Title: Malicious Activity Detection in Encrypted Network Traffic, a Homomorphic Encryption Method
Department: HMS Labs
Size: 1-4 students
Scope: Security, Data mining, Edge computing
Description: There is an increasing need for cyber security while preserving user privacy. Nowadays, more and more data are encrypted, which makes it challenging to monitor network activities. Since the data are encrypted, how a security software can see what is going on in the network, what information is being transferred, by who, etc. However, there are ways such as homomorphic encryption that allow us to gain knowledge out of encrypted data without revealing the actual private information.
The goal of this thesis is to develop a solution to mine data on encrypted data.
The project should consider the below criteria :
- Study state-of-the-art in homomorphic encryption, Edge computing, Data mining,
- High efficiency and real-time response is a key point,
- Security of deployed application in terms of authenticity and integrity
- Develop a Cloud-based management application for the solution is a bonus.
The project and scope can be adjusted to the size of the group and the participants.
Prerequisites:
Bachelor or master program within computer science or similar. Experience in a programming environment suitable for cloud and embedded development like Python or Java, and knowledge in cyber security are necessary. General knowledge in C/C++, make, CMake is an advantage.
Contact Person:
Shooresh Sufiye
+46 7220 225 63
shsu@hms.se