Creating Features in Python using sliding windows

The first step to using ML for intrusion analysis detection is the creation of Features that can be used in training and detection.  I talk in another blog about creating features from sliding windows bound statistics of packet streams.  We can walk through the steps of GitHub repository contains Python code that creates features from Wireshark/tshark packet streams. The program accepts live tshark output or tshark streams created from .pcap files. 

Network Traffic into Sliding Windows

The example program requires Python and Wireshark/tshark.  The Python code uses 4 multiprocess tasks making this essentially a 5 core process.  It is a 100% CPU bound on a 4 core machine so I suspect it will run faster on a hex-core or above.

There was a tshark+3 task version that ran 15% faster consuming 85% of a 4 core machine. 

The Python modules/processes communicate via Multiprocessing Queues.

Flow of application located on GitHub

1. tshark captures live data or replays data from a pcap file. It each packet as a line of text output in their ek format. I chose it because each record is on a single line so now multi-line json assembly is required. The Python processes launch it and listen to standard out.
2. PacketCapture is a python process that reads tshark and then transforms the data to make it more consumable.  It converts the EK to true JSON and massages some of the label styles to json standard.  The final text is pushed into a message queue
3. PacketAnalyze accepts the dictionary from the Queue.  It creates a node pair identifier and identifies the protocol and forwards the original data, the id and protocol to the next stage via a Queue.  PacketAnalyze also captures aggregated statistics across the run. Nothing is done with those at this time and they are lost when the program exists.
4. ServiceIdentity This module reads and ID, Protocol, packet data structure.  It analyzes the packet to identify the higher-level service type of the message.  Examples include DNS, SMTP, FTP, TLS, HTTP, SMB, SMB2, etc.  The service list is added to the incoming data set and sent to a topic.
5. TimesAndCounts manages the time windows and calculates the time bucket/window statistics and writes them to output.  it reads from the inbound topic and aggregates statistics across a set of incoming packets.  The statistics are retained for a single time window and are written to csv file, one record for each time window.

Sample output

The final output is a CSV with over 20 columns or features. 

tcp_frame_ln	tcp_ip_ln	tcp_ln	udp_frame_ln	udp_ip_ln	udp_ln	arp_frame_ln	num_tls	num_http	num_ftp	num_ssh	num_smtp	num_dhcp	num_dns	num_nbns	num_smb	num_smb2	num_pnrp	num_wsdd	num_ssdp	num_tcp	num_udp	num_arp	num_igmp	pairs	num_ports	num_packets	window_end_time
0	0	0	2006	1084	1118	210	0	2	0	0	0	0	16	4	0	0	0	0	0	0	22	5	18	8	14	46	14806
0	0	0	3479	2699	2487	0	0	5	0	0	0	0	6	15	2	0	0	0	0	0	28	0	6	4	8	34	19806
0	0	0	16524	2781	14822	0	0	17	0	0	0	3	4	0	1	0	0	6	0	0	33	0	9	5	13	42	24806
0	0	0	9798	1810	8636	84	0	18	0	0	0	5	0	0	0	0	0	0	0	0	23	2	2	5	7	27	29806
0	0	0	16843	5915	15239	420	0	10	0	0	0	0	12	4	0	0	0	6	0	0	36	10	20	10	14	66	34806
0	0	0	14842	7344	12918	168	0	33	0	0	0	1	10	2	0	0	0	0	0	0	46	4	6	8	12	56	39806
0	0	0	8476	4324	7168	0	0	22	0	0	0	0	2	8	0	0	0	0	0	0	32	0	0	4	7	32	44806
0	0	0	5126	2956	4244	0	0	5	0	0	0	0	6	6	2	0	0	2	0	0	23	0	0	4	11	23	49806
0	0	0	2602	1535	1924	210	0	6	0	0	0	1	2	4	4	0	0	0	0	0	17	5	0	6	10	22	54806
0	0	0	4914	2800	4168	84	0	6	0	0	0	0	3	3	3	0	0	2	0	0	19	2	0	5	12	21	59806
6857	6615	6111	18677	9873	16171	504	0	16	0	0	0	7	21	2	4	0	2	4	0	13	59	12	21	16	33	105	64806
6929	6747	6203	34439	17134	29359	420	0	31	0	0	0	5	23	30	2	0	15	6	0	13	120	10	24	15	36	167	69806
29150	14857	26074	15555	8969	12973	0	0	17	0	0	0	0	13	17	4	0	5	2	0	46	63	0	4	11	24	113	74806
0	0	0	2771	1020	1843	0	0	3	0	0	0	1	10	6	1	0	0	0	0	0	22	0	0	8	14	22	79806
0	0	0	8781	7696	9281	0	0	3	0	0	0	1	2	0	0	0	5	0	0	0	19	0	0	6	11	19	84806

Updating the Program

The program is extensible.  Obvious options include

1. Add additional service detectors
2. Output the PacketAnalyze summary data to a file

Video

.pcap Notes

Wireshark changed their labeling on their JSON at some point in the last 3-5 years. You may have problems reading some older pcap files

References

• Repository: 
• Python source code https://github.com/freemansoft/Network-intrusion-dataset-creator This code is 8x faster than the original.
• Other Blogs and Videos: 
• Blog: https://joe.blog.freemansoft.com/2021/04/network-intrusion-features-via-sliding.html
• Video: https://youtu.be/b3MaxbAAdDw
• Blog: https://joe.blog.freemansoft.com/2021/04/creating-features-in-python-using.html
• Video: https://youtu.be/jKgGh5a5gFA
• Originating Research 
• Research paper the original source code was based on. https://www.researchgate.net/profile/Nadun-Rajasinghe/project/A-customizable-Network-Intrusion-Detection-dataset-creating-framework/attachment/5aff08f8b53d2f63c3ccae32/AS:627686015766528@1526663416701/download/1570426776.pdf?context=ProjectUpdatesLog
• Original Python source repository https://github.com/nrajasin/Network-intrusion-dataset-creator