![]() As a result, DDoS attacks on the internal network were detected in real-time and whether or not IP addresses were spoofed was confirmed. ![]() Detection accuracy and performance of the collected real-time traffic on a core network is analyzed thru the use of the proposed algorithm, and a prototype was developed to evaluate the performance of the algorithm. Also, a method is proposed for the effective detection of malware infection systems triggering IP-spoofed DDoS attacks on an edge network. This study calculates the frequency of network-based packet attributes and analyzes the anomalies of the attributes in order to detect IP-spoofed DDoS attacks. Depending on the advancement of IT infrastructure such as the server or network equipment, DDoS attack traffic arising from a few malware-infected systems capable of crippling the organization’s internal network has become a significant threat. Large-scale network environments require effective detection and response methods against DDoS attacks. ![]()
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