Detection of Distributed Denial of Service (DDoS) Attacks Using Artificial Intelligence on Cloud

被引：19
|
作者：
Alzahrani, Saba [1 ]
Hong, Liang [1 ]
机构：
[1] Tennessee State Univ, Dept Elect & Comp Engn, Nashville, TN 37203 USA
来源：
2018 IEEE WORLD CONGRESS ON SERVICES (IEEE SERVICES 2018) | 2018年
关键词：
DDoS; Anomaly; Signature; Neural; Cloud;
D O I：
10.1109/SERVICES.2018.00031
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This research proposes a system for detecting known and unknown Distributed Denial of Service (DDoS) Attacks. The proposed system applies two different intrusion detection approaches anomaly-based distributed artificial neural networks(ANN5) and signature-based approach. The Amazon public cloud was used for running Spark as the fast cluster engine with varying cores of machines. The experiment results achieved the highest detection accuracy and detection rate comparing to signature based or neural networks-based approach.
引用
收藏
页码：35 / 36
页数：2
相关论文
共 50 条
  • [1] AI in the Detection and Prevention of Distributed Denial of Service (DDoS) Attacks
    Ahmadi, Sina
    [J]. International Journal of Advanced Computer Science and Applications, 2024, 15 (10) : 23 - 29
  • [2] Review on Mitigation of Distributed Denial of Service (DDoS) Attacks in Cloud Computing
    Khadke, Ashwini
    Madankar, Mangala
    Motghare, Manish
    [J]. PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND CONTROL (ISCO'16), 2016,
  • [3] Distributed Denial of Service (DDoS) Attacks Detection Using Machine Learning Prototype
    Hoyos Ll, Manuel S.
    Isaza E, Gustavo A.
    Velez, Jairo I.
    Castillo O, Luis
    [J]. DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE, (DCAI 2016), 2016, 474 : 33 - 41
  • [4] Distributed Denial of Service (DDoS) Attacks Detection System for OpenStack-based Private Cloud
    Virupakshar, Karan B.
    Asundi, Manjunath
    Channal, Kishor
    Shettar, Pooja
    Patil, Somashekar
    Narayan, D. G.
    [J]. INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND DATA SCIENCE, 2020, 167 : 2297 - 2307
  • [5] A Survey on Distributed Denial of Service (DDoS) Attacks in SDN and Cloud Computing Environments
    Dong, Shi
    Abbas, Khushnood
    Jain, Raj
    [J]. IEEE ACCESS, 2019, 7 : 80813 - 80828
  • [6] Distributed Denial of Service (DDoS) Attacks Detection: A Machine Learning Approach
    Samom, Premson Singh
    Taggu, Amar
    [J]. APPLIED SOFT COMPUTING AND COMMUNICATION NETWORKS, 2021, 187 : 75 - 87
  • [7] Protecting against distributed denial of service (DDoS) attacks using distributed filtering
    Trostle, Jonathan
    [J]. 2006 SECURECOMM AND WORKSHOPS, 2006, : 201 - 211
  • [8] Evaluation of Experiments on Detecting Distributed Denial of Service (DDoS) Attacks in Eucalyptus Private Cloud
    Lonea, Alina Madalina
    Popescu, Daniela Elena
    Prostean, Octavian
    Tianfield, Huaglory
    [J]. SOFT COMPUTING APPLICATIONS, 2013, 195 : 367 - 379
  • [9] Distributed denial of service attacks detection in cloud computing using extreme learning machine
    Kushwah, Gopal Singh
    Ali, Syed Taqi
    [J]. INTERNATIONAL JOURNAL OF COMMUNICATION NETWORKS AND DISTRIBUTED SYSTEMS, 2019, 23 (03) : 328 - 351
  • [10] Distributed Denial of Service Attacks in Cloud Computing
    Abusaimeh, Hesham
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2020, 11 (06) : 163 - 168
12345