Source Code has moved: https://goo.gl/E7WiXd
In this repository you will find the source code and documentation of the SherLock and Moriarty applications used in the SherLock smartphone data collection experiment. Note: the SherLock agent's source code will be made avalaible soon.
A long-term smartphone sensor dataset with a high temporal resolution. The dataset also offers explicit labels capturing the to activity of malwares running on the devices. The dataset currently contains 10 billion data records from 30 users collected over a period of 2 years and an additional 20 users for 10 months (totaling 50 active users currently participating in the experiment). The primary purpose of the dataset is to help security professionals and academic researchers in developing innovative methods of implicitly detecting malicious behavior in smartphones. Specifically, from data obtainable without superuser (root) privileges. However, this dataset can be used for research in domains that are not strictly security related. For example, context aware recommender systems, event prediction, user personalization and awareness, location prediction, and more. The dataset also offers opportunities that aren't available in other datasets. For example, the dataset contains the SSID and signal strength of the connected WiFi access point (AP) which is sampled once every second, over the course of many months.
To gain full access to the SherLock Dataset, follow these two steps:
- Read, complete and sign the license agreement. The general restrictions are: -The license lasts for 3 years, afterwhich the data must be deleted. -Do not share the data with those who are not bound by the license agreement. -Do not attempt to de-anonymize the individuals (volunteers) who have contributed the data. -Any of your publication that benefit from the SherLock project must cite the following article: Mirsky, Yisroel, et al. "SherLock vs Moriarty: A Smartphone Dataset for Cybersecurity Research." Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security. ACM, 2016. 2)Send the scanned document as a PDF to bgu.sherlock@gmail.com and provide a gmail account to share a google drive folder with.
More information can be found here: http://bigdata.ise.bgu.ac.il/sherlock/
If you use the source code or impliment pcStream, please cite the following paper: Mirsky, Yisroel, et al. "SherLock vs Moriarty: A Smartphone Dataset for Cybersecurity Research." Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security. ACM, 2016.
Yisroel Mirsky yisroel@post.bgu.ac.il