ANALYSIS OF PROBLEMS OF INFORMATION PROTECTION IN SEMANTIC NETWORKS
Abstract
The article analyzes the structure, principles and technologies used in the creation of semantic
networks, the methodology for representing knowledge in a semantic network. Special
attention is paid to the analysis of the structure of queries to data stored in the semantic network.
The purpose of the analysis is to determine the structural elements that carry confidential or other
important information for the further formation of a methodology for its protection, considering
the specifics of the semantic network. As a result of the analysis of typical structures of semantic
networks, the fundamental structural elements and concepts that make up the structure of the analyzed
method of knowledge representation are considered. The specialized languages used for its
construction and the structure of the information request to the knowledge base are determined, in
which elements carrying confidential information and potentially vulnerable to attacks by intruders
were identified. Problems in the information security of semantic networks have been identified,
such as: exposure to malicious SPARQL queries, which can be used to obtain information
from the semantic network without appropriate privileges and accesses; data vulnerability in the
transmitted information request, characterized by a weak focus of existing protection methods on
the specifics of semantic networks; the problem of assessing the level of confidence in the received
data of the semantic network. One of the approaches to solve these problems can be the creation
of a distributed system for evaluating the trust in nodes and data in the semantic network, as well
as the implementation of mechanisms for protecting information and information requests.
The results obtained as a result of the analysis on the structure of the transmitted data are an integral
part of the process of developing information security tools in semantic networks.
References
2. Muhammad L.J., Garba E.J., Oye N.D., Wajiga G.M. On the Problems of Knowledge Acquisition
and Representation of Expert System for Diagnosis of Coronary Artery Disease (CAD), International
Journal of u- and e- Service, Science and Technology, 2018, Vol. 11, No. 3, pp. 49-58.
3. Khabarov S. Kurs lektsiy po distsipline «Predstavlenie znaniy v informatsionnykh sistemakh»
dotsenta kafedry informatsionnykh sistem i tekhnologiy [Course of lectures on the discipline
"Knowledge Representation in Information Systems", Associate Professor of the Department
of Information Systems and Technologies]. SPbGLTU.
4. Patel A., Jain S. Formalism of Representing Knowledge, 6th International Conference on
Smart Computing and Communications, 2017.
5. Kobrinskiy B.A. Metodologiya formalizatsii znaniy [Methodology of knowledge formalization].
RNIMU im. N.I. Pirogova, 2020.
6. The World Wide Web Consortium (W3C). Query. Available at: https://www.w3.org/standards/
semanticweb/query.
7. Macina A. SPARQL distributed query processing over linked data. Université Côte d’Azur,
2019.
8. GibbinsN. Semantic Web in Depth. SPARQL Protocol and RDF Query Language, Electronics
and Computer Science. University of Southampton, 2014.
9. Bamashmoos F., Holyer I., Tryfonas T., Woznowski P. Towards Secure SPARQL Queries in
Semantic Web Applications using PHP Faculty of Engineering. University of Bristol, Bristol,
United Kingdom Faculty of Computing and Information Technology, King Abdulaziz University,
Jeddah, Saudi Arabia, 2017.
10. Kirrane S., Villatam S., d’Aquin M. Privacy, security and policies: A review of problems and
solutions with semantic web technologies, Semantic Web, 2018, Vol. 9, No. 2, pp. 153-161.
11. Rahimzadeh Holagh S., Mohebbi K. A glimpse of Semantic Web trust, SN Applied Sciences.
Switzerland, 2019.
12. Medi´c A., Golubovi´c A. Making secure semantic Web, Universal Journal of Computer Science
and Engineering Technology, 2010, pp. 99-104.
13. Fizza Abbas U., Hussain R., Son J., Oh H. A Study of RDF Security Concerns in Semantic
Web, Fall Conference of the Korean Society for Information Processing, 2013, Vol. 20, No. 2,
pp. 906-909.
14. Malik N., Kumar S. Malik Security in Web Semantics: A Revisit, 12th INDIACom;
INDIACom-2018; 5th International Conference on Computing for Sustainable Global Development,
2018.
15. Atkinson S., Jagodzinski P., Johnson C., Phippen A. Semantic Web: a personal privacy perspective,
WIT Transactions on Information and Communication Technologies, 2006.
16. Odinochkina S.V. Osnovy tekhnologiy XML [Fundamentals of XML technologies]. Saint Petersburg:
NIU ITMO, 2013, 56 p.
17. Elnaggar A. The Semantic Web. Department of Information Technology, Institute of Graduate
Studies and Research, University of Alexandria, Egypt, 2015.
18. Sazonau, V., Sattler, U., Brown, G. General Terminology Induction in OWL, The Semantic
Web – ISWC 2015: 14th International Semantic Web Conference, 2015, pp. 533-550.
19. Maedche A., Volz R. The ontology extraction & maintenance framework Text-To-Onto, Proceedings
of the Workshop on Integrating Data Mining and Knowledge Management, 2001.
20. Glimm B., Stuckenschmidt H. 15 Years of Semantic Web: An Incomplete Survey, Künstliche
Intelligenz. Springer, 2016, Vol. 30, No. 2, pp. 117-130.
21. Sabater J., Sierra C. REGRET: a reputation model for gregarious societies, Proceedings of the
4th international workshop on deception, fraud and trust in agent societies, 2005, pp. 61-69.
22. Babenko L.K., Tolomanenko E.A. Development of algorithms for data transmission in sensor
networks based on fully homomorphic encryption using symmetric Kuznyechik algorithm,
Journal of Physics: Conference Series, 2021, 1812, 012034. DOI: 10.1088/1742-
6596/1812/1/012034