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Conference Paper/Proceeding/Abstract 687 views

Detection of evil flies : securing air-ground aviation communication

Suleman Khan, Pardeep Kumar Orcid Logo, An Braeken, Andrei Gurtov

Proceedings of the 27th Annual International Conference on Mobile Computing and Networking, Pages: 852 - 854

Swansea University Author: Pardeep Kumar Orcid Logo

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DOI (Published version): 10.1145/3447993.3482869

Abstract

The aviation community is employing various air traffic control and mobile communication technologies, such as ubiquitous datalinks, wireless communication architectures and protocols. Recently, software-defined networking (SDN) based architectures (i.e., cockpit network communications environment t...

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Published in: Proceedings of the 27th Annual International Conference on Mobile Computing and Networking
ISBN: 978-1-4503-8342-4
Published: New York, NY, USA ACM 2021
URI: https://cronfa.swan.ac.uk/Record/cronfa57884
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first_indexed 2021-09-14T10:33:51Z
last_indexed 2022-03-29T03:22:19Z
id cronfa57884
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fullrecord <?xml version="1.0"?><rfc1807><datestamp>2022-03-28T18:55:46.4932683</datestamp><bib-version>v2</bib-version><id>57884</id><entry>2021-09-14</entry><title>Detection of evil flies : securing air-ground aviation communication</title><swanseaauthors><author><sid>90a5efa66b9ae87756f5b059eb06ef1e</sid><ORCID>0000-0001-8124-5509</ORCID><firstname>Pardeep</firstname><surname>Kumar</surname><name>Pardeep Kumar</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2021-09-14</date><deptcode>SCS</deptcode><abstract>The aviation community is employing various air traffic control and mobile communication technologies, such as ubiquitous datalinks, wireless communication architectures and protocols. Recently, software-defined networking (SDN) based architectures (i.e., cockpit network communications environment testing (COMET))have been proposed for Air-Ground communication. However, an evil can break the communication between a pilot and air traffic control, resulting in a hazardous (or life-threatening) situation up in the air or failure of ground equipment. This paper proposes an efficient evil detection and prevention mechanism (called DoEF)for the COMET architecture. The proposed DoEF utilizes a deep learning-based approach, i.e., long-short term memory (LSTM), to detect the evil flies and provide possible countermeasures. Our preliminary results show that the proposed scheme reduces the detection time and increases the detection accuracy of distributed denial of service (DDoS) attacks for the aviation network.</abstract><type>Conference Paper/Proceeding/Abstract</type><journal>Proceedings of the 27th Annual International Conference on Mobile Computing and Networking</journal><volume/><journalNumber/><paginationStart>852</paginationStart><paginationEnd>854</paginationEnd><publisher>ACM</publisher><placeOfPublication>New York, NY, USA</placeOfPublication><isbnPrint/><isbnElectronic>978-1-4503-8342-4</isbnElectronic><issnPrint/><issnElectronic/><keywords/><publishedDay>25</publishedDay><publishedMonth>10</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-10-25</publishedDate><doi>10.1145/3447993.3482869</doi><url/><notes/><college>COLLEGE NANME</college><department>Computer Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>SCS</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2022-03-28T18:55:46.4932683</lastEdited><Created>2021-09-14T11:26:44.4839951</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Mathematics and Computer Science - Computer Science</level></path><authors><author><firstname>Suleman</firstname><surname>Khan</surname><order>1</order></author><author><firstname>Pardeep</firstname><surname>Kumar</surname><orcid>0000-0001-8124-5509</orcid><order>2</order></author><author><firstname>An</firstname><surname>Braeken</surname><order>3</order></author><author><firstname>Andrei</firstname><surname>Gurtov</surname><order>4</order></author></authors><documents/><OutputDurs/></rfc1807>
spelling 2022-03-28T18:55:46.4932683 v2 57884 2021-09-14 Detection of evil flies : securing air-ground aviation communication 90a5efa66b9ae87756f5b059eb06ef1e 0000-0001-8124-5509 Pardeep Kumar Pardeep Kumar true false 2021-09-14 SCS The aviation community is employing various air traffic control and mobile communication technologies, such as ubiquitous datalinks, wireless communication architectures and protocols. Recently, software-defined networking (SDN) based architectures (i.e., cockpit network communications environment testing (COMET))have been proposed for Air-Ground communication. However, an evil can break the communication between a pilot and air traffic control, resulting in a hazardous (or life-threatening) situation up in the air or failure of ground equipment. This paper proposes an efficient evil detection and prevention mechanism (called DoEF)for the COMET architecture. The proposed DoEF utilizes a deep learning-based approach, i.e., long-short term memory (LSTM), to detect the evil flies and provide possible countermeasures. Our preliminary results show that the proposed scheme reduces the detection time and increases the detection accuracy of distributed denial of service (DDoS) attacks for the aviation network. Conference Paper/Proceeding/Abstract Proceedings of the 27th Annual International Conference on Mobile Computing and Networking 852 854 ACM New York, NY, USA 978-1-4503-8342-4 25 10 2021 2021-10-25 10.1145/3447993.3482869 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2022-03-28T18:55:46.4932683 2021-09-14T11:26:44.4839951 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Suleman Khan 1 Pardeep Kumar 0000-0001-8124-5509 2 An Braeken 3 Andrei Gurtov 4
title Detection of evil flies : securing air-ground aviation communication
spellingShingle Detection of evil flies : securing air-ground aviation communication
Pardeep Kumar
title_short Detection of evil flies : securing air-ground aviation communication
title_full Detection of evil flies : securing air-ground aviation communication
title_fullStr Detection of evil flies : securing air-ground aviation communication
title_full_unstemmed Detection of evil flies : securing air-ground aviation communication
title_sort Detection of evil flies : securing air-ground aviation communication
author_id_str_mv 90a5efa66b9ae87756f5b059eb06ef1e
author_id_fullname_str_mv 90a5efa66b9ae87756f5b059eb06ef1e_***_Pardeep Kumar
author Pardeep Kumar
author2 Suleman Khan
Pardeep Kumar
An Braeken
Andrei Gurtov
format Conference Paper/Proceeding/Abstract
container_title Proceedings of the 27th Annual International Conference on Mobile Computing and Networking
container_start_page 852
publishDate 2021
institution Swansea University
isbn 978-1-4503-8342-4
doi_str_mv 10.1145/3447993.3482869
publisher ACM
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 0
active_str 0
description The aviation community is employing various air traffic control and mobile communication technologies, such as ubiquitous datalinks, wireless communication architectures and protocols. Recently, software-defined networking (SDN) based architectures (i.e., cockpit network communications environment testing (COMET))have been proposed for Air-Ground communication. However, an evil can break the communication between a pilot and air traffic control, resulting in a hazardous (or life-threatening) situation up in the air or failure of ground equipment. This paper proposes an efficient evil detection and prevention mechanism (called DoEF)for the COMET architecture. The proposed DoEF utilizes a deep learning-based approach, i.e., long-short term memory (LSTM), to detect the evil flies and provide possible countermeasures. Our preliminary results show that the proposed scheme reduces the detection time and increases the detection accuracy of distributed denial of service (DDoS) attacks for the aviation network.
published_date 2021-10-25T04:13:57Z
_version_ 1763753944459247616
score 11.036706

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