Classification of stakeholders (users) of accounting information for the enterprise cybersecurity purposes

Abstract

Introduction. The intensification of cyberrisks due to global hybrid conflicts, the COVID-19 pandemic, and economic imbalances threatens the accounting system as the main generator of economic information, which requires the organization of an effective system of enterprises cybersecurity. It is necessary to understand cyberthreats impact on the functioning of different types of stakeholders for development of the effective cybersecurity.Purpose. The main purpose is to research and improve the classification of accounting information users for the enterprises cybersecurity and minimize the variable cyberrisks that threaten different groups of stakeholders.Methods. General scientific empirical, logical and historical methods of cognition of reality in the process of researching the relevance of variable cyberthreats for different types of stakeholders were used. The research is based on general methods of studying economic processes, facts and phenomena from the standpoint of accounting and enterprises cybersecurity. The information base of the research is historical documents on the classification of stakeholders, scientific works of domestic and foreign scientists about dividing users of accounting information into types, and so on.Results. It is proved that the classical scientific views on the classification of accounting information users are ineffective for the purposes of enterprises cyberprotection, as they do not take into account the activation of relevant for the digital economy of variable cyberthreats. It is proposed to classify accounting information users by the following criteria: the ability to manage the activities of the business entity, the right of access, the likelihood of cyberthreats, the ability to dispose of the access right, access to accounting objects, functional law, information processing, economic activity, age, organizational and legal form, type of communication channels used, frequency of information acts.Discussion. The use of the proposed stakeholders’ classification helps to identify cyberrisks; prevent, avoid and minimize cyberthreats consequences, relevant to each type of accounting information users, which requires further research about enterprises cybersecurity.

Accountancy for E-Business Enterprises Based on Cyber Security

“…There are advantages to these e-commerce solutions, and the best one will depend on the company and the target market (Hendra et al, 2021, Arun et al, 2022. Digital information and communication technologies can support and improve company operations under the umbrella of e-business (Muravskyi et al, 2021). When it comes to the online exchange of products and services, E-commerce is only a subset of e-business (Gosal et al, 2021).…”

Network accounting information security based on classification and regression tree algorithm

“…Accounting data stored in various media may face security threats such as unauthorized access, modification, or deletion by unauthorized personnel. The main threat faced by accounting data in transmission is malicious intrusion by network hackers, who illegally alter, delete, or steal accounting data [5].…”

“…To establish a classification and regression tree for a learning set, there are the following steps: (1) using the entire training set as the root node; (2) segmenting nodes: If the samples included in the node belong to the same category, treat this node as a leaf node; If not, continue to split it; (3) scanning all the attributes contained in the node and calculate the Gini value for each attribute when divided into different situations; (4) finding the appropriate attributes and segmentation values, and determine whether the segmentation can minimize the Gini coefficient after segmentation; (5) dividing the nodes into two subsets: left subtree and right subtree; ( 6) repeating ( 2)-( 5) for the left subtree; ( 7) repeating ( 2)-( 5) for the right subtree. Due to the binary segmentation performed by the classification and regression tree, for multiple different partitions of the attributes in step 3 above, if the values are discrete values such as a, b and c, there are three situations in the partition: ab, ac, and bc.…”