Research Article

Network Traffic Anomaly Detection Based on ML-ESN for Power Metering System

Table 1

Some important metadata information.

IDNameTypeLengthDescription

1EventIDString64Event ID
2ReceiveTimeLong8Receive time
3OccurTimeLong8Occur time
4RecentTimeLong8Recent time
5ReporterIDLong8Reporter ID
6ReporterIPIPstring128Reporter IP
7EventSrcIPIPstring128Event source IP
8EventSrcNameString128Event source name
9EventSrcCategoryString128Event source category
10EventSrcTypeString128Event source type
11EventTypeEnum128Event type
12EventNameString1024Event name
13EventDigestString1024Event digest
14EventLevelEnum4Event level
15SrcIPIPstring1024Source IP
16SrcPortString1024Source port
17DestIPIPstring1024Destination IP
18DestPortString1024Destination port
19NatSrcIPIPstring1024NAT translated source IP
20NatSrcPortString1024NAT translated source port
21NatDestIPIPstring1024NAT translated destination IP
22NatDestPortString1024NAT translated destination port
23SrcMacString1024Source MAC address
24DestMacString1024Destination MAC address
25DurationLong8Duration (second)
26UpBytesLong8Up traffic bytes
27DownBytesLong8Down traffic bytes
28ProtocolString128Protocol
29AppProtocolString1024Application protocol