Defacement Detection with Passive Adversaries

A novel approach to defacement detection is proposed in this paper, addressing explicitly the possible presence of a passive adversary. Defacement detection is an important security measure for Web Sites and Applications, aimed at avoiding unwanted modifications that would result in significant reputational damage. As in many other anomaly detection contexts, the algorithm used to identify possible defacements is obtained via an Adversarial Machine Learning process. We consider an exploratory setting, where the adversary can observe the detector’s alarm-generating behaviour, with the purpose of devising and injecting defacements that will pass undetected. It is then necessary to make to learning process unpredictable, so that the adversary will be unable to replicate it and predict the classifier’s behaviour. We achieve this goal by introducing a secret key—a key that our adversary does not know. The key will influence the learning process in a number of different ways, that are precisely defined in this paper. This includes the subset of examples and features that are actually used, the time of learning and testing, as well as the learning algorithm’s hyper-parameters. This learning methodology is successfully applied in this context, by using the system with both real and artificially modified Web sites. A year-long experimentation is also described, referred to the monitoring of the new Web Site of a major manufacturing company

Epidemiology and outcome of candidemia in internal medicine wards: A regional study in Italy

Background More than one-third of candidemia episodes occur in Internal Medicine Wards (IMWs) but only few studies have focused on this setting and specific data about epidemiology, clinical characteristics and risk factors for mortality are scant. Objective To describe epidemiology and to assess risk factors for in-hospital mortality among patients with candidemia in IMWs. Methods Multicenter retrospective cohort study on patients with candidemia cared for in IMWs of an Italian region (Emilia Romagna) from January 2012 to December 2013. Non survivors were compared with survivors; variables with p\uc2\ua0\ue2\u89\ua4\uc2\ua00.1 at univariate analysis were entered into a multivariate Cox regression model. Results 232 patients were included. Overall candidemia incidence was 2.2 cases/1000 admissions. Candida albicans accounted for 59% of cases. Antifungal treatment was started \uc2\ua072\uc2\ua0h from blood cultures in 47%, 27% and 12% of patients, respectively; 13.8% of patients received no antifungal treatment. In-hospital mortality was 40%. At multivariate analysis, chronic-obstructive-pulmonary-disease (HR 2.72, 95%CI 1.66\ue2\u80\u934.45, p\uc2\ua0<\uc2\ua00.001) and isolation of C. tropicalis (HR 2.18, 95%CI 1.19\ue2\u80\u933.99, p\uc2\ua0=\uc2\ua00.01) were the independent risk factors for in-hospital mortality; central-venous-catheter removal (HR 0.59, 95%CI 0.36\ue2\u80\u930.96, p\uc2\ua0=\uc2\ua00.03) and adequate and timely (within 72\uc2\ua0h from blood drawing) empirical therapy (HR 0.42, 95%CI 0.25\ue2\u80\u930.69, p\uc2\ua0=\uc2\ua00.001) were protective factors. Conclusions The present study conducted in a relatively large geographic area confirms high incidence and mortality of candidemia in IMWs, with a worrisome rate of inappropriateness in patient management. Specific interventions aimed to increase awareness of IMWs about candidemia are needed

Testicular torsion during the COVID-19 pandemic: Results of a multicenter study in northern Italy

The literature reported an increased avoidance of the Emergency Department (ED) during COrona VIrus Disease 19 (COVID-19) pandemic, causing a subsequent increase of morbidity and mortality for acute conditions. Testicular torsion is a surgical emergency, which can lead to the loss of the affected testicle if a delayed treatment occurs. As testicular loss is time-related, outcome was hypothesized to be negatively affected by the pandemic