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Ahmad Zainudin,Dong-Seong Kim,Jae-Min Lee 한국통신학회 2022 한국통신학회 학술대회논문집 Vol.2022 No.2
Software-Defined Networking (SDN) is a promising platform for Industrial Internet of Things (IIoT) networks that provide flexibility, reliability, and efficiency. SDN-based IIoT networks have a centralized controller that is a single vulnerable target to attack. In this paper, a lightweight Distributed Denial-of-Service (DDoS) detection and classification based on network features is proposed using an improved CNN-LSTM and tested with the latest CICDDoS2019 dataset. The proposed model achieves a low computation time which enables the delay constraint industrial network with a DDoS detection rate above 99.02% and a computation time of 0.14 ms.
Ahmad Zainudin,Adinda Riztia Putri,Goodness Oluchi Anyanwu,Cosmas Ifeanyi Nwakanma,Dong-Seong Kim,Jae-Min Lee 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.11
In this paper, we proposed a hybrid-Long Short-Term Memory (LSTM) deep learning algorithm for thermal sensor-based Human Activity Recognition (HAR). Edge computing is characterized with Deep Learning (DL) computational capability as well as real-time response which is a requirement for non-intrusive HAR application. Applying DL on edge devices is more challenging due to the limited computational capability. Hence, a low-cost computational CNN-LSTM model is proposed in this work. Based on the simulation results, the proposed approach achieved a computational time of 0.5543 ms. which outperforms other algorithms.