Earticle

초록

영어

Today, the network becomes the core element in all that is done efficiently and effectively. They include block transfer, linear transfer, and asynchronous transfer. Optical Burst Switching (OBS) is also classified with them. By picking on data sent with OBS, some security failures occur, and these comprise Replay Attacks, Spoofing, and Burst Header Packet (BHP) flooding attacks which are among these threats. The addressed methodology incorporates the application of the Support Vector Machine (SVM) algorithm to fight down BHP attacks. The simulation outcomes reveal that the performance which is obtained from the actual learning algorithm is the best at 97.7% in all four classes of flooding attacks which include NB-No Block, NB-Wait, No Block, or Block. This proposed Intelligent Identification of BHP Flooding Attack on OBS utilizing Machine Learning Technique (I2BHPOBSML) shows that it is giving better results than the past Works.

목차

Abstract
I. INTRODUCTION
II. LITERATURE REVIEW
III. HEADER PACKET FLOODING ATTACK ON OBS USING ML TECHNIQUE
IV. SIMULATION AND RESULTS
V. CONCLUSION
REFERENCES

키워드

저자

• Muhammad Saleem [ School of Computer Science Minhaj University Lahore Lahore, Pakistan ]
• Muhammad Sajid Farooq [ Department of Cyber Security, NASTP Institute of Information Technology Lahore (NIIT), Lahore, 54000, Pakistan ]
• Muhammad Ubaid Ullah [ University of South Asia, Lahore, Pakistan ]
• Muhammad Shoukat Aslam [ Minhaj University Lahore Lahore, Pakistan ]
• Muhammad Adnan Khan [ School of Computing, Skyline University College, Sharjah, United Arab Emirates. RSCI, Riphah International University, Lahore 54000, Pakistan. ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004