Special session on Machine Learning Techniques and Information security (MLTIS)
Objective and Motivation
With the advancement in using Machine Learning techniques, the capabilities of Information Security techniques to model complex systems and solving more complex problems makes them a useful tool in scientific researches and applications.
Machine learning is being used decades ago in many applications such as medical applications, biometric authentication, image retrieval, and other applications. Since the emerging of the Big Data, obtained from different field such as meteorology, genomics, finance, healthcare, social media and web data, the importance of the machine learning became very crucial for the decision makers.
Optimization can be used in various applications to find the minimal cost, maximal profit, and others. It has a vital role in designing smart/intelligent systems, e.g. recommender systems, search engines, image retrieval/recognition…etc. The advance of these systems requires the development of new optimization techniques to enhance the learning algorithms of the applied machine learning techniques. In general, optimization provide offers a valuable framework for reasoning about, formulating, analyzing, and solving different problems in machine learning.
The aim of this session is to attract researchers and practitioners from academia and industry for exchanging theoretical and practical ideas, and provide a discussion environment in order to share their experiences of the state-of-the-art in Information Security related to machine learning.
Scope and Interests:
Prospective authors are invited to submit their research papers on the topics, but not limited to the following:
- Machine learning and optimization application.
- Using machine learning techniques in big data.
- Feature extraction using machine learning techniques.
- Database and Data Management Security
- Security and Privacy of Mobile/Wireless Systems
- Cloud Computing Security and Resource Management
- Biometrics and Encryption.
- Big Data Analytics and Security.
- Secure Medical Images.
- Business Intelligent and Data Mining Security.
Dr. Kareem Kamal A.GhanyAssistant Professor, Faculty of Computers and Information, Beni-Suef University, Egypt. Email : email@example.com
The scientific Reviewing Committee:
- Kareem Kamal A. Ghany, Faculty of Computers and Information, Beni-Suef University, Egypt. firstname.lastname@example.org
- Mahmood A. Moniem, Institute of Statistical Studies and Research, Cairo University, Egypt. email@example.com
- Marcelo Damasceno de Melo, Federal Institute of Education, Science and Technology of Rio Grande do Norte, Brazil. firstname.lastname@example.org
- Abd El-Aziz Ahmed Abd El-Aziz, Institute of Statistical Studies and Research, Cairo University, Egypt. email@example.com
- Jabar H. Yousif, Sohar University, Sohar, Sultanate of Oman. firstname.lastname@example.org
- Hossam M. Zawbaa, Faculty of Mathematics and Computer Science, Babes-Bolyai University,Romania. email@example.com
- Heba M. Sabri, Sadat Academy for Management Sciences, Egypt. firstname.lastname@example.org
- Heba Ayeldeen, Faculty of Computers & Information, Cairo University, Egypt. email@example.com
- Hesham A. Hefny, Institute of Statistical Studies and Research, Cairo University, Egypt. firstname.lastname@example.org
- Eid Emary, Faculty of Computers & Information, Cairo University, Egypt. email@example.com
Please submit your papers through email to firstname.lastname@example.org
We kindly request that you keep in mind the deadline for papers submissions: July 15, 2015.