TY - GEN
T1 - GRU-Based DDoS Detection for Enhanced Security in Consumer Electronics
AU - Gupta, Brij B.
AU - Tai Chui, Kwok
AU - Gaurav, Akshat
AU - Arya, Varsha
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - As IOT devices grow in popularity in the consumer electronics industry, protecting them from cybercriminals has emerged as a top priority. Distributed denial of service (DDoS) attacks, among other cyber threats, pose serious risks to the operation and accessibility of these networked devices. When it comes to complex DDoS attacks, traditional security measures are frequently inadequate, requiring the adoption of cutting-edge machine learning algorithms for detection and mitigation. In this research, we present a new method of DDoS detection based on Gated Recurrent Units (GRUs) to improve security for consumer devices in this setting. To train and check the accuracy of our GRU model, we use the KDD-Cup dataset. With an accuracy of 98%, the proposed GRU-based DDoS detection system performs well in detecting and categorizing DDoS attacks. Our method also has a minimal processing overhead so that it may be used on low-power Internet of Things gadgets.
AB - As IOT devices grow in popularity in the consumer electronics industry, protecting them from cybercriminals has emerged as a top priority. Distributed denial of service (DDoS) attacks, among other cyber threats, pose serious risks to the operation and accessibility of these networked devices. When it comes to complex DDoS attacks, traditional security measures are frequently inadequate, requiring the adoption of cutting-edge machine learning algorithms for detection and mitigation. In this research, we present a new method of DDoS detection based on Gated Recurrent Units (GRUs) to improve security for consumer devices in this setting. To train and check the accuracy of our GRU model, we use the KDD-Cup dataset. With an accuracy of 98%, the proposed GRU-based DDoS detection system performs well in detecting and categorizing DDoS attacks. Our method also has a minimal processing overhead so that it may be used on low-power Internet of Things gadgets.
KW - Consumer electronics
KW - DDoS attack detection
KW - GRU (Gated Recurrent Unit)
KW - Internet of Things (loT)
UR - http://www.scopus.com/inward/record.url?scp=85182942747&partnerID=8YFLogxK
U2 - 10.1109/ICCE-Berlin58801.2023.10375584
DO - 10.1109/ICCE-Berlin58801.2023.10375584
M3 - Conference contribution
AN - SCOPUS:85182942747
T3 - IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
BT - 2023 IEEE 13th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2023
T2 - 13th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2023
Y2 - 4 September 2022 through 5 September 2022
ER -