Instant messenger is an IM application that allows communication in a secured manner. A secured private IM is needed to ensure data transmission between sender and recipient more secure. This paper presents a secure IM architecture. A secure architecture is divided into four modules; chat module, transceiver module, secure module, and routing module. In this research, hash algorithm was applied in secure module. The main function of hash algorithm is to encrypt and convert into hash value. The purpose of this encryption is to ensure unauthorized person cannot view the original data or information through the network. IM application was developed and tested. The result indicates this architecture and hash algorithm able to improve level of data security.
Abstract-Accurate bus arrival time prediction is a key component for improving the attractiveness of public transport. In this research, a model of bus arrival time prediction, which aims to improve arrival time accuracy, is proposed. The arrival time will be predicted using a Kalman Filter (KF) model, by utilising information acquired from social networks. Social Networks feed road traffic information into the model, based on information provided by people who have witnessed events and then updated their social media accordingly. In order to accurately assess the efficiency of KF model, we simulate realistic road scenarios using the traffic simulator Simulation in Urban Mobility (SUMO). SUMO is capable of simulating real world road traffic using digital maps and realistic traffic models. This paper discusses modelling a road journey using Kalman Filters and verifying the results with a corresponding SUMO simulation. As a second step, SUMO based measures are used to inform the KF model. Integrating the SUMO measures with the KF model can be seen as an initial step to verifying our premise that realtime data from social networks can eventually be used to improve the accuracy of the KF prediction. Furthermore, it demonstrates an integrated experimental environment.
In a perfect condition, there are only normal network traffic and sometimes flash event traffics due to some eye-catching or heartbreaking events. Nevertheless, both events carry legitimate requests and contents to the server. Flash event traffic can be massive and damaging to the availability of the server. However, it can easily be remedied by hardware solutions such as adding extra processing power and memory devices and software solution such as load balancing. In contrast, a collection of illegal traffic requests produced during distributed denial of service (DDoS) attack tries to cause damage to the server and thus is considered as dangerous where prevention, detection and reaction are imminent in case of occurrence. In this paper, the detection of attacks by distinguishing it from legal traffic is of our main concern. Initially, we categorize the parameters involved in the attacks in relation to their entities. Further, we examine different concepts and techniques from information theory and image processing domain that takes the aforementioned parameters as input and in turn decides whether an attack has occurred. In addition to that, we also pointed out the advantages for each technique, as well as any possible weakness for possible future works.
Bioinformatics is combination between biology and informatics. Most of biological data is used by private or government sectors such clinics, hospitals, etc. Web based application is tool to access this biological data. A good methodology or technique is needed to store huge of biological data. In this research, two issues have been identified. First is data integration and second is web query processing. In this paper, technique for data integration and mapping algorithm will propose in order to improve web query processing in bioinformatics. Data integration means integration different data sources and store into a single data source. This single database source will store only important information such a keyword and data source destination. The keyword in data warehouse will match will information enter by web user. Then, a mapping algorithm will map to only relate data source for searching and retrieving process. A simple web based application was developed and tested. Several experiments have been done and results indicates a mapping algorithm and data warehouse approach for data integration able to improve web query processing in bioinformatics in term of time performance.
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