Abstract— Network slicing is one of the essential elements of the fifth-generation (5G) cellular network. However, security threats like distributed denial of service (DDoS) assaults can have an impact. A DDoS attack on a slice might lead to the exhaustion of the shared resources that are accessible. It's crucial to identify and halt the attack as soon as you can since a DDoS attack will cost a business money in direct proportion to how long it lasts. DDOS assaults have long been a problem on the internet. It interferes not just with the target's service but also with their reputation, costing them customers. Deep learning models may therefore be used to recognise DDoS assaults. Furthermore, the approach is shown to be robust to various types of attacks, including UDP flood and TCP SYN flood attacks.
Keywords—DDoS Attacks, network slicing, deep learning, LSTM, simulation.
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DOI:
10.17148/IJARCCE.2023.125126
