ML-Defense: Machine Learning for building Dependable Federated Network System

Ranju Kumari; Faheed A.F. Alenezi; Sejun Song; Baek Young Choi

doi:10.1109/ICTC55196.2022.9952982

ML-Defense: Machine Learning for building Dependable Federated Network System

Ranju Kumari
, Faheed A.F. Alenezi
, Sejun Song
, Baek Young Choi

University of Missouri at Kansas City

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	ICTC 2022 - 13th International Conference on Information and Communication Technology Convergence
Subtitle of host publication	Accelerating Digital Transformation with ICT Innovation
Publisher	IEEE Computer Society
Pages	956-961
Number of pages	6
ISBN (Electronic)	9781665499392
DOIs	https://doi.org/10.1109/ICTC55196.2022.9952982
State	Published - 2022
Externally published	Yes
Event	13th International Conference on Information and Communication Technology Convergence, ICTC 2022 - Jeju Island, Korea, Republic of Duration: Oct 19 2022 → Oct 21 2022

Publication series

Name	International Conference on ICT Convergence
Volume	2022-October
ISSN (Print)	2162-1233
ISSN (Electronic)	2162-1241

Conference

Conference	13th International Conference on Information and Communication Technology Convergence, ICTC 2022
Country/Territory	Korea, Republic of
City	Jeju Island
Period	10/19/22 → 10/21/22

ASJC Scopus Subject Areas

Information Systems
Computer Networks and Communications

Keywords

Federation
IoT
ML
SDN
Security
wormhole attack

Access to Document

10.1109/ICTC55196.2022.9952982

Cite this

Kumari, R., Alenezi, F. A. F., Song, S., & Choi, B. Y. (2022). ML-Defense: Machine Learning for building Dependable Federated Network System. In ICTC 2022 - 13th International Conference on Information and Communication Technology Convergence: Accelerating Digital Transformation with ICT Innovation (pp. 956-961). (International Conference on ICT Convergence; Vol. 2022-October). IEEE Computer Society. https://doi.org/10.1109/ICTC55196.2022.9952982

ML-Defense: Machine Learning for building Dependable Federated Network System. / Kumari, Ranju; Alenezi, Faheed A.F.; Song, Sejun et al.
ICTC 2022 - 13th International Conference on Information and Communication Technology Convergence: Accelerating Digital Transformation with ICT Innovation. IEEE Computer Society, 2022. p. 956-961 (International Conference on ICT Convergence; Vol. 2022-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kumari, R, Alenezi, FAF, Song, S & Choi, BY 2022, ML-Defense: Machine Learning for building Dependable Federated Network System. in ICTC 2022 - 13th International Conference on Information and Communication Technology Convergence: Accelerating Digital Transformation with ICT Innovation. International Conference on ICT Convergence, vol. 2022-October, IEEE Computer Society, pp. 956-961, 13th International Conference on Information and Communication Technology Convergence, ICTC 2022, Jeju Island, Korea, Republic of, 10/19/22. https://doi.org/10.1109/ICTC55196.2022.9952982

Kumari R, Alenezi FAF, Song S, Choi BY. ML-Defense: Machine Learning for building Dependable Federated Network System. In ICTC 2022 - 13th International Conference on Information and Communication Technology Convergence: Accelerating Digital Transformation with ICT Innovation. IEEE Computer Society. 2022. p. 956-961. (International Conference on ICT Convergence). doi: 10.1109/ICTC55196.2022.9952982

Kumari, Ranju ; Alenezi, Faheed A.F. ; Song, Sejun et al. / ML-Defense : Machine Learning for building Dependable Federated Network System. ICTC 2022 - 13th International Conference on Information and Communication Technology Convergence: Accelerating Digital Transformation with ICT Innovation. IEEE Computer Society, 2022. pp. 956-961 (International Conference on ICT Convergence).

@inproceedings{d0a79003924d4bd0b2de6ce48bb925e6,

title = "ML-Defense: Machine Learning for building Dependable Federated Network System",

keywords = "Federation, IoT, ML, SDN, Security, wormhole attack",

author = "Ranju Kumari and Alenezi, \{Faheed A.F.\} and Sejun Song and Choi, \{Baek Young\}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 13th International Conference on Information and Communication Technology Convergence, ICTC 2022 ; Conference date: 19-10-2022 Through 21-10-2022",

year = "2022",

doi = "10.1109/ICTC55196.2022.9952982",

language = "English",

series = "International Conference on ICT Convergence",

publisher = "IEEE Computer Society",

pages = "956--961",

booktitle = "ICTC 2022 - 13th International Conference on Information and Communication Technology Convergence",

}

TY - GEN

T1 - ML-Defense

T2 - 13th International Conference on Information and Communication Technology Convergence, ICTC 2022

AU - Kumari, Ranju

AU - Alenezi, Faheed A.F.

AU - Song, Sejun

AU - Choi, Baek Young

PY - 2022

Y1 - 2022

KW - Federation

KW - IoT

KW - ML

KW - SDN

KW - Security

KW - wormhole attack

UR - https://www.scopus.com/pages/publications/85143254964

UR - https://www.scopus.com/pages/publications/85143254964#tab=citedBy

U2 - 10.1109/ICTC55196.2022.9952982

DO - 10.1109/ICTC55196.2022.9952982

M3 - Conference contribution

AN - SCOPUS:85143254964

T3 - International Conference on ICT Convergence

SP - 956

EP - 961

BT - ICTC 2022 - 13th International Conference on Information and Communication Technology Convergence

PB - IEEE Computer Society

Y2 - 19 October 2022 through 21 October 2022

ER -

ML-Defense: Machine Learning for building Dependable Federated Network System

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

Other files and links

Fingerprint

Cite this