The Edge-IIoT dataset has been featured as a "Document in the top 1% of Web of Science." This indicates that it is ranked within the top 1% of all publications indexed by the Web of Science (WoS) in terms of citations and impact.
In the project we will create a model to predict attack type based on the following 63 features: frame.time ip.src_host ip.dst_host arp.dst.proto_ipv4 arp.opcode arp.hw.size arp.src.proto_ipv4 icmp.checksum icmp.seq_le icmp.transmit_timestamp icmp.unused http.file_data http.content_length http.request.uri.query http.request.method http.referer http.request.full_uri http.request.version http.response http.tls_port tcp.ack tcp.ack_raw tcp.checksum tcp.connection.fin tcp.connection.rst tcp.connection.syn tcp.connection.synack tcp.dstport tcp.flags tcp.flags.ack tcp.len tcp.options tcp.payload tcp.seq tcp.srcport udp.port udp.stream udp.time_delta dns.qry.name dns.qry.name.len dns.qry.qu dns.qry.type dns.retransmission dns.retransmit_request dns.retransmit_request_in mqtt.conack.flags mqtt.conflag.cleansess mqtt.conflags mqtt.hdrflags mqtt.len mqtt.msg_decoded_as mqtt.msg mqtt.msgtype mqtt.proto_len mqtt.protoname mqtt.topic mqtt.topic_len mqtt.ver mbtcp.len mbtcp.trans_id mbtcp.unit_id Attack_label Attack_type
Dataset link: https://www.kaggle.com/datasets/mohamedamineferrag/edgeiiotset-cyber-security-dataset-of-iot-iiot/data