Combination of AHP and TOPSIS methods for the ranking of information security controls to overcome its obstructions under fuzzy environment

The organizations utilizing the cloud computing services are required to select suitable Information Security Controls (ISCs) to maintain data security and privacy. Many organizations bought popular products or traditional tools to select ISCs. However, selecting the wrong information security control without keeping in view severity of the risk, budgetary constraints, measures cost, and implementation and mitigation time may lead to leakage of data and resultantly, organizations may lose their user’s information, face financial implications, even reputation of the organization may be damaged. Therefore, the organizations should evaluate each control based on certain criteria like implementation time, mitigation time, exploitation time, risk, budgetary constraints, and previous effectiveness of the control under review. In this article, the authors utilized the methodologies of the Multi Criteria Decision Making (MCDM), Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to help the cloud organizations in the prioritization and selection of the best information security control. Furthermore, a numerical example is also given, depicting the step by step utilization of the method in cloud organizations for the prioritization of the information security controls

Social-sanitary big data framework

The growing number of medical research on the web shows that the health and healthcare are increasingly digital. In order to ensure the safety of citizens, social cohesion, and economic competitiveness at a national level, the Information and Communication Technology (ICT) can facilitate knowledge and exchange of data through an analytical approach to problem solving, through continuous improvement of statistical managing of Big Data also in the healthcare field. The new technologies have become essential, thanks to the enormous possibilities that they can offer: we have witnessed over a very short period of time, that most of the human activities which were carried out manually have given space to much more efficient digital implementations. For instance, we can consider the serious problems that the vast documental archives have created in its management, and how centralized computer databases helped to solve most of these problems, speeding up and optimizing all research operations and data mining. This natural easiness of data exchange is still being expanded and facilitated by the development of computer networks, and in particular by the internet. Despite progress made in recent years, the quality of the data is still one of the critical aspects of statistical production in the social-sanitary field and is partly due to the lack of accurate data provided by the peripheral structures, where the measurements are still in course of automation. Another factor that adversely affects the quality of the information consists of the delay time between the occurrence of the underlying events and the recording of related data: these, in fact, sometimes they are not inserted immediately in information systems and are then retrieved at a later time. ICT offers possible solutions, improving the administration and helping to streamline procedures and reduce costs. Moreover, the problems of data reliability, the provision of appropriate classifications in survey forms and, more generally, the quality of data are attributable, directly or indirectly, to the degree of computerization in social-sanitary production. In fact, in the presence of a fully computerized detection system, the possibility of errors transcription, manipulation and interpretation of the required information will drastically reduce (due to the non-perfect correspondence between the classification adopted in models of detection and what is recovered in the official records), as well as the time-lag in some cases considerable, between data recording and the actual time/instant of reference; on the other hand, the detailing of the information collected could increase a result of a greater and more appropriate articulation of the detection patterns (certainly not feasible, beyond a given limit, in cases of manual detection) and the activation of an automatic check on the consistency of the data would be possible, not only ex-post, but also during the same stage in which information is entered. In reference to electronic health records, the Legislative Decree 179/2012 published in the Official Gazette of 11 November 2015 defines the set of health Big data and digital socio-sanitary documents generated from clinical present and past events: each one generates big data receiving a prescription, buying a medicine, requiring a health service, accessing to the emergency room, undergoing a diagnostic or laboratory examination, using social networks to communicate health conditions. Cross analysing this information, policy makers, hospitals and clinics could prevent the most common diseases and balance healthcare services according to the real needs of the population in a given territory. The application of these concepts to social-sanitary activities has opened a new and interesting line of research considered as a matter that unfolds on interoperability between the systems of public administration and the ICT. The crucial role of big data in healthcare is therefore to use the already considerable amount of existing information to avoid waste and to concentrate financial resources in sectors and medical specialties really needed by citizens

High Motor Cortex Excitability in Highly Hypnotizable Individuals: A Favourable Factor for Neuroplasticity?

Hypnotizability is a psychophysiological trait associated with morphofunctional brain peculiarities and with several cognitive, sensorimotor and cardiovascular correlates. Behavioral and EEG studies indicate stronger functional equivalence (FE) between motor imagery and action in the individuals with high hypnotizability scores (Highs). We hypothesized that stronger FE leading to greater proneness to ideomotor behavior could be due to greater cortical excitability of the motor cortex. The aim of the study was to evaluate the motor cortical excitability through measurements of the muscle potentials (MEPs) evoked in the left abductor pollicis brevis by transcranial magnetic stimulation (TMS) of the right motor cortex in 10 Highs, 10 medium (Mediums) and 10 low hypnotizable individuals (Lows) classified according to the Stanford Hypnotic Susceptibility Scale, form A (SHSS). They were studied in basal conditions (B) and during motor imagery (MI). Results showed significant, negative correlations (i) between hypnotizability and MEPs Resting Motor Threshold (RMT) in basal conditions, and (ii) between hypnotizability and both MEPs RMT and suprathreshold (I1mv) stimulation intensities during MI. ANOVA revealed significantly lower stimulation intensities in Highs than in Lows, with Mediums exhibiting intermediate values. Thus, the Highs’ greater cortical excitability could sustain their greater FE and proneness to ideomotor behavior. In cognitive neuroscience these findings are relevant to the physiological interpretation of the response to sensorimotor suggestions by participants in the ordinary state of consciousness. In the clinical field they can predict the efficacy of mental training based on motor imagery and, possibly, the degree of imagery-induced cortical plasticity

Visual perception of area and hypnotic susceptibility

The visual perception of area of geometrical figures was compared for subjects of high and low hypnotizability in experiments with direct comparison of two different geometrical figures. The Stanford Hypnotic Susceptibility Scale (Form C) was used to assess subjects' hypnotizability. No differences between 17 highly hypnotizable and 10 low hypnotizable subjects were found. Present results were also compared with those previously obtained for subjects of unknown hypnotizability. The model based on the Image Function Theory proposed earlier to explain the errors in area estimation committed by subjects of unknown hypnotizability was confirmed as a general rule