* ICSE 2018 *
Sun 27 May - Sun 3 June 2018 Gothenburg, Sweden
Mon 28 May 2018 11:30 - 12:00 at R26 - Big Data Chair(s): Jaco Geldenhuys

Malicious software, commonly known as malware are constantly getting smarter with the capabilities of undergoing self-modifications. They are produced in big numbers and widely deployed very fast through the Internet-capable devices. This is therefore as a big data problem and remains challenging in the research community. Existing detection methods should be enhanced in order to effectively deal with today’s malware. In this paper, we discuss a novel real-time monitoring, analysis and detection solution that is achieved by applying big data analytics and machine learning in the development of a general detection model. The learnings achieved through big data render machine learning more efficient. Using the deep learning approach, we designed and developed a scalable detection model that brings improvement to the existing model. Our experiments achieved an accuracy of 97% and ROC of 0.99.

Mon 28 May

11:00 - 12:30: SEiA - Big Data at R26
Chair(s): Jaco GeldenhuysUniversity of Stellenbosch, South Africa
seia-2018-papers11:00 - 11:30
seia-2018-papers11:30 - 12:00
Emmanuel Masabo, Swaib Kyanda KaawaaseMakerere University, Julianne Sansa OtimMakerere University
seia-2018-papers12:00 - 12:30
Andrew LukyamuziMbarara University of Science and Technology, Uganda