Injection Attack Detection on Internet of Things Device with Machine Learning Method
(1) Bina Nusantara University, Jakarta, Indonesia
(2) Bina Nusantara University, Jakarta, Indonesia
(*) Corresponding Author
Abstract
Full Text:
PDFReferences
Acharya, S. (2022, March 17). Why IoT Security is Important for Today’s Networks? SECTRIO. https://sectrio.com/why-iot-security-is-important-for-todays-networks/.
Statista. (2022a, May). Number of Internet of Things (IoT) connected devices worldwide from 2019 to 2030. Statista. https://www.statista.com/statistics/1183457/iot-connected-devices-worldwide/.
Weinberg, A. (2021, October 24). Top 4 Challenges in IoT Data Collection and Management. FirstPoint. https://www.firstpoint-mg.com/blog/top-4-challenges-in-iotdata-collection-and-management/.
Tawalbeh, L., Muheidat, F., Tawalbeh, M., & Quwaider, M. (2020). IoT privacy and security: Challenges and solutions. Applied Sciences (Switzerland), 10(12). https://doi.org/10.3390/APP10124102.
Conti, M., Dehghantanha, A., Franke, K., & Watson, S. (2018). Internet of Things security and forensics: Challenges and opportunities. In Future Generation Computer Systems (Vol. 78, pp. 544–546). Elsevier B.V. https://doi.org/10.1016/j.future.2017.07.060.
Ferrag, M. A., Friha, O., Hamouda, D., Maglaras, L., & Janicke, H. (2022). Edge-IIoTset: A New Comprehensive Realistic Cyber Security Dataset of IoT and IIoT Applications for Centralized and Federated Learning. IEEE Access, 10, 40281–40306. https://doi.org/10.1109/ACCESS.2022.3165809.
Kidd, I. (2021, September 30). The Shocking DDoS Attack Statistics That Prove You Need Protection. Info Security Magazine. https://www.infosecuritymagazine.com/blogs/ddos-attacks-stats-protection/.
Warburton, D. (2021, May 7). DDoS Attack Trends for 2020. F5 Application Threat Intelligence. https://www.f5.com/labs/articles/threat-intelligence/ddos-attack-trendsfor-2020.
Gaber, T., El-Ghamry, A., & Hassanien, A. E. (2022). Injection attack detection using machine learning for smart IoT applications. Physical Communication, 52. https://doi.org/10.1016/j.phycom.2022.101685.
Danardono, E. (2021). Detection of Distributed Denial of Service Attacks from Internet of Things Devices using SVM and NN-MLP methods [Thesis, Bina Nusantara]. http://library.binus.ac.id/Collections/ethesis_detail/RS2-KG-MTI-2021-0011.
Zhou, F., Pan, H., Gao, Z., Huang, X., Qian, G., Zhu, Y., & Xiao, F. (2021). Fire Prediction Based on CatBoost Algorithm. Mathematical Problems in Engineering, 2021. https://doi.org/10.1155/2021/1929137.
Nugroho, K. S. (2019, October 13). Confusion Matrix for Model Evaluation on Supervised Learning. Medium. https://ksnugroho.medium.com/confusion-matrixfor-evaluation-model-pada-unsupervised-machine-learning-bc4b1ae9ae3f.
Businesswire. (2019). The Growth in Connected IoT Devices is Expected to Generate 79.4ZB of Data in 2025, According to a New IDC Forecast. Businesswire. https://www.businesswire.com/news/home/20190618005012/en/The-Growth-inConnected-IoT-Devices-is-Expected-to-Generate-79.4ZB-of-Data-in-2025-Accordingto-a-New-IDC-Forecast.
Hussain, F., Hussain, R., Hassan, S. A., & Hossain, E. (2019). Machine Learning in IoT Security: Current Solutions and Future Challenges. http://arxiv.org/abs/1904.05735.
Garcia-Alfaro, J., & Navarro-Arribas, G. (2009). A Survey on Cross-Site Scripting Attacks. http://arxiv.org/abs/0905.4850.
DOI: http://dx.doi.org/10.30645/jurasik.v8i1.556
DOI (PDF): http://dx.doi.org/10.30645/jurasik.v8i1.556.g534
Refbacks
- There are currently no refbacks.
JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika)
Published Papers Indexed/Abstracted By: