The paper presents the main key features of social engineering and a social engineer activity. Emphasis is placed on the study of social engineering techniques in the system of human-machine interaction used to implement the illegal (malicious) manipulation of human behavior patterns. The matrix of social engineering qualification criteria and the map of information security risks caused by social engineer actions were built.
IntroductionThe practice of human-machine interaction (HMI) makes increasingly high demands on the level of information security. This process is like an eternal dispute -what is stronger, a sword or a shield. The evolution of information protection methods reflects the evolution of unauthorized data access methods [1]. Nowadays people are actively embedding computers in their environment; they are trying to make the computer more "human", the level of computer dependence on the outside world also increases with the development of networks [2,3]. On the other hand, the human factor continues to be the least controlled element of HMI [4], which, in turn, according to the modern information and communication technologies development creates not only new opportunities, but also new risks [5]. As a result, the number of information security [6] vulnerability factors increases. Someday, a computer will learn how to evaluate human behavior [7,8] and make decisions based on the results of cognitive processes analysis, considering the value and semantic aspects of personality behavior. Consequently, we are waiting for a new evolutionary leap in the confrontation of "sword and shield". But, so long as a person is only understandable by the other person, the social engineering knowledge will be in demand [9]. qualitative terms of "probability" and "impact" on the risk object dispersed in an ascending order.
This article raises the issues of research investment support tools and the study of existing IT solutions in the field of predictive analytics investment solutions. The research request is based on the lack of accuracy, and objectivity of existing methods of investment analysis and means of its automation. A review of existing technical solutions and technologies is carried out. The process of analyzing investment instruments has been studied, and bottlenecks in existing approaches to analysis have been identified. A solution for implementing a system of predictive analytics of investment instruments has been developed. The solution is based on the business requirements and functional requirements of the software development company.
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