"Scientific research" Almanac

More titles

• 

  INFORMATION SECURITY OF HOSPITALS IN BULGARIA

  The relevance of this study is determined by the increasing requirements of and threats to the information security of healthcare facilities. The aim of the study is to investigate the state of information security of hospitals in Bulgaria and to define the concept of the model for information security. The following tasks are solved: studying the ... The relevance of this study is determined by the increasing requirements of and threats to the information security of healthcare facilities. The aim of the study is to investigate the state of information security of hospitals in Bulgaria and to define the concept of the model for information security. The following tasks are solved: studying the state of information security of hospitals in Bulgaria and opportunities for improvements; highlighting the good practices; analysing the capability of new technologies. On this basis, a concept for an information security model is developed, taking into account the features of Bulgarian hospitals. The research thesis, which is defended, is that threats and information security requirements have been steadily increasing. This requires precautionary measures and a high level of security and protection of data and services, as well as business continuity and is particular important to hospitals that collect, store and process personal data and health data of their patients. The information security level can be increased by applying an information security model. The studies have analysed the state of information security of medical establishments in Bulgaria and defined a concept for an information security model based on: good practices; following the recommendations for technical implementation required by the GDPR; accounting for the principle of protection levels.

• 

  DEEP NEURAL NETWORKS FOR DETECTION OF CREDIT CARD FRAUD

  This publication presents research on the possibility of using Deep Neural Net-works (DNNs) for detection of credit card fraud. The research is based on an open da-taset and aims to determine how the varying number of hidden layers and other archi-tectural parameters (width of each layer, activation functions) affects training and predictive ... This publication presents research on the possibility of using Deep Neural Net-works (DNNs) for detection of credit card fraud. The research is based on an open da-taset and aims to determine how the varying number of hidden layers and other archi-tectural parameters (width of each layer, activation functions) affects training and predictive potential of the network. It also aims to determine how to use generative-adversarial approach efficiently in order to overcome the problem with the imbalance between legitimate and fraudulent transactions, which is crucial characteristic of the datasets related to detection of credit card fraud. The publication presents the results of various experiments, conducted to achieve the stated goals. A number of experiments have been carried out combining network training of various depth of the network and with different parameters of the learning process, for example, activation function and dropout values. The experiments focus on using generative-adversarial approach as a method for oversampling, in par-ticular. The results indicate that deep neural networks with moderate hidden layers, combined with methods for oversampling are performing much better in identifying fraudulent transactions than the classical neural networks, consisting of only one hid-den layer. The results also indicate that using generative-adversarial approach as a method for oversampling is comparable in efficiency to other widely used techniques.

• 

  THE ROLE OF INTERNAL AND EXTERNAL AUDITORS FOR IDENTIFYING FRAUDS IN ORGANIZATIONS

  The variety of ways and approaches to fraud necessitates the updating of measures and mechanisms to identify and limit them. By properly implementing these mechanisms and approaches, the risk assessment and the display of indicators signalling misconduct contribute to reducing them and improving the effectiveness of the control impact. The ... The variety of ways and approaches to fraud necessitates the updating of measures and mechanisms to identify and limit them. By properly implementing these mechanisms and approaches, the risk assessment and the display of indicators signalling misconduct contribute to reducing them and improving the effectiveness of the control impact. The relevance of the study is due to the growing threat of spreading fraud and the need for adequate and timely measures to limit them. The purpose of the research study is to outline the possible actions to curb fraud, applied by internal and external auditors, as well as to examine the methodology used in the preparation of fraud risk assessments. The tasks are as follows: to clarify the role of internal audit in combating fraud; examining methodological guidelines for fraud risk assessment; implementation of anti-fraud management measures and adequate audit procedures. The thesis being defended is that fraud is a complex phenomenon and the role of internal and external auditors is essential for detecting and limiting it by applying innovative and adequate methods. The study substantiates the relationship between management actions and the ability to prevent and detect fraud, as well as the conditionality of audit procedures, performed by external auditors on the type and nature of possible fraudulent financial reporting schemes.