A threshold authenticated encryption scheme using hybrid problems

In this paper, we propose a threshold authenticated encryption scheme using both factoring and discrete logarithm problems.We apply the concept of threshold cryptography in the verification and message recovery phase, where t out of n recipients are required to verify and recover the message. Security analysis shows that our scheme will remain secure even if one of these problems can be solved

A Review on the Role of Big Data Analytics in the Financial Services Industry

The financial services industry's digital revolution has facilitated the penetration and transformation of advanced analytics, machine learning, artificial intelligence, big data, and the cloud. These technologies are used by large organisations to expedite digital transformation, meet consumer demand, and improve profit and loss. While the majority of organisations hold enormous amounts of useful data, they typically lack the knowledge essential to maximise its value because the data is unstructured or incorrectly recorded inside the organisation. This article discusses the applications of Big Data Analytics in the financial services industry and how they are being employed. Text analytics, audio analytics, and predictive analytics are just a few of the approaches now being used to provide value to financial organisations. This can assist in resolving various critical issues in the field, including market forecasting, fraud detection, credit scoring, real-time targeted marketing, and overall customer experience enhancement

An insight into internship program for undergraduate Arabic language learners in Malaysia

This study attempts to investigate the outcome of the internship training program in the Department of Arabic Language and Literature, at the International Islamic University Malaysia (IIUM). Methodologically, this study was conducted to gather the opinions and experience on the internship program among Arabic language and literature students. The participants were purposively selected from 57 out of 66 students who have completed their three months internship program either in the public or private sector from July to September 2015 by using an online survey and open-ended questionnaire. General findings from this study show that internship training has essentially improved their soft skills and increased their workplace literacy and well-being. Despite the poor perception of Arabic language in the mutual graduate employability as well as its practicality aspects and job market by the industry, Arabic language and literature students are well accepted in both private and public sectors to undertake their internship training as reported in this article. In conclusion, internship training is crucial, particularly among Arabic language and literature students as it enriches their experiences, knowledge and skills in both their personal and social life. It also increased their level of confidence to explore their future opportunity in the Malaysian job market including setting up their own businesses through entrepreneurship knowledge and skil

RSA authentication mechanisms in control grid computing environment using Gridsim toolkit

There are security concerns when our sensitive data is placed in the third party infrastructure such as in the Grid Computing environment. As such, it is difficult to be assured that our data is in the safe hands.Thus, authentication has become the most critical factor pertaining to this.There are several approaches has been discussed in the grid computing environment on the safeguard, scalable and efficient authentication that are either Virtual Organization centric or Resource centric.Most of the grid computing uses public key infrastructure (PKI) to secure the identification, but the vulnerability are still cannot be avoid. In order to satisfy the security need of grid computing environment, we design an alternative authentication mechanism using RSA algorithm to ensure the user identification, and carry out the experiment in the Gridsim toolkit simulator

Systematic literature review: factor for physical security and access control in maximun security protection

Physical security and access control as one of the installations should be upgraded to confirm the security and readiness of the asset belong to the group to continue safely. As the quick development in technology offers a boundless defence level for physical security and access control in the office, every organization must offer a passable budget pertinent to the transformation of the world today. Through a very humane approach of natural surveillance, access control, maintenance, and reinforcements of territory, this strategy will contribute to the field of physical security as a whole. The purpose of this paper is to recognize the features that regulate taking for perimeter protection and access control in maximum were identified and analysed. The findings have revealed that five categories of features can be used to study the taking for perimeter protection and access control in maximum security protection: physical security; access control; security standard and policy; security awareness program and security training and security protection. A Systematic Literature Review (SLR) was accepted since it uses a more rigorous and well-defined method to swotting the study indication pertinent to the study. Initially, 62 papers were retrieved by a manual search in six databases and 17 primary studies were finally included. Consequently, 5 factors education

Data Quality in Big Data: A Review

Abstract The Data Warehousing Institute (TDWI) estimates that data quality problems cost U.S. businesses more than $600 billion a year. The problem with data is that its quality quickly degenerates over time. Experts say 2 percent of records in a customer file become obsolete in one month because customers die, divorce, marry, and move. In addition, data entry errors, system migrations, and changes in source systems, among other things, generate bucket loads of errors. More complex, as organizations fragment into different divisions and units, interpretations of data elements change to meet the local business needs. However, there are several ways that the Company should concern, such as to treat data as a strategic corporate resource; develop a program for managing data quality with a commitment from the top; and hire, train, or outsource experienced data quality professionals to oversee and carry out the program. The Organizations can sustain a commitment to managing data quality over time and adjust monitoring and cleansing processes to changes in the business and underlying systems by using the Commercial data quality tools. Data is a vital resource. Companies that invest proportionally to manage this resource will stand a stronger chance of succeeding in today's competitive global economy than those that squander this critical resource by neglecting to ensure adequate levels of quality. This paper reviews the characteristics of big data quality and the managing processes that are involved in it

Visual analytics with decision tree on network traffic flow for botnet detection

Visual analytics (VA) is an integral approach combining visualization, human factors, and data analysis. VA can synthesize information and derive insight from massive, dynamic, ambiguous and often conflicting data. Thus, help discover the expected and unexpected information. Moreover, the visualization could support the assessment in a timely period on which pre-emptive action can be taken. This paper discusses the implementation of visual analytics with decision tree model on network traffic flow for botnet detection. The discussion covers scenarios based on workstation, network traffic ranges and times. The experiment consists of data modeling, analytics and visualization using Microsoft PowerBI platform. Five different VA with different scenario for botnet detection is examined and analysis. From the studies, it may provide visual analytics as flexible approach for botnet detection on network traffic flow by being able to add more information related to botnet, increase path for data exploration and increase the effectiveness of analytics tool. Moreover, learning the pattern of communication and identified which is a normal behavior and abnormal behavior will be vital for security visual analyst as a future reference

Data analysis using MapReduce in Hadoop environment

Data is growing at every moment which makes it almost impossible to process all of it. More than a decade ago, researchers from big company in IT industry such as Google and Yahoo introduce Hadoop and MapReduce as a solution for big volume of data processing. Now, by running on a free and open platform both method had gain popularity among the industry and academicians in the academic world. Thus, this paper will use MapReduce method in Hadoop environment and apply it on a sample dataset as a way to analyse the given data. The purpose of study is to gain understanding of using MapReduce in Hadoop environment

A hybrid prediction model for energy-efficient data collection in wireless sensor networks

Energy consumption because of unnecessary data transmission is a significant problem over wireless sensor networks (WSNs). Dealing with this problem leads to increasing the lifetime of any network and improved network feasibility for real time applications. Building on this, energy-efficient data collection is becoming a necessary requirement for WSN applications comprising of low powered sensing devices. In these applications, data clustering and prediction methods that utilize symmetry correlations in the sensor data can be used for reducing the energy consumption of sensor nodes for persistent data collection. In this work, a hybrid model based on decision tree (DT), autoregressive integrated moving average (ARIMA), and Kalman filtering (KF) methods is proposed to predict the data sampling requirement of sensor nodes to reduce unnecessary data transmission. To perform data sampling predictions in the WSNs efficiently, clustering and data aggregation to each cluster head are utilized, mainly to reduce the processing overheads generating the prediction model. Simulation experiments, comparisons, and performance evaluations conducted in various cases show that the forecasting accuracy of our approach can outperform existing Gaussian and probabilistic based models to provide better energy efficiency due to reducing the number of packet transmissions

Programme standards: medical and health sciences

This document, The Programme Standards: Medical and Health Sciences (the Programme Standards), contains benchmarked statements pertaining to the field of medical and health sciences. The complex multidisciplinary nature of medical and health science requires a sound, research-informed, scientific education. Graduates must acquire sufficient knowledge, understanding, skills and professionalism that underpin the education and training of health professionals. They should be aware of the current approaches used in health care and research. They are encouraged to integrate the knowledge of various key disciplines to further understand their respective fields. These objectives can be achieved by incorporating professional standards within the programme