Analyzing CDR/IPDR data to find People Network from Encrypted Messaging Services
Abstract
Criminals are increasingly using mobile based communication applications, like WhatsApp, that have end-to-end encryption to connect to each other. This makes traditional analysis of call graphs, or traffic analysis, virtually impossible and so is a hindrance for law enforcement personnel. Old methods of traffic analysis have been rendered useless and criminals, including arms dealers and terrorists, are able to engage in criminal activity undetected by police. At present, law enforcement must use extensive manual effort to parse data provided by cell companies to extract information. We have built a system that analyses cellular GPRS metadata and builds a profile and finds potential call connections explicitly which are implicit in the dataset. This paper describes our approach and system in detail and includes results of our evaluation using an anonymized dataset from Delhi Police. Our system permits call graph analysis to be done, and significantly reduces the time needed from the data analysis process.
Cite
@article{arxiv.1809.09747,
title = {Analyzing CDR/IPDR data to find People Network from Encrypted Messaging Services},
author = {Adya Joshi and Ranjan Bose and Madan Oberoi},
journal= {arXiv preprint arXiv:1809.09747},
year = {2018}
}
Comments
In proceedings of First IEEE International Workshop on IoT and Cloud based Collaborative Analytics for Prevention of Crimes and Heinous Activities (I-CAPCHA 2018), in Conjunction with 4th IEEE international Conference on collaboration and Internet computing (CIC 2018) 7 pages