Network-based detection of SMS attacks, abuse and spam
The fast growth in mobile phone use has brought an increase in SMS usage as well as a marked upwards trend in the use of SMS as a vector for malware, spam and other attacks.
This work studies methods to detect and handle such attacks and abuse in as close to real-time as possible. It consists of several projects that look at various ways to characterize the attacks and recognize them on the mobility network in early stages (using message fingerprints, similarity metrics, counting Bloom filters, etc.), then evaluate propagation rate / extent and institute mitigation solutions (using machine learning and statistical methods, along with mathematical simulations and own algorithms).
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