Big Data Handling Approach for Unauthorized Cloud Computing Access

Nowadays, cloud computing is one of the important and rapidly growing services; its capabilities and applications have been extended to various areas of life. Cloud computing systems face many security issues, such as scalability, integrity, confidentiality, unauthorized access, etc. An illegitimate intruder may gain access to a sensitive cloud computing system and use the data for inappropriate purposes, which may lead to losses in business or system damage. This paper proposes a hybrid unauthorized data handling (HUDH) scheme for big data in cloud computing. The HUDH scheme aims to restrict illegitimate users from accessing the cloud and to provide data security provisions. The proposed HUDH consists of three steps: data encryption, data access, and intrusion detection. The HUDH scheme involves three algorithms: advanced encryption standards (AES) for encryption, attribute-based access control (ABAC) for data access control, and hybrid intrusion detection (HID) for unauthorized access detection. The proposed scheme is implemented using the Python and Java languages. The testing results demonstrated that the HUDH scheme can delegate computation overhead to powerful cloud servers. User confidentiality, access privilege, and user secret key accountability can be attained with more than 97% accuracy.

HERMES – a GUI-based software tool for pre-processing of X-ray absorption spectroscopy data from laboratory Rowland circle spectrometers

HERMES, a graphical user interface software tool, is presented, for pre-processing X-ray absorption spectroscopy (XAS) data from laboratory Rowland circle spectrometers, to meet the data handling needs of a growing community of practice. HERMES enables laboratory XAS data to be displayed for quality assessment, merging of data sets, polynomial fitting of smoothly varying data, and correction of data to the true energy scale and for dead-time and leakage effects. The software is written in Java 15 programming language, and runs on major computer operating systems, with graphics implementation using the JFreeChart toolkit. HERMES is freely available and distributed under an open source licence.

Usage Experience and Capabilities of the VEGA-Science System

Currently, when satellite data volumes grow rapidly and exceed petabyte values and their quality provides reliable analysis of long-term time series, traditional data handling methods assuming local storage and processing may be impossible to implement for small or distributed research teams. Thus, new methods based on modern web technologies providing access to very large distributed data archives are gaining increasing importance. Furthermore, these new data handling solutions should provide not just access but also analysis and processing features, similar to desktop solutions. This paper describes the VEGA-Science web GIS—an open-access novel tool for satellite data processing and analysis. The overview of its architecture and basic technical components is given, but most attention is paid to examples of actual system application for various applied and research tasks. In addition, an overview of projects using the system is given to illustrate its versatility and further development directions are considered.

Comparison of Acquired Activated Protein C Resistance, Using the CAT and ST-Genesia® Analysers and Three Thrombin Generation Methods, in APS and SLE Patients

Background: Acquired activated protein C resistance (APCr) has been identified in antiphospholipid syndrome (APS) and systemic lupus erythematosus (SLE). Objective: To assess agreement between the ST-Genesia® and CAT analysers in identifying APCr prevalence in APS/SLE patients, using three thrombin generation (TG) methods. Methods: APCr was assessed with the ST-Genesia using STG-ThromboScreen and with the CAT using recombinant human activated protein C and Protac® in 105 APS, 53 SLE patients and 36 thrombotic controls. Agreement was expressed in % and by Cohen's kappa coefficient. Results: APCr values were consistently lower with the ST-Genesia® compared to the CAT, using either method, in both APS and SLE patients. Agreement between the two analysers in identifying APS and SLE patients with APCr was poor (≤65.9%, ≤0.20) or fair (≤68.5%, ≥0.29), regardless of TG method, respectively; no agreement was observed in thrombotic controls. APCr with both the ST Genesia and the CAT using Protac®, but not the CAT using rhAPC, was significantly greater in triple antiphospholipid antibody (aPL) APS patients compared to double/single aPL patients (p < 0.04) and in thrombotic SLE patients compared to non-thrombotic SLE patients (p < 0.05). Notably, the ST-Genesia®, unlike the CAT, with either method, identified significantly greater APCr in pregnancy morbidity (median, confidence intervals; 36.9%, 21.9–49.0%) compared to thrombotic (45.7%, 39.6–55.5%) APS patients (p = 0.03). Conclusion: Despite the broadly similar methodology used by CAT and ST-Genesia®, agreement in APCr was poor/fair, with results not being interchangeable. This may reflect differences in the TG method, use of different reagents, and analyser data handling.

Occupational Hearing Loss for Platinum Miners in South Africa: A Case Study of Data Sharing Practices and Ethical Challenges in the Mining Industry

Background: The relevant legislation ensures confidentiality and has paved the way for data handling and sharing. However, the industry remains uncertain regarding big data handling and sharing practices for improved healthcare delivery and medical research. Methods: A semi-qualitative cross-sectional study was used which entailed analysing miners’ personal health records from 2014 to 2018. Data were accessed from the audiometry medical surveillance database (n = 480), the hearing screening database (n = 24,321), and the occupational hygiene database (n = 15,769). Ethical principles were applied to demonstrate big data protection and sharing. Results: Some audiometry screening and occupational hygiene records were incomplete and/or inaccurate (N = 4675). The database containing medical disease and treatment records could not be accessed. Ethical challenges included a lack of clarity regarding permission rights when sharing big data, and no policy governing the divulgence of miners’ personal and medical records for research. Conclusion: This case study illustrates how research can be effectively, although not maliciously, obstructed by the strict protection of employee medical data. Clearly communicated company policies should be developed for the sharing of workers’ records in the mining industry to improve HCPs.