For anomaly detection in crowded scene videos you can use -

• The UCSD annotated dataset available at this link : http://www.svcl.ucsd.edu/projects/anomaly/dataset.htm
• University of Minnesota unusual crowd activity dataset :  http://mha.cs.umn.edu/Movies/Crowd-Activity-All.avi
• Signal Analysis for Machine Intelligence : http://vision.eecs.yorku.ca/research/anomalous-behaviour-data/

For anomaly detection in surveillance videos -

• Virat video dataset  - http://www.viratdata.org/
• McGill University : http://www.cim.mcgill.ca/~javan/index_files/Dominant_behavior.html

Hope this helps!

http://www.svcl.ucsd.edu/projects/anomaly/dataset.htm

http://mha.cs.umn.edu/Movies/Crowd-Activity-All.avi

http://www.viratdata.org/

http://vision.eecs.yorku.ca/research/anomalous-behaviour-data/

http://www.cim.mcgill.ca/~javan/index_files/Dominant_behavior.html

One point to take into account is that these datasets do benchmark against known attacks and do not measure the capability of detection against new attacks.The other thing is that if a dataset includes benign traffic it will correspond to a specific user profile behaviour. This implies that one has to be very careful on the type of conclusions that one draws on these datasets.

This list also might be helpful: http://www.liaad.up.pt/kdus/products/datasets-for-concept-drift

Here are some datasets: http://homepage.tudelft.nl/n9d04/occ/index.html

Some datasets are originally normal / anomaly, other datasets were modified from UCI datasets.

For anomaly detection in crowded scene videos you can use -

• The UCSD annotated dataset available at this link : http://www.svcl.ucsd.edu/projects/anomaly/dataset.htm
• University of Minnesota unusual crowd activity dataset :  http://mha.cs.umn.edu/Movies/Crowd-Activity-All.avi
• Signal Analysis for Machine Intelligence : http://vision.eecs.yorku.ca/research/anomalous-behaviour-data/

For anomaly detection in surveillance videos -

• Virat video dataset  - http://www.viratdata.org/
• McGill University : http://www.cim.mcgill.ca/~javan/index_files/Dominant_behavior.html

Hope this helps!

http://www.svcl.ucsd.edu/projects/anomaly/dataset.htm

http://mha.cs.umn.edu/Movies/Crowd-Activity-All.avi

http://www.viratdata.org/

http://vision.eecs.yorku.ca/research/anomalous-behaviour-data/

http://www.cim.mcgill.ca/~javan/index_files/Dominant_behavior.html

Even though, there were several bench mark data sets available to test an anomaly detector, the better choice would be about the appropriateness of the data and also whether the data is recent enough to imitate the characteristics of today network traffic.

some types of action detection data sets available in

http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm#action

There are multiple major ones which have been widely used in research:

More anomaly detection resource can be found in my GitHub repository: https://github.com/yzhao062/anomaly-detection-resources

there are many datasets available online especially for anomaly detection,

one of the best websites that can provide you different datasets is the Canadian Institute for Cybersecurity.

here te link :

https://www.unb.ca/cic/datasets/index.html

Refer

Conference Paper An efficient approach for network traffic classification

Article Instance Based Classification for Decision Making in Network Data