The increasing volume of encrypted network traffic yields a clutter for hackers to use encryption
to spread their malicious software on the network. We study the problem of detecting TLS-…

Implementing traditional machine learning models and neural networks has become trivial
in detecting malicious network traffic and has sparked interest in many researchers …

Since the advent of technology, securely transferring data between two computers over the
internet has been a difficult task. This is especially true for organizations and universities who …

The recent proliferation of programmable network equipment has opened up new possibilities
for embedding intelligence into the data plane. Deploying models directly in the data …

It is now possible to run per-packet Machine Learning (ML) inference tasks in the data plane
at line-rate with dedicated hardware in programmable network switches. We refer to this …

Feature extraction is critical for TLS traffic analysis using machine learning techniques, which
it is also very difficult and time-consuming requiring huge engineering efforts. We designed …

Even before the spread of the COVID-19 pandemic, student loan debttotaling over $1.64
trillion-was a cause for concern, as it is the second largest source of consumer debt in the …

Tutkimuksessa tiivistyy eri menetelmiä haittaohjelmien havaitsemiseen ja analysointiin
käyttäen koneoppimismenetelmiä. Tutkimus toteutettiin, sillä haittaohjelman uhriksi voi nykyään …