The birds of the Bush Heritage, Cravens Peak Reserve

Bird communities were studied in two subregional areas of Cravens Peak, the Toko Plains and the Simpson-Strzelecki Dunefields, using the point counts method. A total of 42 2ha 20 minute surveys, 46 five-hundred metre radius area surveys and 170 5km drive through area surveys were conducted and observations made. Bird species were identified, counted and recorded. The data were compared in the two subregions and, as a whole, considering species groups according to land system on which the ecosystem occurs, the specific ecosystem and according to their general feeding habits (insectivore, omnivore, frugivore, granivore, nectarivore and carnivore). Species richness and species relative abundance were compared using Simpson’s Diversity Index and the data revealed that species are distributed largely on the basis of habitat. In general, areas with a greater number of vegetation strata recorded greater species diversity. Overall, the Tall Open Acacia georginae Shrubland on alluvial floodplains has a greater diversity of birds in a 2ha area (0.87, Simpson’s Index of Diversity 1-D) compared to the other survey sites

A solution for secure use of Kibana and Elasticsearch in multi-user environment

Monitoring is indispensable to check status, activities, or resource usage of IT services. A combination of Kibana and Elasticsearch is used for monitoring in many places such as KEK, CC-IN2P3, CERN, and also non-HEP communities. Kibana provides a web interface for rich visualization, and Elasticsearch is a scalable distributed search engine. However, these tools do not support authentication and authorization features by default. In the case of single Kibana and Elasticsearch services shared among many users, any user who can access Kibana can retrieve other's information from Elasticsearch. In multi-user environment, in order to protect own data from others or share part of data among a group, fine-grained access control is necessary. The CERN cloud service group had provided cloud utilization dashboard to each user by Elasticsearch and Kibana. They had deployed a homemade Elasticsearch plugin to restrict data access based on a user authenticated by the CERN Single Sign On system. It enabled each user to have a separated Kibana dashboard for cloud usage, and the user could not access to other's one. Based on the solution, we propose an alternative one which enables user/group based Elasticsearch access control and Kibana objects separation. It is more flexible and can be applied to not only the cloud service but also the other various situations. We confirmed our solution works fine in CC-IN2P3. Moreover, a pre-production platform for CC-IN2P3 has been under construction. We will describe our solution for the secure use of Kibana and Elasticsearch including integration of Kerberos authentication, development of a Kibana plugin which allows Kibana objects to be separated based on user/group, and contribution to Search Guard which is an Elasticsearch plugin enabling user/group based access control. We will also describe the effect on performance from using Search Guard.Comment: International Symposium on Grids and Clouds 2017 (ISGC 2017

Privacy-Preserving Genetic Relatedness Test

An increasing number of individuals are turning to Direct-To-Consumer (DTC) genetic testing to learn about their predisposition to diseases, traits, and/or ancestry. DTC companies like 23andme and Ancestry.com have started to offer popular and affordable ancestry and genealogy tests, with services allowing users to find unknown relatives and long-distant cousins. Naturally, access and possible dissemination of genetic data prompts serious privacy concerns, thus motivating the need to design efficient primitives supporting private genetic tests. In this paper, we present an effective protocol for privacy-preserving genetic relatedness test (PPGRT), enabling a cloud server to run relatedness tests on input an encrypted genetic database and a test facility's encrypted genetic sample. We reduce the test to a data matching problem and perform it, privately, using searchable encryption. Finally, a performance evaluation of hamming distance based PP-GRT attests to the practicality of our proposals.Comment: A preliminary version of this paper appears in the Proceedings of the 3rd International Workshop on Genome Privacy and Security (GenoPri'16

A systematic review of people with autism spectrum disorder and the Criminal Justice System

This paper provides a systemic review of the available literature on people with autism spectrum disorder (ASD) in the criminal justice system (CJS). The review considers two main types of study: those that examined the prevalence of people with ASD in the CJS and those that examined the prevalence of offending in populations with ASD. In addition, types of offences in people with ASD, co-morbid psychiatric diagnoses, and characteristics of people with ASD who commit offences (including predisposing factors) are considered. A combination of search terms was used in a variety of databases in order to find all of the available literature on this topic, and research studies were included based on specified inclusion and exclusion criteria. It was found that whilst there is an emerging literature base on this topic, there are a wide variety of methodologies used, making direct comparison difficult. Nevertheless it can be concluded so far that people with ASD do not seem to be disproportionately over-represented in the CJS, though they commit a range of crimes and seem to have a number of predisposing features. There is poor evidence of the presence of comorbid psychiatric diagnoses (except in mental health settings) amongst offenders with ASD, and little evidence of the oft-asserted over-representation of certain kinds of crimes. It is recommended that further research of good quality is required in this area, rather than studies that examine populations that are not representative of all those with ASD

A practical and secure multi-keyword search method over encrypted cloud data

Cloud computing technologies become more and more popular every year, as many organizations tend to outsource their data utilizing robust and fast services of clouds while lowering the cost of hardware ownership. Although its benefits are welcomed, privacy is still a remaining concern that needs to be addressed. We propose an efficient privacy-preserving search method over encrypted cloud data that utilizes minhash functions. Most of the work in literature can only support a single feature search in queries which reduces the effectiveness. One of the main advantages of our proposed method is the capability of multi-keyword search in a single query. The proposed method is proved to satisfy adaptive semantic security definition. We also combine an effective ranking capability that is based on term frequency-inverse document frequency (tf-idf) values of keyword document pairs. Our analysis demonstrates that the proposed scheme is proved to be privacy-preserving, efficient and effective