An Improved 30 Gbps-Class Large-Capacity Packet Processing Method Using Core Isolation Technology

With the spread of 5G services and the development of IoT technology, network traffic for information delivery is increasing in capacity. As network traffic increases, cyber threats also increase, resulting in an increasing importance on traffic analysis. The existing packet processing engine generates a signature by analyzing the characteristics of the attack after the occurrence of suspicious traffic, and based on this, it is difficult to properly respond to new and variant attack traffic because a manual response method is performed to detect the same attack. In addition, even during a network operation, only analysis results generated by passive filtering appear, and when abnormal or suspicious traffic is observed, the quality of the report is often affected by the analysis capability of the administrator. The packet processing method proposed in this paper applies the core isolation method to the NUMA structure applied to the existing 20 Gbps packet processing engine to increase the accessibility of the existing NUMA memory structure and lower the packet drop rate to enable high-capacity 30 Gbps traffic processing. Using the proposed processing engine, it is possible to determine the degree of possibility of abnormal traffic, preferentially by a quick analysis of suspicious traffic rather than a detailed analysis of traffic.