Security Assurance in Agile Software Development Methods

Agile software development was introduced in the beginning of the 2000s to increase the visibility and efficiency software projects. Since then it has become as an industry standard. However, fitting sequential security engineering development models into iterative and incremental development practices in agile methods has caused difficulties in defining, implementing, and verifying the security properties of software. In addition, agile methods have also been criticized for decreased quality of documentation, resulting in decreased security assurance necessary for regulative purposes and security measurement. As a consequence, lack of security assurance can complicate security incident management, thus increasing the software's potential lifetime cost. This chapter clarifies the requirements for software security assurance by using an evaluation framework to analyze the compatibility of established agile security development methods: XP, Scrum, and Kanban. The results show that the agile methods are not inherently incompatible with security engineering requirements.

Comparing the Emergence of Technical and Social Sciences Research in Artificial Intelligence

Applications of Artificial Intelligence (AI) can be examined from perspectives of different disciplines and research areas ranging from computer science and security, engineering, policymaking, and sociology. The technical scholarship of emerging technologies usually precedes the discussion of their societal implications but can benefit from social science insight in scientific development. Therefore, there is an urgent need for scientists and engineers developing AI algorithms and applications to actively engage with scholars in the social sciences. Without collaborative engagement, developers may encounter resistance to the approval and adoption of their technological advancements. This paper reviews a dataset, collected by Elsevier from the Scopus database, of papers on AI application published between 1997 and 2018, and examines how the co-development of technical and social science communities has grown throughout AI's earliest to latest stages of development. Thus far, more AI research exists that combines social science and technical explorations than AI scholarship of social sciences alone, and both categories are dwarfed by technical research. Moreover, we identify a relative absence of AI research related to its societal implications such as governance, ethics, or moral implications of the technology. The future of AI scholarship will benefit from both technical and social science examinations of the discipline's risk assessment, governance, and public engagement needs, to foster advances in AI that are sustainable, risk-informed, and societally beneficial.

NON-STATE FORMS OF LAW ENFORCEMENT IN UKRAINE: CONSTITUTIONAL AND LEGAL DIMENSION

The article is devoted to the study of the constitutional and legal essence of non-state forms of law enforcement in Ukraine. The author emphasizes that in Ukraine law enforcement has always been associated with the activities of state bodies, but these bodies today under various circumstances are not able to fully ensure the security of all systems operating in society. The development of the European vector of Ukraine, the processes of decentralization and deconcentration of power, the urgent need to create a safe environment have led to the development of non-state forms of law enforcement. The relevance of the study is due to the existing problems of determining the constitutional and legal content of existing non-state forms of law enforcement in Ukraine. The author reveals the problematic issues of defining the term «law and order» and «protection of law and order» in the Constitution of Ukraine and legislation. It is determined that the format of modern problem definition requires the search for opportunities for the development of security engineering with the involvement of non-governmental elements of law enforcement. The author believes that the function of law enforcement is implemented in two forms: state and non-state, respectively, under the form of law enforcement we mean the external manifestation of specific actions carried out by state and non-state elements of law enforcement to protect human rights and freedoms, law enforcement. The opinion that it is necessary to distinguish between private, municipal and public forms of law enforcement is substantiated. Private forms of law enforcement should include the activities of: private security companies; private detectives. The municipal forms of law enforcement include the activities of: the municipal guard; municipal parking inspectors; municipal officials performing law enforcement functions. The public forms of law enforcement include the activities of: public formations for the protection of public order; security coordination offices; public assistants of a district police officer on a voluntary basis. It is concluded that the constitutional and legal design of the definition of law and order with the involvement of non-state forms of its protection is an important form of security engineering and an effective institution for ensuring human and civil rights and freedoms in Ukraine.

Management accounting instruments as a security engineering tools used in solving crisis problems (Threats)

Managing organizations means taking lots of decisions based on information contained mainly in the accounting books and financial statements. The processing of this information for decision-making purposes is the domain of management accounting, offering managers a number of decision-making tools described in this article to help overcome difficulties (threats), also known as crisis situations. From the presented management tools (security engineering tools) budgeting with attention to the creation of a budget in the enterprise (traditional budget and budget based on activity-based costing) and task-based budget in public finance sector units has been characterized. Both budgets were compared, taking into account common features. The comparison shows that budgeting based on activity-based costing and task-based budgeting are instruments combining goals with the tasks of the organization and the efficiency of using the resources available.