Denial of Service (DOS) and (DDOS) Distributed Denial of Service attacks have become a major security threat to university campus network security since most of the students and teachers prepare online services such as enrolment, grading system, library etc. Therefore, the issue of network security has become a priority to university campus network management. Using online services in university network can be easily compromised. However, traditional security mechanisms approach such as Defense-In-Depth (DID) Model is outdated in today’s complex network and DID Model has been used as a primary cybersecurity defense model in the university campus network today. However, university administration should realize that Defense-In-Depth (DID) are playing an increasingly limited role in DOS/DDoS protection and this paper brings this fact to light. This paper presents that the Defense-In-Depth (DID) is not capable of defending complex and volatile DOS/DDOS attacks effectively. The test results were presented in this study in order to support our claim. The researchers established a Defense-In-Depth (DID) Network model at the Central Luzon State University and penetrated the Network System using DOS/DDOS attack to simulate the real network scenario. This paper also presents the new approach Defense-through-Deception network security model that improves the traditional passive protection by applying deception techniques to them that give insights into the limitations posed by the Defense-In-Depth (DID) Model. Furthermore, this model is designed to prevent an attacker who has already entered the network from doing damage.

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In today’s fierce telecommunications market competition, customer chum is very severe. In order to retain customers, telecommunications companies have made various attempts from various data and consumption characteristics analysis to big data analysis. However, since the actual situation of customer churn is very complicated, how to predict customer churn accurately and quickly is a difficult problem. After the researchers successfully conducted big data analysis of customer churn and successfully retained customers, in this article, the researchers mainly compared several commonly used algorithms in order to find a better algorithm for big data analysis of telecommunications customer churn. Compare and analyze the accuracy and efficiency of these several algorithms and suggest that the business support staffs of telecommunications companies adopt major methods for big data analysis. The researcher found that the Decision Tree (CART) algorithm is better for the prediction of customer churn and guided other branch staffs to predict customer churn and retain customers in a timely manner. This kind of big data analysis can be used to retain customers in the telecommunications industry.

The gamified e-learning approach has been widely used as a learning and teaching strategy, particularly in higher education. This strategy has been successfully used to engage, motivate and enhance learning performances. However, learners or students react differently to game designs and game mechanics depending on the subject area that a particular gamified application though there are several studies shows that gamification enhances motivation. In this paper, we designed and implemented a specific learning model for the gamified digital logic gates or LogIO. Thus, thirty (30) learners evaluated and we determined how do game design elements affect learners in terms of motivation, performance and learning experience. The main results of this study showed that learners agreed that the motivation level and usability of LogIO have a weighted mean of 4.56 and 4.49 respectively while performance and learning experience level has 81% during the utilization of the gamified mobile application. These results support the significance and relevance of adapting particular design elements for gamified digital logic gates to enhance motivation, performance and learning experience.

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