|Project Title||Data Leakage Prevention as a service for Emails|
|H2020 Topic List||Not specified yet|
|Role within the Consortium||* Project Partner|
* Project Coordinator
|Type of activity||* Technology development|
|Project Description||Data Leakage Prevention (DLP) Systems are used to protect the sensitive information from unauthorized |
disclosure .This project mainly involves the use of data fingerprinting in Data Leakage Prevention for emails.
Generally, content-based analysis tools become ineffective if the sensitive data is largely modified. To detect the
sensitive data, data fingerprinting is extensively used. However, traditional fingerprinting can lose track when the
sensitive data is altered or modified, because traditional hashes such as MD5 and SHA1 have the property where a
tiny change to the data being hashed results in totally different fingerprint. A machine learning algorithm such as
Support vector machine , Naïve Bayes, Rule based learning may be used to classify the sensitiveness of an email..
In this project, the effectiveness of ML algorithms in classifying email documents will be studied extensively