LOCATING USER IN 5G NETWORKS USING HIGH-BAND
Authors: Giorgi Akhalaia
Affiliation: georgian technical university
Category:
Keywords: 5G Network Security, Secure Communications; Location-Based Attacks, End-user privacy
ABSTRACT. In recent years, in digital technologies and services, special attention has been paid to the security of user's personal and personally identifiable information. Prior to the introduction of new functionality, the service, user privacy is a constant consideration during the security testing process. The development of mobile technologies, artificial intelligence, automation systems made it necessary to introduce new standards of mobile communications. With 3 key principles (ultra-reliability/low latency; improved mobile broadband; massive vehicle connectivity), the 5G standard will disrupt the mobile communications ecosystem and create a more scalable network. Despite the improved protection mechanisms, there are still weaknesses in the 5G network from which an attacker can carry out certain cyber attacks. A MITM type of attack makes it possible to eavesdrop on the user's device. The aim of the study is to assess the threats in the 5G network in relation to the security of the user's personal data. The focus is on assessing threats related to user location, using vulnerabilities in the 5G network to determine user location, and developing recommendations to protect against it.
References:
1. Huawei Technologies CO,. LTD in “5G Network Architecture – A high Level Perspective”, 2016
2. S. Asad Hussain, S. Ahmed, M. Emran, “Positioning a Mobile Subscriber in a Cellular Network System based on Signal a. Strength”, IAENG International Journal of Computer Science, 34:2, IJCS_34_2_13,2007. b. https://www.researchgate.net/publication/26492533
3. Qualcomm Technologies inc. “What is 5G”, in online article. https://www.qualcomm.com/5g/what-is-5g
4. M. Hanif, “5G Phones Will Drain Your Battery Faster Than You Think”, in online journal, 2020. a. https://www.rumblerum.com/5g-phones-drain-battery-life/
5. Shaik, R.Borgaonkar, S. Park, J.P. Selfert. ” New vulnerabilities in 4G and 5G cellular access network protocols: exposing device capabilities” in WiSec ’19: Proceedings of the 12th Conference on Security and Privacy in Wireless and Mobile Networks, DOI: 10.1145/3317549, ISBN: 9781450367264, 2019.
6. Ultrasecurity, “Strom-Breaked” (Software Package), (Last access: 8.12.2021) a. https://github.com/ultrasecurity/Storm-Breaker
7. SK Telecom, in “5G architecture design and implementation guideline”, 2015.
8. Samsung in online report “Samsung Phone Battery Drains Quickly on 5G Service” a. https://www.samsung.com/us/support/troubleshooting/TSG01201462/
9. Purdy, “Why 5G Can Be More Secure Than 4G” in Forbes online journal, 2019. a. https://www.forbes.com/sites/forbestechcouncil/2019/09/23/why-5g-can-be-more-secure-than-4g/?sh=2ffcdf1657b2
10. Cell Phone Trilateration Algorithm, Online Journal “Computer Science”, 2019. (Last access: 10.12.2021) a. https://www.101computing.net/cell-phone-trilateration-algorithm/
11. Johhny, “How to find the Cell Id location with MCC, MNC, LAC and CellID (CID)”, 2015 a. https://cellidfinder.com/articles/how-to-find-cellid-location-with-mcc-mnc-lac-i-cellid-cid
12. M. Iavich, G. Akhalaia, S.Gnatyuk. Method of Improving the Security of 5G Network Architecture Concept for Energy and Other Sectors of the Critical Infrastructure, In: Zaporozhets A. (eds) Systems, Decision and Control in Energy III. Studies in Systems, Decision and Control, vol 399. Springer, Cham. https://doi.org/10.1007/978-3-030-87675-3_14,
13. M. K. Maheshwari, M.Agiwal, N. Saxena, R. Abhishek. "Flexible Beamforming in 5G Wireless for Internet of Things”, in IETE Technical Review, 36:1, 3-16, DOI: 10.1080/02564602.2017.1381048, 2017. https://doi.org/10.1080/02564602.2017.1381048
14. M. Ivezic, L. Ivezic, “5G Security & Privacy Challenges” in 5G.Security Personal Blog, 2019. a. https://5g.security/cyber-kinetic/5g-security-privacy-challenges/
15. Yusof, R., Khairuddin, U., and Khalid, M., ‘A New Mutation Operation for Faster Convergence in Genetic Algorithm Feature Selection’,In International Journal of Innovative Computing, Information and Control, Vol. 18, No. 10, 2012, pp 7363-7380.
16. Ibrahim S. Shehu, Olumide S, Adewale, Muhammad B.”Vehicle Theft Alert and Location Identification Using GSM, GPS and Web Technologies”, in I.J. Information Technology and Computer Sciences, 2016, 7, 1-7. i. Published Online July 2016 in MECS (http://www.mecs-press.org/)
17. The EU Space Programme (Last Access: 10.12.2021) a. https://www.euspa.europa.eu/european-space/eu-space-programme
18. Hu Z, R. Odarchenko, S. Gnatyuk “Statistical Techniques for Detecting Cyberattacks on Computer Networks Based on an Analysis of Abnormal Traffic Behavior”, in I.J. Computer Network and Information Security, 2020, 6, 1-13 a. Published Online December 2020 in MECS (http://www.mecs-press.org/)
19. M, Iavich, T. Kuchukhidze, S. Gnatyuk, “Novel Certification Method for Quantum Random Number Generators“, in I.J. Computer Network and Information Security, 2021, 3, 28-38 a. Published Online June 2021 in MECS (http://www.mecs-press.org/)
20. Avtandil Gagnidze, Maksim Iavich, Giorgi Iashvili// Novel Version of Merkle Cryptosystem// Bulletin of the Georgian National Academy of Sciences, vol. 11, no. 4, 2017, p. 28-33
21. Giorgi Iashvili, Zhadyra Avkurova, Maksim Iavich, Madina Bauyrzhan, Avtandil Gagnidze, Sergiy Gnatyuk// Content-Based Machine Learning Approach for Hardware Vulnerabilities Identification System// International Conference on Computer Science, Engineering and Education Applications // Springer, Cham, No 23 2021, p. 117 - 126
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