You can try these techniques and many more.- All anomaly detection techniques
As discussed in article, these are outlier detection techniques.Are you looking for outliers? better to get some known abnormalities and build a classification.
If supervised not possible, try to fit one of these approaches-
ABOD for identifying abnormalities in high dimensional data
Should clustering be based on distance or density to find outliers(abnormalities)
Connectivity based outlier detection technique
There are other techniques like PCA based, regression based, auto-encoder, knn, weighted Knn and even self organizing map (SOM) . let me know if you need some more information.
Imp- Know your abnormalities better before jumping to machine learning, I have experienced that even qq plot or just data points 3sd away might give better anomaly detection.