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YouTube has become a popular social media among the users. Due to YouTube popularity, it became a platform for spammer to distribute spam through the comments on YouTube. This has become a concern because spam can lead to phishing attack which the target can be any user that click any malicious link. Spam has its own features that can be analyzed and detected by classification. Hence, enhancement features are proposed to detect YouTube spam. In order to conduct the experiments, a YouTube Spam detection framework that consists of five (5) phases such as data collection, pre-processing, features selection and extraction, classification and detection were developed. This paper, proposed the YouTube detection framework, examined and validate each of the phases by using two types of data mining tool. The features are constructed from analysis by using data collected from YouTube Spam dataset by using Naïve Bayes and Logistic Regression and tested in two different data mining tools which is Weka and Rapid Miner. From the analysis, thirteen (13) features that had been tested on Weka and RapidMiner shows high accuracy, hence is being used throughout the experiment in this research. Result of Naïve Bayes and Logistic Regression run in Weka is slightly higher than RapidMiner. In addition, result of Naïve Bayes is higher than Logistic Regression with 87.21% and 85.29% respectively in Weka. While in RapidMiner there is slightly different of accuracy between Naïve Bayes and Logistic Regression 80.41% and 80.88%. But, precision of Naïve Bayes is higher than Logistic Regression.

Numerous non-profit driven establishments depend on volunteers to help achieve their administrative targets. Despite the fact that volunteers work side-by-side or now and again substitute representatives in delivering services, inputting volunteer work into non-profit ventures of delivering services presents remarkable difficulties. Understanding these difficulties provides a significant fundamental building step in comprehending the influence these challenges have on service developmental plans and operations when utilizing volunteers. In this study, the paper brings forward a Charity Fundraising Information System (CFIS) framework and presents the modelling and evaluation of a plan and operational variables applicable to volunteer fulfilment in non-profit driven organizations. Discoveries indicate that fulfilled volunteers are bound to stay longer with the same establishment, give monetarily to the non-profit driven organization, and prescribe the volunteer involvement to other people. Every one of these results guarantees the continuous sustenance of the non-profit driven establishment.

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Purpose -Information security has become an essential entity for organizations across the globe to eliminate the possible risks in their organizations by conducting information security risk assessment (ISRA). However, the existence of numerous different types of risk assessment methods, standards, guidelines and specifications readily available causes the organizations to face the daunting tasks in determining the most suitable method that would augur well in meeting their needs. Therefore, to overcome this tedious process, this paper suggests collective information structure model for ISRA. Design/methodology/approach -The proposed ISRA model was developed by deploying a questionnaire using close-ended questions administrated to a group of information security practitioners in Malaysia (N ϭ 80). The purpose of the survey was to strengthen and add more relevant additional features to the existing framework, as it was developed based on secondary data. Findings -Previous comparative and analyzed studies reveals that all the six types of ISRA methodologies have features of the same kind of information with a slight difference in form. Therefore, questionnaires were designed to insert additional features to the research framework. All the additional features chosen were based on high frequency of more than half percentage agreed responses from respondents. The analyses results inspire in generating a collective information structure model which more practical in the real environment of the workplace.The authors would like to thank University Tun Hussien Onn Malaysia (UTHM) for supporting this research. The authors would also like to thank SIRIM QAS, CyberSecurity and all the Information Security Practitioners for their support. Practical implications -Generally, organizations need to make comparisons between methodologies and decide on the best due to the inexistence of agreed reference benchmark in ISRA methodologies. This tedious process leads to unwarranted time, money and energy consumption. Originality/value -The collective information structure model for ISRA aims to assist organizations in getting a general view of ISRA flow and gathering information on the requirements to be met before risk assessment can be conducted successfully. This model can be conveniently used by organizations to complete all the required planning as well as to select the suitable methods to complete the ISRA.Keywords Risk assessment, Collective information structure, Info-structure, Information security, Information security risk assessment (ISRA)Paper type Research paper IntroductionInformation security has drawn attention from researchers, professionals, journalists, legislators, governments and citizens to raise awareness among organizations to invest in information security for decision-making and for the continuance of high-standard business operations (Jourdan et al., 2010). Hence, regardless of being government, private or public organizations, most of them are currently applying a range of security counter measures,...

Message Service (SMS) Spam is one form of mobile device attack that can affect mobile user’s security and privacy. This study developed a Malay SMS Spam detection framework specifically for Malay language. The paper discusses about the spam word detection using keywords filtering technique and security question to enable authorized user reset password when forgot the password. The development of the detection tool is done using the Object Oriented Methodology (OOM). There are four phases in OOM which is Requirement Phase, Analysis Phase, Design Phase and Coding Phase. This detection tool is then further analyzed to evaluate the functionality. This project also compares the existing tool to know the lack of current existing tool. Most of the existing spam tools are capable of identifying English text-based messages but there are close to none to filter the Malay language text-based SMS spam. It is expected that the developed tool is able to detect the SMS spam by using keywords filtering technique in Malay language.

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