ARP Spoof (aka. ARP cache poisoning) is a serious security problem. It can be used for denial of service (DoS) or man in the middle (MITM) attacks. There have been several solutions, proposed to solve this problem. Yet, all of the previous have some critical drawbacks such as infeasibility, unmanageability, high cost, performance penalty and ineffectiveness. Hence, in this paper, we have proposed a new solution, which is feasible, manageable, effective, low cost, platform independent and usable for both small and medium network sizes. A prototyped system, called dynamic ARP-spoof protection & surveillance (DAPS) system has also been implemented and experimented on. The experimental results have demonstrated the favorable features of our solution in comparison to the previous ones.

SSL is a protocol for secured traffic connections. By using the SSL, HTTPS has been designed to prevent eavesdroppers and malicious users from web application services. However, man-in-the-middle attack techniques based on stripping and sniffing the HTTPS connections are still possible, causing security problems on web applications. Several scrip-kiddy tools to launch such attacks are easy to find and available on the Internet. In this paper, we therefore proposed a solution to protect against SSL striping attack. By enforcing a connection to HTTPS, our techniques determine the web URL and enforce the communication to HTTPS for protecting against the SSL striping attack. The experimental results on a test-bed have demonstrated an effectiveness and efficiency of our solution.

Network security is usually protected by a firewall, which checks in-out packets against a set of defined policies or rules. Hence, the overall performance of the firewall generally depends on its rule management. For example, the performance can be decreased when there are firewall rule anomalies. The anomalies may happen when two sets of firewall rules are overlapped or their decision parts are both an acceptance and a denial simultaneously. In this paper, we propose a new paradigm of the firewall design, consisting of two parts: (1) Single Domain Decision firewall (SDD) -a new firewall rule management policy that is certainly not conflicts, and (2) the Binary Tree Firewall (BTF) -a data structure and an algorithm to fast check the firewall rules. Experimental results have indicated that the new design can fix conflicting anomaly and increase the speed of firewall rule checking from O(N²) to O(log₂ N).

To provide VoIP traffic with message authentication and confidentiality, Secure Real Time Protocol (SRTP) and a media keying protocol are needed. SDP Security Description (SDES) is the most widely deployed keying protocol. It also needs Transport Layer Secure (TLS) over the VoIP signal protocol (SIP), known as SIPS. However, from several previous studies, SIPS can be compromised; then cause further problems on SRTP and SDES. So, in this paper, we propose a technique to enhance the SDES protocol to be secure even in the SIP environment without TLS.

Overtaking maneuver on roads without a clear view can cause serious accident. Hence, real-time video streaming deliveries between two vehicles over Vehicular Ad Hoc Networks (VANETs) have been proposed as an overtaking maneuver assistance system. The system is also known as a V2V see-through system since it sends real-time video scenes seeing by a front vehicle to the driver of the back vehicle to help him decide on overtaking maneuver. However, sending real-time video streaming over VANET is still problematic due to delay and packet loss. Several solutions have previously proposed to fix the problems, but all of them still have some drawbacks. So, we propose in this paper a cross-layer optimization of video streams (video frame skipping, video transcoding and frame rate reduction) for overtaking environments. The proposed approach is based on IEEE 802.11 EDCA. Experimental results on our approach using OMNET++ have demonstrated some favorable points, such as bandwidth waste avoidance and acceptable video latency.

Due to the flood of pornographic web sites on the internet, effective Web filtering systems are essential. Web filtering based on content has become one of the important techniques to handle and filter inappropriate information on the web. We examine two machine learning algorithms (support vector machines and Naive Bayes) for pornographic web filtering based on text content. We then focus initially on Thai-language and English-language web sites. In this paper, we aim to investigate whether machine learning algorithms are suitable for web sites classification. The empirical results show that the classifier based support vector machines are more effective for pornographic web filtering than Naive Bayes classifier after testing, especially an effectiveness for the over-blocking problem.