KFU. Card publication. Assessment of a Semi-supervised Machine Learning Method for Thwarting Network DDoS Assaults

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

ASSESSMENT OF A SEMI-SUPERVISED MACHINE LEARNING METHOD FOR THWARTING NETWORK DDOS ASSAULTS

Form of presentation

Articles in international journals and collections

Year of publication

2024

��

��

Authors, employees of KFU

Akhmetshin Elvir Munirovich, author

Bibliographic description in the original language

Lakshmi S.G, Durga T.N.V, Srilatha P, Assessment of a Semi-supervised Machine Learning Method for Thwarting Network DDoS Assaults//Lecture Notes in Electrical Engineering. - 2024. - Vol.1155, Is.. - P.307-318.

Annotation

In latest existence, Path identifiers (PID) have utilised as inter-domain routing (IDR) things in association. Though, the PIDs utilised in present methods are immobile that creates it simple for attacker to introduce D DoS flooding attacks. To discourse this problem, current a D-PID structure, which make use of PIDs negotiated among neighbouring domains as IDR substance. The PID of the inter-domain connection between two domains in DPID is going to be kept private and can vary periodically. Cryptographic techniques may be employed as well to safeguard the security of information shared over a network. There is a good possibility that DPID's data-secure technique will stop networking D DoS assaults.

Keywords

Machine Learning

The name of the journal

Lecture Notes in Electrical Engineering

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192388027&doi=10.1007%2f978-981-97-0644-0_28&partnerID=40&md5=0e4b5b93e008df3a2d52ef636468ffea

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=307430&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Akhmetshin Elvir Munirovich	ru_RU
dc.date.accessioned	2024-01-01T00:00:00Z	ru_RU
dc.date.available	2024-01-01T00:00:00Z	ru_RU
dc.date.issued	2024	ru_RU
dc.identifier.citation	Lakshmi S.G, Durga T.N.V, Srilatha P, Assessment of a Semi-supervised Machine Learning Method for Thwarting Network DDoS Assaults//Lecture Notes in Electrical Engineering. - 2024. - Vol.1155, Is.. - P.307-318.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=307430&p_lang=2	ru_RU
dc.description.abstract	Lecture Notes in Electrical Engineering	ru_RU
dc.description.abstract	In latest existence, Path identifiers (PID) have utilised as inter-domain routing (IDR) things in association. Though, the PIDs utilised in present methods are immobile that creates it simple for attacker to introduce D DoS flooding attacks. To discourse this problem, current a D-PID structure, which make use of PIDs negotiated among neighbouring domains as IDR substance. The PID of the inter-domain connection between two domains in DPID is going to be kept private and can vary periodically. Cryptographic techniques may be employed as well to safeguard the security of information shared over a network. There is a good possibility that DPID's data-secure technique will stop networking D DoS assaults.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject		ru_RU
dc.title	Assessment of a Semi-supervised Machine Learning Method for Thwarting Network DDoS Assaults	ru_RU
dc.type	Articles in international journals and collections	ru_RU