An Intelligence Technique For Denial Of Service (Dos) Attack Detection

The emergent damage to computer network keeps increasing due to an extensive and prevalent connectivity on the Internet. Nowadays, attack detection strategies have become the most vital component in computer security despite the main preventive measure in detecting the attacks. The main issue with current detection systems is the inability to detect the malicious activity in certain circumstances. Most of the current intrusion detection systems implemented nowadays depend on expert systems where new attacks are not detectable. Therefore, this paper concern about Denial of Service (DoS) attack, detection using Neural Network. The data used in training and testing was KDD 99 data set based on the Defense Advanced Research Projects Agency (DARPA) intrusion detection programme, which is publicly accessible by Lincoln Labs. Special features of connection records have been acknowledged to be used in DoS attacks. The result from this experiment will show the effectiveness of Neural Network using the backpropagation learning algorithm for detecting DoS attack

Investigation of Security Awareness on e-Learning System Among Lecturers and Students in Higher Education Institution

The advancement of computer and Internet technologies have brought teaching and learning activities to a new dimension. Learners were virtually moved out from their classrooms to a new learning environment where learning contents and materials were delivered electronically. This new environment, which is called e-learning environment uses the web and other Internet technologies to enhance teaching and learning experience. The success and failure of any e-learning system fall on how secure the system is. Security of an e-learning system is very important so that the information contained in the system is not compromised. However no matter how secure an elearning system is the security threats always fall on human factor. Human is identified as the weakest link in information security and lack of security awareness such as password sharing will compromise the security of e-learning system. This paper studies the awareness level in information security among elearning users, particularly students at Higher Education Institution. The study focuses on evaluating awareness level, perception and behavior of e-learning users from International Islamic University Malaysia. Results of this study helps the university authority in preparing effective and specific awareness program in e-learning security for their students

Firewall Redundancy Rules Filtering Using Integrity Rules Checking

Securing your network plays a very crucial role in organizations, institutions, and personal home networks. A firewall is a first network defender that located at the entrance between a private network and the public network. Firewall had this job to monitor the arriving or leaving packet into and from the network, while making a decision whether to give permission or deny the packet based on its rules policy requirements. Commonly, there will be a large of firewall rules set are stored inside the firewall which each packet need to be compared sequentially with filtering until matching rules is found. A new strategy of integrity rules checking is proposed to reduce a firewall rules by analyzing the integrity among the firewall rules relationship to be checked for incoming packet. We believe that the proposed strategy will minimize the firewall rules set and undoubtedly optimize the time of firewall rules filtering