The modern vehicles nowadays are managed by networked controllers. Most of the networks were designed with little concern about security which has recently motivated researchers to demonstrate various kinds of attacks against the system. In this paper, we discussed the vulnerabilities of the Controller Area Network (CAN) within invehicle communication protocol along with some potential attacks that could be exploited against it. Besides, we present some of the security solutions proposed in the current state of research in order to overcome the attacks. However, the main goal of this paper is to highlight a holistic approach known as intrusion detection system (IDS) which has been a significant tool in securing networks and information systems over the past decades. To the best of our knowledge, there is no recorded literature on a comprehensive overview of IDS implementation specifically in the CAN bus network system. Thus, we proposed an in-depth investigation of IDS found in the literature based on the following aspects: detection approaches, deployment strategies, attacking techniques, and finally technical challenges. In addition, we also categorized the anomaly-based IDS according to these methods, e.g., frequencybased, machine learning-based, statistical-based, and hybrid-based as part of our contributions. Correspondingly, this study will help to accelerate other researchers to pursue IDS research in the CAN bus system.

Smartphones are becoming more and more popular due to the increase in their processing power, mobility aspect and personal nature. Android is one of the most popular and fully customizable open source mobile platforms that come with a complete software stack. One of the main reasons behind the rapid growth in adoption of smartphones is their capability to facilitate users with third-party applications. Android offers hundreds of thousands of applications via application markets and users can readily install these applications. However, this rapid growth in smartphone usage and the ability to install thirdparty applications has given rise to several security concerns. In this paper, we present the current state of smartphone security mechanisms and their limitations in order to identify certain security requirements for proposing enhancements for the smartphone security model. We analyze the improvements proposed for the basic Android security model and discuss their advantages and limitations in detail. We also present certain security requirements that need to be fulfilled in order to design and implement security enhancements for Android that can be widely adopted by the broader community.

Android has been steadily gaining market share, and the number of available applications is increasing at a healthy pace. Because of the myriad of third‐party applications, privacy concerns are starting to surface in the community. Application developers usually request access to more system resources than are strictly required for their apps. However, the stock Android permission model does not allow users to selectively grant permissions. This is a well‐known issue, but existing solutions to this problem are either too abstract or require detailed changes to the core model—making it difficult for both developers and users to accept them. In this paper, we present a fine‐grained, user‐centric permission model for Android that allows users to selectively grant permissions to applications that they install. Our model allows specification of permissions based on application and system attributes as well as simple yes or no policies. The model is kept as simple as possible, and its open source implementation is highly usable for the average end user. It requires minimal backward compatible changes to the core permission model and is shown to be highly efficient in terms of performance overhead. We present our model and point interested readers to our freely available changeset to help them use, evaluate, and improve our permission model. Copyright © 2014 John Wiley & Sons, Ltd.

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Scientific Data Grid provides geographically distributed resources for large-scale data-intensive applications that generate large scientific data sets and it mostly deals with large computational problems. Research in the area of grid has given various ideas and solutions to address these requirements. However, since the number of participants (scientists and institutes) that involve in this kind of environment is increasing tremendously, scalability, availability and reliability have been the core problem for such system. Peer-to-peer (P2P) is one of the architecture that promising scale and dynamism environment. In this paper, we present a P2P model for Scientific Data Grid that utilizes the P2P services to address those problems. For the purpose of this study, we have developed and used our own data grid simulation written using PARSEC. In this paper, we illustrate our P2P Scientific Data Grid model, our data grid simulation and the design of proposed data replication strategies. We then analyze the performance of data discovery service with and without the existence of replication strategies relative to their success rates, response time, average number of hop and bandwidth consumption. The results from simulation study that show how the proposed replication strategies promote high data availability in the proposed Scientific Data Grid model and how these strategies improve the discovery process are presented.

In modern scientific computing communities, scientists are involved in managing massive amounts of very large data collections in a geographically distributed environment. Research in the area of grid computing has given us various ideas and solutions to address these requirements. Data grid mostly deals with large computational problems and provides geographically distributed resources for large-scale data-intensive applications that generate large data sets. Peer-to-peer (P2P) networks have also become a major research topic over the last few years. In a distributed P2P system, a discovery algorithm is required to locate specific information, applications, or users within the system. In this research work, we present our scientific data grid as a large P2P-based distributed system model. By using this model, we study various discovery algorithms for locating data sets in a data grid system. The algorithms we studied are based on the P2P architecture. We investigate these algorithms using our Grid Simulator developed using PARSEC. In this paper, we illustrate our scientific data grid model and our Grid Simulator. We then analyze the performance of the discovery algorithms relative to their average number of hop, success rates and bandwidth consumption.