Last week I had the opportunity to attend the 1st Transylvanian Deep Learning Summer School (TMLSS). It took place in Cluj, Romania and its main focus was Deep Learning and Reinforcement Learning. Here is the link to website that includes the programme and the full list of lecturers. (link)
Radhika Gupta is a student studying Computer Science at Carnegie Mellon University in Pittsburgh, Pennsylvania, USA. With the Stratosphere team and thanks to the Women in Tech Fund, she was able to attend Hack in Paris and Nuit Du Hack in Paris, France. Here are five things she learned after attending these conferences!
The first edition of RESET cybersecurity conference took place last week in the Kennedy Lecture Theatre of the UCL in London. Hundreds of attendees gathered together to discuss about cyber attacks, threat actors, threat hunting, defence strategies, and more. The event schedule consisted of 8 technical talks, 2 panels, and opening and closing notes. The speaker selection was excellent, with the presence of well known figures such as Wendy Nather, Kim Zetter, and Rebekah Brown.
The Stratosphere IPS is a behavioral-based intrusion detection and prevention system. It uses machine learning algorithms to detect malicious behaviors. In order to do that, we create models based on real malware behaviours to ensure a good accuracy and performance of our IPS. For this reason, in 2015 we started our sister project called 'Malware Capture Facility Project'.
The goal of the NoMaD project is to collect, label, organize and make available a large, verified and labeled dataset of normal and malicious HTTPS connections. This dataset is designed to support the research team at Cisco Prague as well as to support the research activities and publications of the CVUT University. The project will give Cisco Systems an evolving dataset to generate better and faster analysis; and will give the CTU University the opportunity to research about the HTTPSbehaviors in the network as part of its Stratosphere Project.
Some days ago we finally made public two tools that were very important for starting this project. The tools are CCDetector and BotnetDetectorComparer. With these tools we created the experiments in the paper “An empirical comparison of botnet detection methods”. You can download them and use them to verify the paper and test more ideas. Please contact us if you need assistance.