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Izvestiya SFedU
Engineering sciences
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ISSN 1999-9429 print
ISSN 2311-3103 online
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  • IMPLICIT THREATS IDENTIFICATION BASED ON ANALYSIS OF USER ACTIVITY ON THE INTERNET SPACE

    V. V. Bova , D. Y. Zaporozhets, Y.A. Kravchenko , E. V. Kuliev , V. V. Kureichik , N. A. Lyz
    2020-10-11
    Abstract ▼

    The article is devoted to the problem of identifying implicit information threats of a user's
    search activity in the internet space based on an analysis of his activity in the course of this interaction.
    The use of knowledge stored in the Internet space for the implementation of criminal intentions
    poses a threat to the whole society. Identifying malicious intent in the users’ actions of the
    global information network is not always a trivial task. The proven technologies for analyzing the
    context of user interests fail in the case of cautious and competent actions of attackers who do not
    explicitly demonstrate the goal they are pursuing. The paper analyzes the threats associated with
    certain scenarios for the implementation of search procedures that manifest themselves in search
    activities. Criteria of inefficient and effective search scenarios estimation are described. Among
    the signs indicating the possibility of a threat, the following main ones are highlighted: avoiding
    solving the problem in aimless navigation or attractive resources, superficial search, lack of
    meaningful immersion in solving the search problem, and chaotic actions during the search.
    To determine the presence of adverse signs, a system of indicators is built. The features of an effective
    scenario for organizing a search in the Internet space are formulated, options for the presence
    of implicit threats for a similar situation are described.An approach for identification the
    described threats is presented taking into account the specified criteria for evaluating various
    scenarios of user behavior in the global information space. A machine learning algorithm has
    been developed to identify problem scenarios by comparing with key behavioral patterns. The
    software implementation of the subsystem for identifying information threats has been created,
    experimental studies have been conducted to confirm the effectiveness of the subsystem. Experimental
    studies were carried out on the basis of processing open data from social networks, as well
    as using analysis of user search activity in the university corporate information environment.

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