Computer Science

In recent times among the multitude of attacks present in network system, DDoS attacks have emerged to be the attacks with the most devastating effects. The main objective of this paper is to propose a system that effectively detects DDoS attacks appearing in any networked system using the clustering technique of data mining followed by classification. This method uses a Heu-ristics Clustering Algorithm (HCA) to cluster the available data and Naïve Bayes (NB) classification to classify the data and detect the attacks created in the system based on some network attributes of the data packet. The clustering algorithm is based in unsupervised learning technique and is sometimes unable to detect some of the attack instances and few normal instances, therefore classification techniques are also used along with clustering to overcome this classification problem and to enhance the accuracy. Naïve Bayes classifiers are based on very strong independence assumptions with fairly simple construction to derive the conditional probability for each relationship. A series of experiment is performed using " The CAIDA UCSD DDoS Attack 2007 Dataset " and " DARPA 2000 Dataset " and the efficiency of the proposed system has been tested based on the following performance parameters: Accuracy , Detection Rate and False Positive Rate and the result obtained from the proposed system has been found that it has enhanced accuracy and detection rate with low false positive rate.

This study aimed to investigate ICT competency of mathematics teachers at secondary schools of Nepal. A cross-sectional survey design was deployed among 336 secondary school teachers of Nepal. The data was analyzed by Mann Whitney U, Kruskal Wallis H, and multiple linear regression. Result showed that teachers' ICT competency level was found to be proficient in the fundamental concept of computers and the use of Internet. In contrast, it was found to be developing-level in software and hardware. Statistically significant results were found in competencies with respect to age, type of school, culture, and district. Additionally, own laptop, Internet use, work experience, knowledge of software and hardware were significant predictors for ICT competency of teachers. The overall findings clarify that ICT enhancement programs are needed for mathematics teachers at secondary schools in Nepal.