Detecting DDoS Attacks in IoT-Based Networks Using Matrix Profile

被引:5
|
作者
Alzahrani, Mohammed Ali [1 ]
Alzahrani, Ali M. [1 ]
Siddiqui, Muhammad Shoaib [1 ]
机构
[1] Islamic Univ Madinah, Fac Comp & Informat Syst, Madinah 42351, Saudi Arabia
来源
APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 16期
关键词
Distributed Denial of Services (DDoS) attacks; Internet of Things (IoT); matrix profile; smart cities; anomaly detection; CHALLENGES;
D O I
10.3390/app12168294
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The Internet of Things (IoT) is a swiftly developing technology in all sectors, with the number of devices that connect to the Internet has increased remarkably in recent years. However, most of these devices use cheap hardware and lack a concrete security defence system. This may encourage hackers to recruit these devices and use them to launch Distributed Denial of Service (DDoS) attacks, which is one of the main causes of concern among security engineers. This paper investigates the possibility of using a matrix profile to detect DDoS attacks in an IoT-based environment. According to our empirical experiments, the preliminary findings illustrate that the matrix profile algorithm can efficiently detect IoT-based DDoS attacks.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] Matrix Profile Based Algorithms using Self-Collected Data for Detecting DDoS Attacks in IoT Equipment
    Sinan, Fahri
    Fuladi, Ramin
    Anarim, Emin
    [J]. 2024 IEEE INTERNATIONAL BLACK SEA CONFERENCE ON COMMUNICATIONS AND NETWORKING, BLACKSEACOM 2024, 2024, : 135 - 139
  • [2] Detecting DDoS Attacks in IoT Environment
    Labiod, Yasmine
    Korba, Abdelaziz Amara
    Ghoualmi-Zine, Nacira
    [J]. INTERNATIONAL JOURNAL OF INFORMATION SECURITY AND PRIVACY, 2021, 15 (02) : 145 - 180
  • [3] Mitigation against DDoS Attacks on an IoT-Based Production Line Using Machine Learning
    Huraj, Ladislav
    Horak, Tibor
    Strelec, Peter
    Tanuska, Pavol
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (04): : 1 - 18
  • [4] Detecting Sinkhole Attacks in IoT-Based Wireless Sensor Networks Using Distance From Base Station
    Mondal, Koushik
    Yadav, Satyendra Singh
    Pal, Vipin
    Singh, Akhilendra Pratap
    Yogita, Yogita
    Singh, Mangal
    [J]. INTERNATIONAL JOURNAL OF INFORMATION SYSTEM MODELING AND DESIGN, 2022, 13 (06)
  • [5] Detecting the Cyber Attacks on IoT-Based Network Devices Using Machine Learning Algorithms
    Calp, M. Hanefi
    Butuner, Resul
    [J]. JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, 2024,
  • [6] Matrix profile for DDoS attacks detection
    Alotaibi, Faisal
    Lisitsa, Alexei
    [J]. PROCEEDINGS OF THE 2021 16TH CONFERENCE ON COMPUTER SCIENCE AND INTELLIGENCE SYSTEMS (FEDCSIS), 2021, : 357 - 361
  • [7] Detection and Mitigation of DoS and DDoS Attacks in IoT-Based Stateful SDN: An Experimental Approach
    Galeano-Brajones, Jesus
    Carmona-Murillo, Javier
    Valenzuela-Valdes, Juan F.
    Luna-Valero, Francisco
    [J]. SENSORS, 2020, 20 (03)
  • [8] Detection of DDoS Attacks on Urban IoT Devices Using Neural Networks
    Obetta, Simon Onyebuchi
    Moldovan, Arghir-Nicolae
    [J]. PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, BIG DATA AND SECURITY, IOTBDS 2023, 2023, : 236 - 242
  • [9] A Measurement Study of IoT-Based Attacks Using IoT Kill Chain
    Haseeb, Junaid
    Mansoori, Masood
    Welch, Ian
    [J]. 2020 IEEE 19TH INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS (TRUSTCOM 2020), 2020, : 557 - 567
  • [10] DDoS Attack Detection in IoT-Based Networks Using Machine Learning Models: A Survey and Research Directions
    Alahmadi, Amal A.
    Aljabri, Malak
    Alhaidari, Fahd
    Alharthi, Danyah J.
    Rayani, Ghadi E.
    Marghalani, Leena A.
    Alotaibi, Ohoud B.
    Bajandouh, Shurooq A.
    [J]. ELECTRONICS, 2023, 12 (14)