Ahmad Noraziah

On cloud computing security issues

The cloud is a next generation platform that provides dynamic resource pools, virtualization, and high availability. The concept of cloud computing is using a virtual centralization. This means, in one part, we have a full control on data and processes in his computer. On the other part, we have the cloud computing where the service and data maintenance is provided by vendors. The client or customers usually unaware about the place where processes are running or the data is stored. So, logically speaking, the client has no control over it. This is the reason cloud computing facing so many security challenge. In this paper, we presented selection issues in cloud computing and focus on the security issues. There are four cloud computing security issues that will be focused, namely XML signature, browser security, cloud integrity and binding issues and flooding attacks. Data security on the cloud side is not only focused on the process of data transmission, but also the system security and data protection for those data stored on the storages of the cloud side. There are some considerations that need to be focused in order to achieve better safe environment in cloud computing such as storage and system protection and data protection. In order to achieve better performance in security, cloud computing needs to fulfill five goals which are availability, confidentiality, data integrity, control and audit. By implementing these goals, we hope data security in cloud computing will be more secure. We also hope that cloud computing will have a bright future with arise of a large number of enterprises and will bring an enormous change in the Internet since it is a low-cost supercomputing to provide services.

Replication techniques in data grid environments

A millions of data has been produce by cross-organizational research and collaborations must be managed, shared and analyzed. Data grid is a useful technique to solve these tasks that applicable to process the large number of data produced by scientific experiments. It also enables an organization to operate and manage distributed resources over the internet as a secure, robust, and flexible infrastructure. Some problems must be considered in managing data grid such as reliability and availability of the data to the user access, network latency, failures or malicious attacks during execution and etc. The replication strategy is the solution to solve these problems that can minimize the time access to the data by creating many replicas and storing replicas in appropriate locations. In this paper, we present some reviews on the existing dynamic replication replacement strategies due to the limited storage used on data grid and also to improve the management of data grid. It is shown that replication techniques able to improve availability and reliability of data, network latency, bandwidth consumption, fault tolerance and etc in data grid environments.

Binary vote assignment on a grid for efficient access of replicated data

Data replication can be used to improve the availability of data in a distributed database system. In such a system, a mechanism is required to maintain the consistency of the replicated data. Grid structure (GS) technique based on quorum is one of the latest solutions for performing this while providing a high availability of the system. It was shown in the previous study, that it still requires a bigger number of copies be made available to construct a quorum. So it is not suitable for the large systems. In this paper, we propose a technique called the binary vote assignment on grid (BVAG) technique by considering only neighbors have the replicated data. In comparison to the GS technique, BVAG requires lower communication cost for an operation, while providing higher data availability, which is preferred for large systems.

Cloud Computing: Analysis of Various Platforms

Cloud computing is fundamentally altering the expectations for how and when computing, storage, and networking resources should be allocated, managed, consumed, and allow users to utilize services globally. Due to the powerful computing and storage, high availability and security, easy accessibility and adaptability, reliable scalability and interoperability, cost and time effective cloud computing is the top, needed for current fast growing business world. A client, organization or a trade that adopting emerging cloud environment can choose a well suitable infrastructure, platform, software, and a network resource, for any business, where each one has some exclusive features and advantages. The authors first develop a comprehensive classification for describing cloud computing architecture. This classification help in survey of several existing cloud computing services developed by various projects globally such as Amazon, Google, Microsoft, Sun and Force.com and by using this survey’s results the authors identified similarities and differences of the architecture approaches of cloud computing.

Prediction of hepatitis prognosis using Support Vector Machines and Wrapper Method

Hepatitis patients are those who need continuous special medical treatment to reduce mortality rate. Using clinical test findings data and machine learning technology such as Support Vector Machines (SVM), the classification and prediction of their life prognosis can be done. However, we cannot pledge that all the features values in the data are correlated to each other. Therefore, we incorporate Wrapper Methods to remove noise features before classification. This study shows the increase in prediction between data by combining feature selection method prior to classification process.

IPMA : indirect patterns mining algorithm

Indirect pattern is considered as valuable and hidden information in transactional database. It represents the property of high dependencies between two items that are rarely occurred together but indirectly appeared via another items. Indirect pattern mining is very important because it can reveal a new knowledge in certain domain applications. Therefore, we propose an Indirect Pattern Mining Algorithm (IPMA) in an attempt to mine the indirect patterns from data repository. IPMA embeds with a measure called Critical Relative Support (CRS) measure rather than the common interesting measures. The result shows that IPMA is successful in generating the indirect patterns with the various threshold values.

E-Visitor Information management System(E-VIMS) using MyKad

Electronic visitor information system (E-VIMS) has been developed to replace traditional visitor registration and visitor information management activities. E-VIMS able to record visitor information during visitor registration by using visitorpsilas Malaysia government multipurpose card (MyKad). The concepts underlying in E-VIMS are MyKad, smart card reader, personal computer/smart card (PC/SC) and data management. This application enables capturing new visiting record by auto-clock in/out, and assignment of visitor pass. Visitor information are recorded in a centralized database server, which provides data management and manipulation through searching and report generating. The benefits of E-VIMS are enhancing the level of security enforced in premises, providing an organized view of visitor records and reducing the time spent on managing visitor information.

Managing transactions on grid-neighbour replication in distributed systems

Managing transactions is very important in distributed databases in order to preserve data consistency and reliability of the systems. This paper presents a new design to manage transactions on neighbour replication in a distributed database system. We address how to build a reliable system for managing transactions on a neighbour replication grid (NRG) in terms to preserve the data consistency and support fault-tolerance. We first recall the model and technique of NRG that impose neighbours binary vote assignment to its logical grid structure on data copies. We extend our work in managing transactions to normal and failure cases. Finally, the implementation of the system is presented.

Improved Parameterless K-Means: Auto-Generation Centroids and Distance Data Point Clusters

Internet has brought a major drift in user community. Apart from its well-known usage, it also promotes social networking. Research on such social networking has advanced significantly in recent years which have been highly influenced by the online social websites. People perceive the web as a social medium that allows larger interaction among people, sharing of knowledge, or experiences. Internet or social web forums act as an agent to reproduce some general information that would benefit the users. A product review by the user is a more accurate representation of its real-world performance and web-forums are generally used to post such reviews. Though commercial review websites allow users to express their opinions in whatever way they feel, the number of reviews that a product receives could be very high. Hence, opinion mining techniques can be used to analyze the user-reviews, classify the content as positive or negative, and thereby find out how the product fares. This paper focuses its attention on providing a recommendation to the products available on the web by analyzing the context to score the sentences for each review by identifying the opinion and feature words using a novel algorithm.

Scalable technique to discover items support from trie data structure

One of the popular and compact trie data structure to represent frequent patterns is via frequent pattern tree (FP-Tree). There are two scanning processes involved in the original database before the FP-Tree can be constructed. One of them is to determine the items support (items and their support) that fulfill minimum support threshold by scanning the entire database. However, if the changes are suddenly occurred in the database, this process must be repeated all over again. In this paper, we introduce a technique called Fast Determination of Item Support Technique (F-DIST) to capture the items support from our proposed Disorder Support Trie Itemset (DOSTrieIT) data structure. Experiments through three UCI benchmark datasets show that the computational time to capture the items support using F-DIST from DOSTrieIT is significantly outperformed the classical FP-Tree technique about 3 orders of magnitude, thus verify its scalability.