KEYWORD |
Automatic System for automatic detection of web criptojackers
Thesis in external company
keywords CYBERSECURITY, MACHINE LEARNING, BLOCKCHAIN
Reference persons MARCO MELLIA
External reference persons Stefano Traverso - s.traverso@ermessecurity.com
Research Groups SmartData@PoliTO, Telecommunication Networks Group
Thesis type EXPEIRMENTAL, IN COMPANY
Description While browsing the web, it is easy to step into web crypto-miners or crytojackers, services which exploit users’ hardware to mine cryptocurrencies via Javascript applications running inside the browser. Their activity may severely impair users’ navigation and decrease device performance - especially for mobile phones and tablets. Unfortunately, only little is known about this kind of services, and we lack automatic methodologies to automatically identify and block them.
In this thesis, we are looking for talented students that would like to contribute to the creation of the Ermes Cyber Security solutions, by designing, implementing, and testing automatic tools for automatic identification of web cryptojackers.
Ermes Cyber Security is an innovative startup that offers advanced web-threat protection technologies to help companies protect the navigation of their employees. Ermes Cyber Security is located in the Politecnico di Torino incubator, I3P.
Required skills Excellent programming skills - knowledge of the machine learning fundamentals.
students with average grade higher than 27/30 are preferred.
Notes The thesis will be done in the company, in collaborations with the SmartData@PoliTO center
Deadline 12/11/2019
PROPONI LA TUA CANDIDATURA