CC BY
15
УДК 004.8
Алексеенко Ю.В., студент магистратуры 2 курс, факультет «Техника и технологии»
ИСОиП (филиал) ДГТУ Россия, г. Шахты Iuliia Alekseenko, graduate student 2year, Faculty "Engineering and Technology" Institute of Service and Business (Branch) DSTU
Russia, Shakhty Авдеева Т.Г., студент магистратуры 2 курс, факультет «Техника и технологии»
ИСОиП (филиал) ДГТУ Россия, г. Шахты Tatyana Avdeeva, graduate student 2year, Faculty "Engineering and Technology" Institute of Service and Business (Branch) DSTU
Russia, Shakhty
THE APPLICATION OF NEURAL NETWORK FOR CYBERSECURITY
Abstract: Over the pastfew years, the number of cyber attacks has increased dramatically. Currently, not only government organizations and business companies are attacked by hackers, but many Internet users. Recent studies have shown that machine learning and analytics can predict potential attacks pretty accurate. This article contains the results of the analysis of attacks from 2017 to 2018. The authors also describe several ways of protection by using neural networks and machine learning algorithms as a promising solution to the problem.
Keywords: machine learning, neural networks, cybersecurity, artificial intelligence, cyber attacks.
The relevance of the problem aimed at preventing cyberattacks is determined by modern safety requirements. Firstly, the word "cyberattack", is considered as the type of attacks. Cyberattack is any type of offensive acts performed by a person or a group of people aimed at breaking computer systems, information, computer networks, infrastructures, and personal electronic devices. There are two major types of cyberattacks: attacks where the primary goal is to disable the target computer or knock it offline, or attacks where the goal is to get access to the target computer's data and perhaps gain admin privileges on it [1].
The round diagram below shows the motivation of cyberattacks in 20172018. Cyber Crime has more than 64%. The second place takes Cyber Espionage (around 22 %) which presents 1/4 of all analyzed attacks. Hacktivism and Cyber Warfare take the third and fourth places respectively [2].
Motivations of Attacks
Cyber Crime ■ Cyber Espionage Hacktivism ■ Cyber Warfare
5%
8%
22%
65%
Figure 1 - Motivations behind attacks
Last few years there has been a significant increase in the amount of information getting stolen as the result of successful cyberattacks every day. Moreover, the total damage from various attacks is 5 billion. These costs are supposed to be increased greatly over the next 5 years, while the spends on cyber security measures will be1 trillion dollars in the next four years [3].
Thus, the development of new tools and systems to fight cyberattacks is an urgent problem for many business companies and organizations to protect their data and infrastructure. While the set of following steps are usually taken as security measures: company security policy, special software and its constant updating, cloud services, cyber security specialists, many companies are likely to use such new approaches as data analysis and machine learning to insure a more reliable level of security. The Cyber Research Alliance (CRA) identified the application of Big Data Analytics to cyber security as one of the top six priorities for future cyber security research and development [4].
Systems working on these principles are able to detect two types of warnings: attack recognition and anomaly-based behavior in a system. The first type of systems provides a strong defense against familiar attacks; the other is primary focused on those attacks that are not yet encountered. To work correctly both types of systems collect some data to analyze: time when an attack or attempt of this attack happened, the sequence of events which might have led to this attack, differences in data received from various sources, statistical analysis and etc.
All successfully working security systems can be divided into two major classes: human-based and machine-based ones. Most of "analyses-driven solutions" rely on rules created by an expert and therefore miss any attacks that don't match these rules. Meanwhile, today's machine-learning approaches rely on "anomaly detection", to trigger false positives creating distrust of the system and are to be investigated by humans.
For example, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and the machine-learning startup PatternEx
demonstrate an artificial intelligence platform called AI2 that predicts cyber-attacks significantly better than existing systems by continuously incorporating input from human experts. The team showed that AI2 can detect 85 percent of attacks, which is roughly three times better than previous benchmarks, while also reducing the number of false positives by a factor of 5 [5]._
Figure 2 - AI2 system
The application of neural networks for solving information protection problems is primarily related to the intellectual analysis and prediction of time series (for example, the traffic dynamics of a protected local network), as well as the search for hidden correlations in arrays of primary data.
Also, neural networks can be used for solving encryption tasks, for example, changing an encryption algorithm or encryption key where this change will happen randomly at different time periods.
The real problem of using neural networks for cybersecurity is associated with great computing power needed to train this network. This process is time consuming and requires a big array of training data. Thus, sometimes the solutions based on neural networks are hard to use for a large corporate network if the main purpose is online detection.
To summarize, it can be said that using neural networks for cybersecurity problems is a promising solution, since such networks are more flexible if to compare them with pre-programmed detection algorithms.
References:
1 What is a cyber attack? Recent examples show disturbing trends // CSO. URL: https://www.csoonline.com/article/3237324/cyber-attacks-espionage/what-is-a-cyber-attack-recent-examples-show-disturbing-trends.html
2 February 2017 Cyber Attacks Statistics // HACKMAGEDDON. URL: https://www.hackmageddon.com/2017/03/20/february-2017-cyber-attacks-statistics/
3 6 brutal cyber attacks that shook the world in 2017 // moneycontrol. URL: https://www.moneycontrol.com/news/business/6-brutal-cyber-attacks-that-shook-the-world-in-2017-2467803.html
4 Security Analytics: Using Deep Learning to DetectCyber Attacks // UNF Digital Commons. URL: https://digitalcommons.unf.edu/cgi/viewcontent.cgi?article=1783&context=etd
5 System predicts 85 percent of cyber-attacks using input from human experts// Phys.org. URL: https://phys.org/news/2016-04-percent-cyber-attacks-human-experts.html
УДК 37.1174
Arkhipova Irina Yurievna Fourth year master student Federal State Autonomous Education Institution of Higher Education «M. K.
Ammosov North-Eastern Federal
University»
The Republic of Sakha (Yakutia), Yakutsk THE ROLE OF YAKUT ETHNOPEDAGOGICAL TRADITION IN DEVELOPING REGIONAL EDUCATION SYSTEM IN THE REPUBLIC
OF SAKHA
Abstract: this article reveals the question of the role of the Yakut ethnopedagogy in the context of its development pattern before adopting the Comprehensive Project for the modernization of the regional education system. Under the topic the content of the work presents many years of experience in interdisciplinary research in the field of education in the Republic of Sakha. Within the framework of the topic under study, the content of the work presents many years of experience in interdisciplinary research in the field of education in the Republic of Sakha. There is a continuity of the first travelers, researchers and exiles' works and researches on the specificity of the Yakut people, which allowed to distinguish the regional ethnopedagogy as a separate, peculiar in its approaches and, accordingly, the object of study.
Keywords: Yakut ethnopedagogy, interdisciplinarity, ethnosociology, historiography, ethnic characteristics.
The relevance of the study is due to the results of the practical implementation of the theoretical attitudes of the Yakut ethnopedagogy in the field of secondary educational institutions in Yakutia.
The goal of the study is to understand the role of the Yakut ethnopedagogy in the formation of the education system in Yakutia.
The objectives to achieve this goal are as follows:
- To study the Yakut ethnopedagogical tradition;
- To identify the role of the efforts of the Yakut ethnopedagogues in developing the regional education system of Yakutia.
The time frame of this topic covers the period from the beginning of the 90s of the 20th century to 2008.
