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2020-05-04
Zalozhnev, Alexey Yu., Andros, Denis A., Ginz, Vasiliy N., Loktionov, Anatoly Eu..  2019.  Information Systems and Network Technologies for Personal Data Cyber Security in Public Health. 2019 International Multidisciplinary Information Technology and Engineering Conference (IMITEC). :1–5.
The article focuses on Personal Data Cyber Security Systems. These systems are the critical components for Health Information Management Systems of Public Health enterprises. The purpose of this article is to inform and provide the reader with Personal Data Cyber Security Legislation and Regulation in Public Health Sector and enlighten him with the Information Systems that were designed and implemented for Personal Data Cyber Security in Public Health.
2019-12-18
Chugunkov, Ilya V., Fedorov, Leonid O., Achmiz, Bela Sh., Sayfullina, Zarina R..  2018.  Development of the Algorithm for Protection against DDoS-Attacks of Type Pulse Wave. 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). :292-294.

Protection from DDoS-attacks is one of the most urgent problems in the world of network technologies. And while protect systems has algorithms for detection and preventing DDoS attacks, there are still some unresolved problems. This article is devoted to the DDoS-attack called Pulse Wave. Providing a brief introduction to the world of network technologies and DDoS-attacks, in particular, aims at the algorithm for protecting against DDoS-attack Pulse Wave. The main goal of this article is the implementation of traffic classifier that adds rules for infected computers to put them into a separate queue with limited bandwidth. This approach reduces their load on the service and, thus, firewall neutralises the attack.

2019-05-01
Douzi, S., Benchaji, I., ElOuahidi, B..  2018.  Hybrid Approach for Intrusion Detection Using Fuzzy Association Rules. 2018 2nd Cyber Security in Networking Conference (CSNet). :1-3.

Rapid development of internet and network technologies has led to considerable increase in number of attacks. Intrusion detection system is one of the important ways to achieve high security in computer networks. However, it have curse of dimensionality which tends to increase time complexity and decrease resource utilization. To improve the ability of detecting anomaly intrusions, a combined algorithm is proposed based on Weighted Fuzzy C-Mean Clustering Algorithm (WFCM) and Fuzzy logic. Decision making is performed in two stages. In the first stage, WFCM algorithm is applied to reduce the input data space. The reduced dataset is then fed to Fuzzy Logic scheme to build the fuzzy sets, membership function and the rules that decide whether an instance represents an anomaly or not.