Node Energy Consumption Dataset

Advanced Metering Infrastructure is prone to cyber threats and Distributed Denial of Service is renowned attack that threatens critical infrastructure. Intrusion detection schemes proposed in earlier works consider the network specific parameters for intrusion detection rather than physical layer parameters. Hence, the proposal considers the physical layer parameters in detecting distributed denial of service attack through abnormal energy consumption pattern of the Data concentrator in the advanced metering infrastructure.  The proposal is implemented in real time advanced metering infrastructure. The energy consumption of the data concentrator is observed  under normal traffic scenario. Further, attack is emulated and the energy consumption pattern is recorded. The data under normal and malicious traffic pattern is captured using wireshark and energy information is appended with the captured data.

高级计量基础设施（Advanced Metering Infrastructure）极易遭受网络攻击威胁，其中分布式拒绝服务（Distributed Denial of Service，DDoS）攻击是威胁关键基础设施的典型攻击手段。既往研究提出的入侵检测方案，多仅依托网络特定参数开展入侵检测，未将物理层参数纳入考量范畴。为此，本方案将物理层参数融入高级计量基础设施中数据集中器（Data concentrator）的异常能耗模式检测流程，以实现分布式拒绝服务攻击的识别。本方案在真实高级计量基础设施环境中完成实时部署与实现：首先观测正常流量场景下数据集中器的能耗特征；随后模拟分布式拒绝服务攻击并记录对应能耗模式。研究通过Wireshark捕获正常与恶意流量场景下的数据集，并将能耗信息附加至捕获的数据样本中。