A review on security and privacy issues in E-learning and the MapReduce aproach - Noor Akma, Abu Bakar; Mazlina, Abdul Majid; Khalid, Adam; Kirahman, Ab Razak; Noorhuzaimi@Karimah, Mohd Noor (https://global.uthm.edu.my/icoel2019/proceeding_icoel2019.pdf, 2019)
E-learning is very useful and extensively used nowadays for the learners and teachers in education lines for the process of teaching and learning via an electronic device. E-learning usually uses the network as an access medium, and it is exposing to the threats. Using the Internet leaves indelible tracks, such as log files, cookies and posts and effects on the privacy based on information as well. Therefore, the actions against security incidents increased since network-connected devices. Log files are generated at every level of the computing infrastructure and represent a valuable source of information in detecting attacks. Thus, log files are big volume and velocity needed for the higher in data processing time. The log files are very large and complex structure but required to diagnosing the system security. MapReduce is a promising parallel programming model for processing large data. Then, we proposed e-Learning using MapReduce algorithm in protecting the security and privacy of eLearning. The methodology is started with the literature study, then comparing each result of the previous works and the last part is the result. The description of the proposed solutions discussed. A comparative study on this topic has been done as an approach to focus on the security issues in e-learning. The expected results show that the proposed solution of MapReduce will enhance the security and privacy issues in e-Learning. Furthermore, the result expected can reduce the processing time and more efficient in facing the problems of the logged data, which is a big size in e-Learning