Bivariate attacks and confusion coefficients

We solve the problem of finding the success rate of an optimal side-channel attack targeting at once the first and the last round of a block cipher. We relate the results to the properties of the direct and inverse substitution boxes (when they are bijective), in terms of confusion coefficients

Community Policing and Intelligence-Led Policing: An Examination of Convergent or Discriminant Validity

Purpose Despite increased scholarly inquiry regarding intelligence-led policing (ILP) and popularity among law enforcement agencies around the globe, ambiguity remains regarding the conceptual foundation and appropriate measurement of ILP. Although most scholars agree that ILP is indeed a unique policing philosophy, there is less consensus regarding the relationship between ILP and the ever-present model of community-oriented policing (COP). Consequently, there is a clear need to study the empirical distinctions and overlaps in these policing philosophies as implemented by US law enforcement agencies. The paper aims to discuss these issues. Design/methodology/approach Data were gleaned from the 2007 LEMAS and 2009 NIJ Intelligence surveys. A total of 227 unique police agencies in the USA are included. A series of bivariate, exploratory factor analyses and structural models are used to determine discriminatory or convergent validity across COP and ILP constructs. Findings The goal was to answer the question: are these two policing philosophies are being implemented as separate and distinct strategies? Results of our exploratory and structural models indicate that COP and ILP loaded on unique latent constructs. This affirms the results of the bivariate correlations, and indicates that COP and ILP have discriminant measurement validity. In other words, COP and ILP are conceptually distinct, even when implemented in police departments across the USA. Implications of these findings and suggestions for future research are discussed. Originality/value This is the first study to empirically test the discriminant or convergent validity of COP and ILP

Cancellable Template Design for Privacy-Preserving EEG Biometric Authentication Systems

As a promising candidate to complement traditional biometric modalities, brain biometrics using electroencephalography (EEG) data has received a widespread attention in recent years. However, compared with existing biometrics such as fingerprints and face recognition, research on EEG biometrics is still in its infant stage. Most of the studies focus on either designing signal elicitation protocols from the perspective of neuroscience or developing feature extraction and classification algorithms from the viewpoint of machine learning. These studies have laid the ground for the feasibility of using EEG as a biometric authentication modality, but they have also raised security and privacy concerns as EEG data contains sensitive information. Existing research has used hash functions and cryptographic schemes to protect EEG data, but they do not provide functions for revoking compromised templates as in cancellable template design. This paper proposes the first cancellable EEG template design for privacy-preserving EEG-based authentication systems, which can protect raw EEG signals containing sensitive privacy information (e.g., identity, health and cognitive status). A novel cancellable EEG template is developed based on EEG graph features and a non-invertible transform. The proposed transformation provides cancellable templates, while taking advantage of EEG elicitation protocol fusion to enhance biometric performance. The proposed authentication system offers equivalent authentication performance (8.58\% EER on a public database) as in the non-transformed domain, while protecting raw EEG data. Furthermore, we analyze the system's capacity for resisting multiple attacks, and discuss some overlooked but critical issues and possible pitfalls involving hill-climbing attacks, second attacks, and classification-based authentication systems

Child Externalising and Internalising Behaviour in the First Year of School: The Role of Parenting in a Low SES Population

Successful transition and adjustment to school life is critical for a child's future success. To ease this transition a child needs to arrive equipped with the necessary skills for school. The extent of a child’s behavioural problems is one indicator of his or her level of adjustment and school readiness. A factor which is consistently associated with such behaviours is parenting practices. This study examined the role of maternal parenting behaviours on externalising and internalising behaviours displayed by children in their first year of schooling. As children living in low socioeconomic status (SES) families are at risk of both adverse parenting behaviours and childhood behavioural difficulties, the study focuses on a low SES cohort. Mothers (n = 197) reported parenting behaviours using the Parenting Styles and Dimensions Questionnaire (PSDQ; Robinson, Mandelco, Olsen, & Hart, 2001). Teachers (n = 21) rated children on how frequently they engaged in fifteen behaviours. These behaviours were subjected to an exploratory factor analysis, eliciting two externalising behaviour factors (aggressive and defiant; hyperactive and inattentive) and one internalising behaviour factor. Bivariate analyses revealed that authoritarian parenting is associated with aggressive and defiant behaviours and that permissive parenting and maternal education is associated with hyperactive and inattentive behaviours. Only the latter result remains significant in the multivariate analysis. Finally, no relationships were found between parenting practices and child internalising behaviours. Parenting behaviours explained a small proportion of the variance in child externalising behaviours, highlighting the need to educate parents in effective parenting practices.

SOPHIA

The Iraqi Insurgency (2003–2011) has commonly been characterized as demonstrating the tendency for violence to cluster and diffuse at the local level. Recent research has demonstrated that insurgent attacks in Iraq cluster in time and space in a manner similar to that observed for the spread of a disease. The current study employs a variety of approaches common to the scientific study of criminal activities to advance our understanding of the correlates of observed patterns of the incidence and contagion of insurgent attacks. We hypothesize that the precise patterns will vary from one place to another, but that more attacks will occur in areas that are heavily populated, where coalition forces are active, and along road networks. To test these hypotheses, we use a fishnet to build a geographical model of Baghdad that disaggregates the city into more than 3000 grid cell locations. A number of logistic regression models with spatial and temporal lags are employed to explore patterns of local escalation and diffusion. These models demonstrate the validity of arguments under each of three models but suggest, overall, that risk heterogeneity arguments provide the most compelling and consistent account of the location of insurgency. In particular, the results demonstrate that violence is most likely at locations with greater population levels, higher density of roads, and military garrisons

Probabilistic Models for Anomaly Detection Based on Usage of Network Traffic

Recent advances in intrusions and attacks reflect vulnerabilities in computer networks. Innovative methods and tools can help attack defenses, prevent attack propagations, detect and respond to such attacks in a timely manner. Intrusion detection and prevention systems search for unauthorized use, recognize anomalous behavior, and prevent attempts to deny services.  These systems gather and analyze information from the network, identify possible breaches of the security profile, as well as misuses. We have been experimenting with methods for introducing important concepts related to intrusion detection and improving undergraduate research experiences and education. To achieve this goal, probabilistic models are introduced to students in computer, information system and network security courses. This article presents a set of probabilistic methods and statistical models for network traffic anomaly detection. It also describes some prospects and how models have ripened from theories to big data analysis applications. Keywords: Intrusion, conditional probability, network system, regression, data analysi

A sectoral analysis of Barbados’ GDP business cycle

This paper has two main objectives. Firstly, to establish and characterise a reference cycle (based on real output) for Barbados over the quarterly period 1974-2003 using the Bry and Boschan algorithm. Secondly, to link this aggregate output cycle to the cycles of the individual sectors that comprises real output. The overriding conclusions are that the cycles of tourism and wholesale and retail closely resembles that of the aggregate business cycle, while the non-sugar agriculture and fishing cycle is acyclical.Barbados; Gross Domestic Product, Business Cycle

The bank lending channel reconsidered

It has been widely accepted that constraints on the wholesale funding of bank balance sheets amplify the transmission of monetary policy through what is called the ‘bank lending channel’. We show that the effect of such bank balance sheet constraints on monetary transmission is in fact theoretically ambiguous, with the prior expectation, based on standard theoretical models of household and corporate portfolios, that the bank lending channel attenuates monetary policy transmission. We examine macroeconomic data for the G8 countries and find no evidence that banking sector deposits respond negatively and more than lending to tightening of monetary policy, as the accepted view of the bank lending channel requires. The overall picture is mixed, but these data generally suggest that deposits fluctuate procyclically and somewhat less over the business cycle than bank lending, and that total bank deposits, unlike bank lending, show little direct response to changes in interest rates. This suggests it is very unlikely that the bank lending channel amplifies monetary policy. Our paper has thus corrected a misunderstanding about the role of banks in monetary policy transmission that has persisted in the literature for some two decades.credit channel; monetary transmission; bank financing constraints