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With recent advances of information and communication technology, smart city has been emerged as a new paradigm to dynamically optimize the resources in cities and provide better facilities and quality of life for the citizens. Smart cities involve a variety of components, including ubiquitous sensing devices, heterogeneous networks, large-scale databases, and powerful data centers to collect, transfer, store, and intelligently process real-time information. Smart cities can offer new applications and services for augmenting the daily life of citizens on making decisions, energy consumption, transportation, health-care, and education. Despite the potential vision of smart cities, security and privacy issues remain to be carefully addressed. This paper delineates a comprehensive survey of security and privacy issues of smart cities, and presents a basis for categorizing the present and future developments within this area. It also presents a thematic taxonomy of security and privacy issues of smart cities to highlight the security requirements for designing a secure smart city, identify the existing security and privacy solutions, and present open research issues and challenges of security and privacy in smart cities.

Even though the cloud paradigm and its associated services has been adopted in various enterprise applications, there has been major issues with regard to authenticating users' critical data. Single Sign on (SSO) is a user authentication technique through which a server authenticates and allows a user to use a single aspect of login credentials, for example, to access multiple services in the cloud. Even though SSO reduces the number of logins that are needed over heterogeneous environments, the risk that might be associated with the security of SSO might be detrimental if, for example, a Man-in-the Middle (MITM) attacker manages to gain control of the SSO credentials. It is also possible to get the identity of the users who have logged into Active Directory or intranet and this identity can easily be used to log into other web-based applications, and this requires the use of the Security Assertion Mark-up Language (SAML). SAML is basically a standard that allows users to be logged into applications as per their sessions. The problem that this paper addresses is the lack of a proactive technique of hardening cloud-based SAML while combining SSO with a Multi-Factor Authentication (MFA) at the time of writing this paper. The authors have, therefore, proposed an effective approach that unifies SSO with MFA in this context. Based on the base score index conducted over Common Vulnerability Scoring System (CVSS), the architecture proves to be reliable, feasible and with better performance.

Cloud computing has arisen as the mainstream platform of utility computing paradigm that offers reliable and robust infrastructure for storing data remotely, and provides on demand applications and services. Currently, establishments that produce huge volume of sensitive data, leverage data outsourcing to reduce the burden of local data storage and maintenance. The outsourced data, however, in the cloud are not always trustworthy because of the inadequacy of physical control over the data for data owners. To better streamline this issue, scientists have now focused on relieving the security threats by designing remote data checking (RDC) techniques. However, the majority of these techniques are inapplicable to big data storage due to incurring huge computation cost on the user and cloud sides. Such schemes in existence suffer from data dynamicity problem from two sides. First, they are only applicable for static archive data and are not subject to audit the dynamic outsourced data. Second, although, some of the existence methods are able to support dynamic data update, increasing the number of update operations impose high computation and communication cost on the auditor due to maintenance of data structure, i.e., merkle hash tree. This paper presents an efficient RDC method on the basis of algebraic properties of the outsourced files in cloud computing, which inflicts the least computation and communication cost. The main contribution of this paper is to present a new data structure, called Divide and Conquer Table (D&CT), which proficiently supports dynamic data for normal file sizes. Moreover, this data structure empowers our method to be applicable for large-scale data storage with minimum computation cost. The one-way analysis of variance shows that there are significant differences between the proposed method and the existing methods in terms of the computation and communication cost on the auditor and cloud.

Fog computing has emerged as an attractive solution to the distributed application of the Internet of Things, and could provide low-latency, highly mobile, and geo-distributed services distinguished from the cloud. While fog computing offers numerous benefits, it also faces various security challenges, of which access control is one of the fundamental requirements since it is concerned with authorizing users to access resources in the open fog environment. This article provides a comprehensive survey of access control of users' data in the environment of fog computing with the aim of highlighting security problems and challenges. It discusses the definition, architecture, and characteristics of fog computing, based on which typical requirements and essential models of access control are addressed. Finally, it highlights known access control schemes in the environment of fog computing, and identifies existing unresolved problems as future directions.

Cloud computing is currently emerging quickly as a client-server technology structure and, currently, providing distributed service applications. However, given the availability of a diverse range of wireless access technologies, people expect continuous connection to the most suitable technology that matches price affordability and performance goals. Among the main challenges of modern communication is the accessibility to wireless networks using mobile devices, with a high service quality (QoS) based on preferences of the users. Past literatures contain several heuristic approaches that use simplified rules to look for the best network that is available. Nevertheless, attributes of mobile devices need algorithms that are quick and effective in order to select best available network near real-time. This study proposes a hybrid intelligent handover decision algorithm primarily founded on two main heuristic algorithms: Artificial Bee Colony or ABC as well as Particle Swarm Optimization or PSO named ABC-PSO to select best wireless network during vertical handover process. The ABC-PSO algorithm has been optimized to achieve small cost function that are powered using the IEEE 802.21 standard taking into account different available wireless networks, the application requirements and the user preferences to improve QoS. Numerical results demonstrate that the ABC-PSO algorithm compared to the related work has lower cost and delay, higher available bandwidth and less number of handover.

With the thriving growth of the cloud computing, the security and privacy concerns of outsourcing data have been increasing dramatically. However, because of delegating the management of data to an untrusted cloud server in data outsourcing process, the data access control has been recognized as a challenging issue in cloud storage systems. One of the preeminent technologies to control data access in cloud computing is Attribute-based Encryption (ABE) as a cryptographic primitive, which establishes the decryption ability on the basis of a users attributes. This paper provides a comprehensive survey on attribute-based access control schemes and compares each schemes functionality and characteristic. We also present a thematic taxonomy of attribute-based approaches based on significant parameters, such as access control mode, architecture, revocation mode, revocation method, revocation issue, and revocation controller. The paper reviews the state-of-the-art ABE methods and categorizes them into three main classes, such as centralized, decentralized, and hierarchal, based on their architectures. We also analyzed the different ABE techniques to ascertain the advantages and disadvantages, the significance and requirements, and identifies the research gaps. Finally, the paper presents open issues and challenges for further investigations. Studying the fundamental of ABE cryptosystem based on different criteria.Taxonomizing the ABE access control in cloud computing.Analysing the existing techniques critically based on taxonomy to identify the gaps.Identifying open issues and challenges of the existing ABE access control techniques.

Cloud computing has emerged as a new computing paradigm that offers great potential for storing data remotely. Presently, many organizations have reduced the burden of local data storage and maintenance by outsourcing data storage to the cloud. However, integrity and security of the outsourced data continues to be a matter of major concern for data owners due to the lack of control and physical possession over the data. To deal with this problem, researchers have proposed remote data auditing (RDA) techniques. However, the majority of existing RDA techniques is only applicable for static archived data and is not applicable for auditing or dynamically updating the outsourced data. They are also not applicable to big data storage because of the high computational overhead on the auditor. In this paper, we propose an efficient RDA technique based on algebraic signature properties for a cloud storage system that incurs minimum computational and communication costs. We also present the design of a new data structure-Divide and Conquer Table (DCT)—that can efficiently support dynamic data operations such as append, insert, modify, and delete. Our proposed data structure can be applied for large-scale data storage and will incur minimum computational cost. A comparison between our proposed method and other state-of-the-art RDA techniques shows that our method is secure and highly efficient in reducing the computational and communication costs on the server and the auditor.

Cloud computing has emerged as a popular computing model to process data and execute computationally intensive applications in a pay-as-you-go manner. Due to the ever-increasing demand for cloud-based applications, it is becoming difficult to efficiently allocate resources according to user requests while satisfying the service-level agreement between service providers and consumers. Furthermore, cloud resource heterogeneity, the unpredictable nature of workload, and the diversified objectives of cloud actors further complicate resource allocation in the cloud computing environment. Consequently, both the industry and academia have commenced substantial research efforts to efficiently handle the aforementioned multifaceted challenges with cloud resource allocation. The lack of a comprehensive review covering the resource allocation aspects of optimization objectives, design approaches, optimization methods, target resources, and instance types has motivated a review of existing cloud resource allocation schemes. In this paper, current state-of-the-art cloud resource allocation schemes are extensively reviewed to highlight their strengths and weaknesses. Moreover, a thematic taxonomy is presented based on resource allocation optimization objectives to classify the existing literature. The cloud resource allocation schemes are analyzed based on the thematic taxonomy to highlight the commonalities and deviations among them. Finally, several opportunities are suggested for the design of optimal resource allocation schemes.

Smart city has been emerged as a new paradigm to dynamically optimize the resources in cities and provide better facilities and quality of life for the citizens. Despite the potential vision of smart cities, security and privacy issues remain to be carefully addressed. In this paper, we present a comprehensive survey of security and privacy issues of smart cities, and categorize the present and future developments within this area. We also describe a thematic taxonomy of security and privacy issues of smart cities to highlight the requirements for designing a secure smart city, identify the existing security and privacy solutions, and present open research issues and challenges of security and privacy in smart cities.

In Mobile Cloud Computing (MCC), migrating an application processing to the cloud data centers enables the execution of resource-intensive applications on the mobile devices. However, the resource-intensive migration approaches and the intrinsic limitations of the wireless medium impede the applications from attaining optimal performance in the cloud. Hence, executing the application with low cost, minimal overhead, and non-obtrusive migration is a challenging research area. This paper presents the state-of-the-art mobile application execution frameworks and provides the readers a discussion on the optimization strategies that facilitate attaining the effective design, efficient deployment, and application migration with optimal performance in MCC. We highlight the significance of optimizing the application performance by providing real-life scenarios requiring the effective design, efficient deployment, and optimal application execution in MCC. The paper also presents cloud-based mobile application-related taxonomies. Moreover, we compare the application execution frameworks on the basis of significant optimization parameters that affect performance of the applications and mobile devices in MCC. We also discuss the future research directions for optimizing the application in MCC. Finally, we conclude the paper by highlighting the key contributions and possible research directions in cloud-based mobile application optimization.

Cloud computing has emerged as a long-dreamt vision of the utility computing paradigm that provides reliable and resilient infrastructure for users to remotely store data and use on-demand applications and services. Currently, many individuals and organizations mitigate the burden of local data storage and reduce the maintenance cost by outsourcing data to the cloud. However, the outsourced data is not always trustworthy due to the loss of physical control and possession over the data. As a result, many scholars have concentrated on relieving the security threats of the outsourced data by designing the Remote Data Auditing (RDA) technique as a new concept to enable public auditability for the stored data in the cloud. The RDA is a useful technique to check the reliability and integrity of data outsourced to a single or distributed servers. This is because all of the RDA techniques for single cloud servers are unable to support data recovery; such techniques are complemented with redundant storage mechanisms. The article also reviews techniques of remote data auditing more comprehensively in the domain of the distributed clouds in conjunction with the presentation of classifying ongoing developments within this specified area. The thematic taxonomy of the distributed storage auditing is presented based on significant parameters, such as scheme nature, security pattern, objective functions, auditing mode, update mode, cryptography model, and dynamic data structure. The more recent remote auditing approaches, which have not gained considerable attention in distributed cloud environments, are also critically analyzed and further categorized into three different classes, namely, replication based, erasure coding based, and network coding based, to present a taxonomy. This survey also aims to investigate similarities and differences of such a framework on the basis of the thematic taxonomy to diagnose significant and explore major outstanding issues.

Man-At-The-End (MATE) attacks and fortifications are difficult to analyze, model, and evaluate predominantly for three reasons: firstly, the attacker is human and, therefore, utilizes motivation, creativity, and ingenuity. Secondly, the attacker has limitless and authorized access to the target. Thirdly, all major protections stand up to a determined attacker till a certain period of time. Digital assets range from business to personal use, from consumer devices to home networks, the public Internet, the cloud, and the Internet of Things - where traditional computer and network security are inadequate to address MATE attacks. MATE is fundamentally a hard problem. Much of the extant focus to deal with MATE attacks is purely technical; though security is more than just a technical issue. The main objective of the paper is to mitigate the consequences of MATE attacks through the human element of security and highlight the need for this element to form a part of a holistic security strategy alongside the necessary techniques and technologies. This paper contributes by taking software protection (SP) research to a new realm of challenges. Moreover, the paper elaborates the concept of MATE attacks, the different forms, and the analysis of MATE versus insider threats to present a thematic taxonomy of a MATE attack. The ensuing paper also highlights the fundamental concept of digital assets, and the core protection mechanisms and their qualitative comparison against MATE attacks. Finally, we present state-of-the-art trends and cutting-edge future research directions by taking into account only the human aspects for young researchers and professionals.

Cloud computing has emerged as a computational paradigm and an alternative to the conventional computing with the aim of providing reliable, resilient infrastructure, and with high quality of services for cloud users in both academic and business environments. However, the outsourced data in the cloud and the computation results are not always trustworthy because of the lack of physical possession and control over the data for data owners as a result of using to virtualization, replication and migration techniques. Since that the security protection the threats to outsourced data have become a very challenging and potentially formidable task in cloud computing, many researchers have focused on ameliorating this problem and enabling public auditability for cloud data storage security using remote data auditing (RDA) techniques. This paper presents a comprehensive survey on the remote data storage auditing in single cloud server domain and presents taxonomy of RDA approaches. The objective of this paper is to highlight issues and challenges to current RDA protocols in the cloud and the mobile cloud computing. We discuss the thematic taxonomy of RDA based on significant parameters such as security requirements, security metrics, security level, auditing mode, and update mode. The state-of-the-art RDA approaches that have not received much coverage in the literature are also critically analyzed and classified into three groups of provable data possession, proof of retrievability, and proof of ownership to present a taxonomy. It also investigates similarities and differences in such framework and discusses open research issues as the future directions in RDA research.

Vehicular networking has become a significant research area due to its specific features and applications such as standardization, efficient traffic management, road safety and infotainment. Vehicles are expected to carry relatively more communication systems, on board computing facilities, storage and increased sensing power. Hence, several technologies have been deployed to maintain and promote Intelligent Transportation Systems (ITS). Recently, a number of solutions were proposed to address the challenges and issues of vehicular networks. Vehicular Cloud Computing (VCC) is one of the solutions. VCC is a new hybrid technology that has a remarkable impact on traffic management and road safety by instantly using vehicular resources, such as computing, storage and internet for decision making. This paper presents the state-of-the-art survey of vehicular cloud computing. Moreover, we present a taxonomy for vehicular cloud in which special attention has been devoted to the extensive applications, cloud formations, key management, inter cloud communication systems, and broad aspects of privacy and security issues. Through an extensive review of the literature, we design an architecture for VCC, itemize the properties required in vehicular cloud that support this model. We compare this mechanism with normal Cloud Computing (CC) and discuss open research issues and future directions. By reviewing and analyzing literature, we found that VCC is a technologically feasible and economically viable technological shifting paradigm for converging intelligent vehicular networks towards autonomous traffic, vehicle control and perception systems.

During the last decade, researchers and developers have been attracted to Vehicular Ad-hoc Network (VANET) research area due to its significant applications, including efficient traffic management, road safety, and entertainment. Several resources such as communication, on-board unit, storage, computing, and endless battery are embedded in the vehicles, which are used for enhancing Intelligent Transportation Systems (ITSs). One of the crucial challenges for VANETs is to securely share an important information among vehicles. In some cases, the data owner is also not available and unable to control the data sharing process, i.e., sharing data with a new user or revoking the existing user. In this paper, we present a new method to address the data sharing problem and delegate the management of data to a Trusted Third Party (TPA) based on bilinear pairing technique. To achieve this goal, we use a cloud computing, as the mainstream platform of utility computing paradigm, to store the huge amount of data and perform the re-encryption process securely.

This article has been retracted at the request of the Editor-in-Chief due to excessive overlap with the publication authored by the same authors and entitled “Towards Dynamic Remote Data Auditing in Computational Clouds” in The Scientific World Journal, Hindawi Publishing Corporation Volume 2014, Article ID 269357, 12 pages http://dx.doi.org/10.1155/2014/269357 The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy .

Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA) techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.