Sofware Engineer Intership
Clichy, France
The objective of this internship is to develop a robust and adaptive encrypted traffic classification method that overcomes generalization challenges, ensuring reliable results across diverse network conditions.
Deep Packet Inspection (DPI) is a sophisticated network traffic analysis technique that examines the content of packets data to identify specific applications, protocols, or potential threats. It plays a critical role in cybersecurity and traffic intelligence, helping to detect malwares, enforce policies, and optimize network performance.However, the increasing adoption of internet traffic encryption is making traditional signature-based DPI techniques ineffective. To address this challenge, research efforts have shifted towards machine learning-based approaches for classifying encrypted traffic.
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Responsibilities
- Conduct research on existing machine learning techniques for encrypted traffic analysis.
- Develop and implement adaptive machine learning models to improve classification accuracy.
- Test and validate models in various network environments to ensure robustness.
- Collaborate with the R&D team members to integrate solutions into ENEA's products.
Required Skills
- Network Communication Protocols: Familiarity with protocols such as HTTP, SSL, QUIC.
- Programming Languages: Proficiency in C and Python.
- Machine Learning: Knowledge of machine learning techniques and related libraries (scikit-learn, Keras, PyTorch).
- Data Analysis: Experience with data preprocessing, feature extraction, and statistical analysis.
Enea Embedded Security - Deep Packet Inspection Software
Enea Qosmos technology is the de facto industry standard for embedded Deep Packet Inspection (DPI) and Traffic Intelligence in cybersecurity and networking.
Our embedded deep packet inspection and traffic intelligence software products’ classify traffic in real-time and provide granular information about network activities, boosting solution performance from the inside. Available as a next-generation DPI (NG DPI) and classification engine SDK or a standalone high throughput network sensor, they support an extensive range of protocols and applications and deliver detailed network traffic visibility, application awareness, and essential insights into encrypted traffic to cybersecurity and networking solutions such as SSE, SASE, SD-WAN, ZTNA, NGFW, and NDR/XDR
Enea also offers IDS-based threat detection capabilities as an SDK, enabling easy and tight integration with cybersecurity solutions while remaining highly flexible and scalable
About Enea
We are a world-leading specialist in advanced telecom and cybersecurity software with a vision to make the world's communications safer and more efficient.
Our solutions connect, optimize and protect communications between companies, people, devices and things worldwide. We are present in over 80 markets and billions of people rely on our technology every day when they connect to mobile networks or use the Internet.
Enea is headquartered in Stockholm, Sweden and is listed on NASDAQ Stockholm.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Classification Data analysis Keras Machine Learning ML models Python PyTorch R R&D Research Scikit-learn Security Statistics
Perks/benefits: Flex hours
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