Motorola Endowed Chair Professor,
Computer Science, Florida Atlantic University

Security Analytics and Big Data Challenges

Cybercrime now costs trillions of dollars annually. Machine learning can help to detect cyberattacks in big data, but it needs to overcome several challenges to be effective. Like the proverbial “needle in a haystack” analogy, severe class imbalance can cause machine learning classifiers difficulty. To compound this problem further, class rarity is not uncommon where only very few instances are available from the positive class causing classifiers further trouble in being able to discriminate between the classes. We evaluate applying sampling techniques to treat the class imbalance problems for detecting cyberattacks in big data. Properly preprocessing the input data is an important step, and we discuss data quality issues of the input features. Finally, we cover how feature selection can also be helpful for detecting cyberattacks in big data.

Dr. Taghi M. Khoshgoftaar is Motorola Endowed Chair professor of the Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University and the Director of NSF Big Data Training and Research Laboratory. His research interests are in big data analytics, data mining and machine learning, health informatics and bioinformatics, social network mining, security analytics, fraud detection, and software engineering. He has published more than 800 refereed journal and conference papers in these areas. He was the conference chair of the IEEE International Conference on Machine Learning and Applications (ICMLA 2016 and ICMLA 2019). He is the Co-Editor-in Chief of the journal of Big Data. He has served on organizing and technical program committees of various international conferences, symposia, and workshops. Also, he has served as North American Editor of the Software Quality Journal and was on the editorial boards of the journals Multimedia Tools and Applications, Knowledge and Information Systems, and Empirical Software Engineering and is on the editorial boards of the journals Software Quality, Software Engineering and Knowledge Engineering, and Social Network Analysis and Mining. For my selected publications, please see my Google Scholar link below: