Rapid growth and usage of Android smartphones worldwide have attracted many attackers to exploit them. Currently, the attackers used mobile malware to attack victims’ smartphones to steal confidential information such as username and password. The attacks are also motivated based on profit and money. The attacks come in different ways, such as via audio, image, GPS location, SMS and call logs in the smartphones. Hence, this paper presents a new mobile malware classification for audio exploitation. This classification is beneficial as an input or database to detect the mobile malware attacks. System calls and permissions for audio exploitation have been extracted by using static and dynamic analyses using open source tools and freeware in a controlled lab environment. The testing was conducted by using Drebin dataset as the training dataset and 500 anonymous apps from Google Play store as the testing dataset. The experiment results showed that 2% suspicious malicious apps matched with the proposed classification. The finding of this paper can be used as guidance and reference for other researchers with the same interest.

Knowledge Management System (KMS) is widely deployed as organizations acknowledged the importance to manage critical knowledge efficiently in secure manner. More over the community of practice (CoP) benefit the growing of Internet by constructing a collaborative KMS for better communication. However while the excitement of expanding the KMS capabilities, some security issues exist which regard to the restriction of the access permission to knowledge, such as unauthorized access, losing and misusing critical knowledge and about other knowledge processing. Therefore, the paper reviews the criteria of access control model (ACM) because it is a competent security model to overcome the security issues by considering the characteristics of collaborative system. Consequently, this paper formulates a model of collaborative KMS access control. The proposed model can be a guidance to study further the member of ACM family particularly the role based access control (RBAC) towards secure collaborative KMS.

Malay heritage carvings were heavily influenced by Hindu-Buddhist culture before the dissemination of Islam. This is evidenced by the paintings of mythical animals and floral motifs found on archaeological objects in Lembah Bujang. The arrival of Islam in Malaya in the 14th century finally brought great changes in the world of carving, including in Terengganu and Kelantan. This study aimed to identify the initial motifs used after the dissemination of Islam in Malaya. The states of Kelantan and Terengganu were chosen because most of the old houses and skilled woodcarvers were born there and are famous for their various carving motifs. Fourteen houses identified as heritage houses were selected. The carvings on 12 houses in Kelantan and Terengganu were based on measured drawings at the Center for Malay Studies (KALAM) UTM, Skudai. A heritage house was then selected as the ideal sample of the 14 heritage houses selected to identify the initial motifs used after the dissemination of Islam. Two famous woodcarvers were interviewed on the aspect of motif selection. The study focused on some components of the house with many carved motifs such as on walls and ventilation panels. The carving motifs were studied for their importance in terms of motif selection and placement. The results of this study found that there are four types of motifs that are often chosen after the dissemination of Islam in Malaya which are flora, fauna, calligraphy and geometry motifs. It is hoped that this study can contribute to the search for Malaysia identity in the context of history and heritage.

This paper introduces a new approach in countermeasuring XML signature wrapping attack called the Spatial Signature Algorithm (SSA). The motivation for proposing the SSA approach is due to the limitation of the SOAP (Simple Object Access Protocol) in handling the XML signature wrapping attacks. A different strategy is to be planned in order to deter such attack without extensive computational expense. Spatial Signature Algorithm builds upon the notion of ratio signature that is recommended by a research in biotechnology. The research suggests the possibility of diagnosing a specific disease based on the idea of ratios, specifically on the comparative relationship between elements to detect the emergence of certain threats. Bridging this notion to security, the principle of using space and ratio to detect abnormality is extended to the application of spatial information and digital signature to detect and combat the XML wrapping signature attack.

Currently, cyber threats and attacks become a main concern among Internet users. To detect and prevent new and unknown attacks, an intelligent intrusion prevention system (IPS) which is better compared with traditional systems is needed. Furthermore, the Next Generation Intrusion Prevention System (NIGPS) is more suitable that could provide an intelligent IPS solution for new and unknown attacks. Therefore, this paper presents the limitation of traditional IPS systems, a comparison between IPS and NIGPS and proposes an enhanced model for NIGPS.