conditioning systems are responsible for the major percentage of energy consumption in buildings. Shared spaces constitute considerable office space area, in which most office employees perform their meetings and daily tasks, and therefore the ACs in these areas have significant impact on the energy usage of the entire office building. The cost of this energy consumption, however, is not paid by the shared space users, and the AC's temperature set-point is not determined based on the users' preferences. This latter factor is compounded by the fact that different people may have different choices of temperature set-points and sensitivities to change of temperature. Therefore, it is a challenging task to design an office policy to decide on a particular set-point based on such a diverse preference set. As a result, users are not aware of the energy consumption in shared spaces, which may potentially increase the energy wastage and related cost of office buildings. In this context, this paper proposes an energy policy for an office shared space by exploiting an established temperature control mechanism. In particular, we choose meeting rooms in an office building as the test case and design a policy according to which each user of the room can give a preference on the temperature set-point and is paid for felt discomfort if the set-point is not fixed according to the given preference. On the other hand, users who enjoy the thermal comfort compensate the other users of the room. Thus, the policy enables the users to be cognizant and responsible for the payment on the energy consumption of the office space they are sharing, and at the same time ensures that the users are satisfied either via thermal comfort or through incentives. The policy is also shown to be beneficial for building management. Through experiment based case studies, we show the effectiveness of the proposed policy.Comment: Journal paper accepted in Energy & Buildings (Elsevier

Geographical veracity of indicators from mobile phone data : a study of call detail records data in France

PhD ThesisThe study of mobile phone data opens opportunities in many research domains and for many applications. One point of critique is that, within current analyses, mobile phone users are considered uniform and interchangeable. To counter this social atom problem, good research practice demands an increasing contextualization of research results, for example by confrontation with auxiliary datasets or geographical knowledge. The latter forms the starting point of this thesis. The main argument is that there exists a spatial knowledge gap when it comes to the use of indicators derived from mobile phone data. The presented studies assess the geographical veracity of indicators derived from Call Detail Record (CDR) data and the underlying methods used. Based on a CDR dataset of almost 18.5 million users in France captured during a 154-day period in 2007, they show how mobile phone indicators can be constructed for all individual users using big data technologies. Investigation then is on the performance, sensitivity to user choices, and error estimations of home detection methods, which form a primordial step for the aggregation of users in space. Next, a spatial analysis of the popular Mobility Entropy (ME) indicator is performed, revealing its bias to cell tower density, for which a correction is then proposed. Ultimately, the relations between mobile phone indicators, indicators from other data sources and city definitions in France are explored. The main contribution of the thesis is that it reveals multiple limits of the common practices, results, and interpretations that govern mobile phone data research. The presented studies challenge the veracity of mobile phone indicators in different, predominantly geographical, ways and open up discussion on what should be done to improve trustworthiness

Mobile phone indicators and their relation to the socioeconomic organisation of cities

Thanks to the use of geolocated big data in computational social science research, the spatial and temporal heterogeneity of human activities are increasingly being revealed. Paired with smaller and more traditional data, this opens new ways of understanding how people act and move, and how these movements crystallise into the structural patterns observed by censuses. In this article we explore the convergence of mobile phone data with more classical socioeconomic data from census in French cities. We extract mobile phone indicators from six months worth of Call Detail Records (CDR) data, while census and administrative data are used to characterize the socioeconomic organisation of French cities. We address various definitions of cities and investigate how they impact the relation between mobile phone indicators, such as the number of calls or the entropy of visited cell towers, and measures of economic organisation based on census data, such as the level of deprivation, inequality and segregation. Our findings show that some mobile phone indicators relate significantly with different socioeconomic organisation of cities. However, we show that found relations are sensitive to the way cities are defined and delineated. In several cases, differing city definitions delineations can change the significance or even the signs of found correlations. In general, cities delineated in a restricted way (central cores only) exhibit traces of human activity which are less related to their socioeconomic organisation than cities delineated as metropolitan areas and dispersed urban regions.Comment: 19 pages, 9 figures, 2 table

An Automated Mobile Game-based Screening Tool for Patients with Alcohol Dependence

Traditional methods for screening and diagnosis of alcohol dependence are typically administered by trained clinicians in medical settings and often rely on interview responses. These self-reports can be unintentionally or deliberately false, and misleading answers can, in turn, lead to inaccurate assessment and diagnosis. In this study, we examine the use of user-game interaction patterns on mobile games to develop an automated diagnostic and screening tool for alcohol-dependent patients. Our approach relies on the capture of interaction patterns during gameplay, while potential patients engage with popular mobile games on smartphones. The captured signals include gameplay performance, touch gestures, and device motion, with the intention of identifying patients with alcohol dependence. We evaluate the classification performance of various supervised learning algorithms on data collected from 40 patients and 40 age-matched healthy adults. The results show that patients with alcohol dependence can be automatically identified accurately using the ensemble of touch, device motion, and gameplay performance features on 3-minute samples (accuracy=0.95, sensitivity=0.95, and specificity=0.95). The present findings provide strong evidence suggesting the potential use of user-game interaction metrics on existing mobile games as discriminant features for developing an implicit measure to identify alcohol dependence conditions. In addition to supporting healthcare professionals in clinical decision-making, the game-based self-screening method could be used as a novel strategy to promote alcohol dependence screening, especially outside of clinical settings