Desta Haileselassie Hagos

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Desta Haileselassie Hagos

Ph.D. started in: 2015
Expected year of graduation: 2019
COINS consortium member: University of Oslo
Supervised by: Paal Engelstad, Øivind Kure
Links: CristinDBLP
Research area: Network Security
Project title: Machine Learning Techniques for Computer Security Attack Analysis
Project description: As computer and network systems have become more dynamic and complex over the years, chances for attackers to compromise security flaws in these systems have also increased. Several traditional Intrusion Detection Systems (IDS) use a signature-based approach in which network events are detected and compared against a predefined database of signatures of known attacks. One of the main limitations of this approach is the failure of detecting and identifying novel computer attacks that do not have known signatures. Machine learning techniques have the potential of detecting novel attacks in traffic by being trained on normal and abnormal traffics. The main goal of this project is to introduce broadly useful, innovative, and open technologies and methodologies for security analysis in computer networks. It will introduce new challenges in the implementation of advanced machine learning models for computer security attack analysis.

Publications:

  1. Desta Haileselassie Hagos, Anis Yazidi, Øivind Kure, Paal E. Engelstad (2017). Enhancing security attacks analysis using regularized machine learning techniques
  2. Desta Haileselassie Hagos (2016). Software-defined networking for scalable cloud-based services to improve system performance of hadoop-based big data applications
  3. Desta Haileselassie Hagos (2015). The performance of network-controlled mobile data offloading from LTE to WiFi networks
Events attended with COINS funding:
  1. COINS Ph.D. student seminar, Bergen, Norway, 2016
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