Abstract
Expanding usage of mobile technologies and devices causes new challenges, especially in terms of security. In the near future, the number of battery powered devices will also significantly increase. Current security approaches are not sufficient for these issues and high-complexity cryptographic techniques are not suitable for such devices. To address these problems, physical layer (PHY) security solutions have recently emerged. Some 5G candidate techniques such as full-duplex communication (FD) and artificial noise transmission (AN) are exploited in various PHY security solutions due to their performance advantages. In this study, a scenario resembling a factory environment is considered and security level is analyzed in real-time by utilizing FD and AN methods. The aim of this analysis is to investigate physically secure transmission regions and to expand these regions by intelligently using AN. Our proposed approach is evaluated in real- time with a testbed that consists of software defined radios (SDRs). Two devices with very different front-end characteristics are utilized as eavesdroppers to analyze hardware effects on the eavesdropping performance. As observed with experiments, robust secure regions can be created by the use of AN on eavesdroppers effectively.
Original language | English |
---|---|
Title of host publication | 2017 IEEE Globecom Workshops, GC Wkshps 2017 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1-7 |
Number of pages | 7 |
ISBN (Electronic) | 9781538639207 |
DOIs | |
Publication status | Published - 2 Jul 2017 |
Event | 2017 IEEE Global Telecommunications Conference, GC 2017 - Singapore, Singapore Duration: 4 Dec 2017 → 8 Dec 2017 |
Publication series
Name | 2017 IEEE Globecom Workshops, GC Wkshps 2017 - Proceedings |
---|---|
Volume | 2018-January |
Conference
Conference | 2017 IEEE Global Telecommunications Conference, GC 2017 |
---|---|
Country/Territory | Singapore |
City | Singapore |
Period | 4/12/17 → 8/12/17 |
Bibliographical note
Publisher Copyright:© 2017 IEEE.
Funding
This work is supported by TUBITAK under Grant 115E827.
Funders | Funder number |
---|---|
TUBITAK | 115E827 |
Keywords
- Artificial noise
- Eavesdropper
- Full-duplex
- Physical layer security
- Software defined radio