NTDA: The Mitigation of Denial of Service (DoS) Cyberattack Based on Network Traffic Detection Approach

被引:0
|
作者
Tahboush, Muhannad [1 ]
Hamdan, Adel [2 ]
Alzobi, Firas [1 ]
Husni, Moath [3 ]
Adawy, Mohammad [1 ]
机构
[1] World Islamic Sci & Educ Univ, Informat & Networks Syst Dept, Amman, Jordan
[2] World Islamic Sci & Educ Univ, Dept Comp Sci, Amman, Jordan
[3] World Islamic Sci & Educ Univ, Software Engn Dept, Amman, Jordan
关键词
Network security; DoS attack; cyberattack; network traffic; ATTACKS;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Security is one of the important aspects which is used to protect data availability from being compromised. Denial of service (DoS) attack is a common type of cyberattack and becomes serious security threats to information systems and current computer networks. DoS aims to explicit attempts that will consume and disrupt victim resources to limit access to information services by flooding a target system with a high volume of traffic, thereby preventing the availability of the resources to the legitimate users. However, several solutions were developed to overcome the DoS attack, but still suffer from limitations such as requiring additional hardware, fail to provide a unified solution and incur a high delay of detection accuracy. Therefore, the network traffic detection approach (NTDA) is proposed to detect the DoS attack in a more optimistic manner based on various scenarios. First, the high network traffic measurements and mean deviation, second scenario relied on the transmission rate per second (TPS) of the sender. The proposed algorithm NTDA was simulated using MATLAB R2020a. The performance metrics taken into consideration are false negative rate, accuracy, detection rate and true positive rate. The simulation results show that the performance parameters of proposed NTDA algorithm outperformed in DoS detection the other well-known algorithms.
引用
收藏
页码:692 / 698
页数:7
相关论文
共 50 条
  • [1] Research on a Denial of Service (DoS) Detection System Based on Global Interdependent Behaviors in a Sensor Network Environment
    Song, Jae-gu
    Jung, Sungmo
    Kim, Jong Hyun
    Seo, Dong Il
    Kim, Seoksoo
    SENSORS, 2010, 10 (11) : 10376 - 10386
  • [2] An Intelligence Technique for Denial of Service (DoS) Attack Detection
    Manan, Wan Nurulsafawati Wan
    Safiuddin, Tuan Muhammad
    Dzolkhifli, Zarina
    Hassin, Mohd Hafiz Mohd
    ADVANCED SCIENCE LETTERS, 2018, 24 (10) : 7446 - 7450
  • [3] Design and Implementation of Post-Detection of Denial of Service (DoS) as a Mitigation System (PDDMS) Based on Dynamic Access Control List Algorithm
    Rochim, Adian Fatchur
    Mochtar, Fahmi Maghrizal
    Fauzi, Adnan
    2021 4TH INTERNATIONAL SEMINAR ON RESEARCH OF INFORMATION TECHNOLOGY AND INTELLIGENT SYSTEMS (ISRITI 2021), 2020,
  • [4] No more DoS? An empirical study on defense techniques for web server Denial of Service mitigation
    Catillo, Marta
    Pecchia, Antonio
    Villano, Umberto
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2022, 202
  • [5] Distributed Denial of Service Attack Detection in Network Traffic Using Deep Learning Algorithm
    Ramzan, Mahrukh
    Shoaib, Muhammad
    Altaf, Ayesha
    Arshad, Shazia
    Iqbal, Faiza
    Castilla, Angel Kuc
    Ashraf, Imran
    SENSORS, 2023, 23 (20)
  • [6] A Comprehensive Survey of Distributed Denial of Service Detection and Mitigation Technologies in Software-Defined Network
    Su, Yinghao
    Xiong, Dapeng
    Qian, Kechang
    Wang, Yu
    ELECTRONICS, 2024, 13 (04)
  • [7] Recursive-clustering-based approach for denial of service (DoS) attacks in wireless sensors networks
    Fouchal, S.
    Mansouri, D.
    Mokdad, L.
    Iouallalen, M.
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2015, 28 (02) : 309 - 324
  • [8] A Queuing Analysis of Tolerating for Denial-of-Service (DoS) Attacks with a Proxy Network
    Aye, Myint Myint
    2009 INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND TECHNOLOGY, VOL II, PROCEEDINGS, 2009, : 366 - 368
  • [9] Mitigating network denial-of-service through diversity-based traffic management
    Matrawy, A
    van Orschot, PC
    Somayaji, A
    APPLIED CRYPTOGRAPHY AND NETWORK SECURITY, PROCEEDINGS, 2005, 3531 : 104 - 121
  • [10] Detecting Distributed Denial of Service in Network Traffic with Deep Learning
    Rusyaidi, Muhammad
    Jaf, Sardar
    Ibrahim, Zunaidi
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2022, 13 (01) : 34 - 41