Compromise-resilient anonymous mutual authentication scheme for n by m-times ubiquitous mobile cloud computing services

Mobile Cloud Computing is a combination of Mobile Computing, Cloud Computing and wireless networks to convey rich computational resources to mobile users, network operators, as well as cloud computing providers. Nowadays, the market of mobile devices and its applications are growing at an alarming speed. In general, single application for a specific purpose is not compatible to different operating systems. So the developer has to develop various versions of application which is compatible to different platforms. In order to overcome the drawback of compatibility and interoperability issues, HTML5-based mobile applications are built by using standard web technologies. HTML5-based mobile applications support same version of application in different platforms, but these applications are vulnerable to attacks because of the data and code being fused together. A new form of Code Injection Attack found in this type of mobile applications inherits the property of XSS attack and also uses many channels to inject malicious code such as Contact, SMS, WIFI, NFC, Barcode etc. This allows the attacker to inject malicious code to exhaust all the resources of the victim. Therefore, security is the major issue which impedes the development of Mobile Cloud Computing. This paper surveys the malicious code injection attacks in Mobile Cloud Computing environment and the possible solutions.

Providing mobile cloud services requires seamless integration between various platforms to offer mobile users optimum performance. To achieve this, many fundamental problems such as bandwidth availability and reliability, resource scarceness, and finite energy must be addressed before rolling out such services. This chapter aims to explore technological challenges for mobile cloud computing in the area of resource management focusing on both parts of the infrastructure: mobile devices and cloud networks. Starting with introducing mobile cloud computing, it then stresses the importance of resource management in the operation of mobile cloud services presenting various types of resources available for cloud computing. Furthermore, it examines the various types of resource management techniques available for mobile clouds. Finally, future directions in the field of resource management for mobile cloud computing environment are presented.

With the proliferation of new mobile devices, mobile cloud computing technology has emerged to provide rich computing and storage functions for mobile users. The explosive growth of mobile data has led to an increased demand for solutions that conserve storage resources. Data deduplication is a promising technique that eliminates data redundancy for storage. For mobile cloud storage services, enabling the deduplication of encrypted data is of vital importance to reduce costs and preserve data confidentiality. However, recently proposed solutions for encrypted deduplication lack the desired level of security and efficiency. In this paper, we propose a novel scheme for serverless efficient encrypted deduplication (SEED) in mobile cloud computing environments. Without the aid of additional servers, SEED ensures confidentiality, data integrity, and collusion resistance for outsourced data. The absence of dedicated servers increases the effectiveness of SEED for mobile cloud storage services, in which user mobility is essential. In addition, noninteractive file encryption with the support of lazy encryption greatly reduces latency in the file-upload process. The proposed indexing structure (D-tree) supports the deduplication algorithm and thus makes SEED much more efficient and scalable. Security and performance analyses prove the efficiency and effectiveness of SEED for mobile cloud storage services.

Identity-based mutual authentication and key agreement (ID-MAKA) between a mobile user and cloud service provider is necessary for accessing any cloud services. In recent years, there are a large number of ID-MAKA schemes had been proposed on mobile cloud computing services to make authentication and accessing process more usability, security, and scalability. In this paper, we propose a new ID-MAKA scheme for mobile cloud computing, which firstly achieves remote biometric-based authentication(remote servers authenticate user’s biometrics), single sign-on (a single credential and single registration for accessing multiple servers) and center-less authentication(the registration center does not participate in the access procedure) in one scheme. In order to realize this target, we design a ZK-token based on ECC and cryptographic hash function, and then artfully employ it to introduce the fuzzy extractor technology and zero-knowledge technology into our scheme. Therefore, the user can access multiple cloud computing servers by registering only once in the registration center, and cloud computing servers can complete the biometric-based remote authentication and key agreement for the user without the registration center participating. In this way, our scheme greatly improves usability, scalability, and security compared to other existing solutions. We give a formal security proof for our scheme by using Real-Or-Random(RoR) model and Burrows-Abadi-Needham (BAN) logic to show that the present scheme is secure and security analysis for other known attacks. Finally, according to the experiment result, our scheme has lower computation and communication cost compared with most existing related schemes.

The widespread use of smartphones and other mobile devices has brought significant changes to the storage requirements of cloud systems, necessitating a reevaluation of security protocols. Mobile Cloud Computing (MCC) is a computing paradigm that combines the capabilities of mobile devices with the flexibility and scalability of cloud computing. MCC allows mobile users to access computational power, storage, and applications over the internet, facilitating resource-intensive tasks such as data analysis, gaming, and multimedia streaming on resource-constrained mobile devices. The integration of mobile and cloud technologies has revolutionized industries such as healthcare, education, and entertainment, offering benefits like enhanced mobility, improved resource utilization, and cost efficiency. Despite its advantages, MCC faces significant security challenges that could undermine user trust and disrupt its adoption. Since mobile devices and cloud servers are connected via insecure networks, malicious actors can exploit vulnerabilities in the system. This paper aims to analyze the primary security issues in MCC technology, focusing on data protection, authentication, access control, and other critical concerns. Unlike other issues, when dealing with business objectives, protection and privacy in financial activities are of paramount importance. This article examines mobile cloud computing, its technological model, and its role in detail. Keywords: Mobile cloud computing, Technology, Privacy issues, Security.

Mobile Cloud Computing (MCC) fuels innovation in Mobile Computing and opens new pathways between mobile devices and infrastructures. There are several issues in MCC environment as it integrates various technologies. Among all issues, security lies on the top where many users are not willing to adopt the cloud services. This paper focuses on the authentication. The objective of this paper is to provide a mechanism for authenticating all the entities involved in accessing the cloud services. A mechanism called Key Based Mutual Authentication (KBMA) is proposed which is divided into two processes namely registration and authentication. Registration is a one-time process where the users are registered for accessing the cloud services by giving the desired unique information. Authentication process is carried out mutually to verify the identities of Device and Cloud Service Provider (CSP). Scyther tool is used for analysing the vulnerability in terms of attacks. The result claims show that the proposed mechanism is resilient against various attacks.

Recent trends in Cloud Computing have further stimulated the popularization of mobile device industry, creating a novel computing paradigm called Mobile Cloud Computing (MCC). MCC takes advantage of the powerful computation and storage capability of cloud servers by offloading heavy computing or storing tasks from mobile devices to cloud servers to keep a thin frontend on the mobile devices. Such benefit is important to MCC leveraging various sensors equipped in modern mobile devices. We explore the sensing capability of MCC and design an application framework that enables a class of exciting mobile applications to be developed in the sensing-oriented MCC environment. A critical issue in such an environment is accountability. We provide a comprehensive analysis of the accountability issues in this new computing context and show how the accountability function is integrated into the application framework.

Mobile cloud computing (MCC) is the availability of cloud computing services in a mobile environment. By providing optimal services for mobile users, MCC incorporates the elements of mobile networks and cloud computing. In mobile cloud computing, all the data and complicated computing modules can be processed in clouds, and mobile devices do not need a powerful configuration like CPU speed, memory capacity, etc. However, the mobile devices are facing up with many struggles in their resources (e.g., battery life, storage, and bandwidth) and communications (e.g., privacy, mobility, and security). These challenges have a significant effect on the improvement of service qualities. In this paper, a literature survey on the MCC and security issues in MCC has presented.

Mobile cloud computing is high technology that extends existing IT capabilities and requirements. And it can also access to shareable remote computing resources pool through the network. As the concept of mobile cloud, many providers have served the mobile cloud services using their own service policies. In other words, there is no formal definition of quality criteria for mobile cloud service evaluation. To solve this problem, some quality models are proposed for cloud service evaluation. However, those did not include many metrics to evaluate the services. Even if the model included a number of criteria, it is difficult to identify whether the metrics are proper or not. Furthermore, most existing models were not concerned about mobile characteristics. Therefore, we propose a cloud service integration model to solve the problem as we mentioned above. First, we select additional metrics to satisfy the mobile characteristics. Second, we present an extended SLA model for modeling complex service-dependencies in mobile cloud services. Third, we describe a method of discovering relations between the metrics of service belonging to mobile cloud services and then using these relations for establishing newly generated SLA.

The combination of Mobile computing and Cloud computing gave rise to a new computing paradigm called Mobile Cloud Computing (MCC) that gives the flexibility to access information and computing resources anywhere anytime. In many applications, mobile nodes capture images/video clips and exchange with other mobile peers (on demand) and use local access points for efficient smooth distribution of information in the wireless network. In such a situation, a three-way data management and dissemination technique is helpful because it provides both data management and distribution at different levels of granularity. The main motivation of this paper is that we seek a balance between accessing information from a remote cloud server, at the cost of increasing latency, and accessing data from other mobile hosts, at a cost of power, bandwidth and increased traffic. To manage this balance, we propose a layered architecture supported by mobile hosts, access points and cloud together for efficiency. The MCC architecture described in this paper also provides fault tolerance in case one of the mobile nodes fails or gets disconnected. In this paper, we discuss a layered architecture for MCC and present a data pre-distribution scheme for efficient sharing of data among potential users in MCC environment. We also propose update propagation and cache replacement policies in MCC. In addition, we also report complexity analysis for cache accesses by mobile nodes using the proposed architecture in terms of communication messages.

Cloud computing is an emerging technology in modern society. In recent years mobile users and cloud service providers are increased rapidly. In the cloud or any other distributed environment, if the users increased then security risks also increase parallelly. Many security problems are still unclear even after the advanced security measures have been taken. Security of stored data in the server is one of the most challenging issues in the cloud-based environment. Only authorized users should access the stored data of the server. Authentication plays a significant role in providing authorization. Therefore, in cloud computing, authentication is the primary measure to protect the data and the server from an unauthorized user. In this paper, an efficient authentication scheme using the smart card in the cloud environment is proposed. In the proposed scheme, with the help of a single private key, the user can access many cloud services. Also, the proposed scheme resists all security attacks. Through the simulation using the AVISPA tool, it is proved that the proposed scheme is robust and suitable for practical implementation.

Mobile cloud is the infrastructure that facilitates the offloading of storage and computing resources of mobile devices pertaining mobile applications to cloud computing. Mobile devices can run expensive applications using mobile cloud as they can outsource services to cloud while providing interface for mobile users. Emerging mobile applications that are expensive can overcome the inherent problems of hand held devices through the concept of mobile cloud computing. The offloading process provide mobiles a rich platform for pervasive computing with on-demand services linked to cloud computing through mobile cloud infrastructure. Thus the mobile cloud computing is an inevitable phenomenon which bring about plethora of pros besides the mobility. The mobile cloud users can perform their resource intensive operations on the fly without time and geographical restrictions. In spite of the advantages it bestows mobile cloud computing has its own security issues. This paper throws light into the security issues and solutions in terms of secure channels transmission in mobile cloud computing. In this paper, we present state-of-the-art of mobile cloud computing besides its security aspects that are to be taken care of for successful mobile cloud computing.

The rapid development of information & communication technology has led to the wide popularity of mobile devices, which have helped to improve business efficiency and enabled simple mobility as small and light devices and convenience of being available anytime, anywhere for cyber-physical-social big data. There are many ongoing studies on mobile cloud computing (MCC) to overcome the limited computing capability and storage capacity and internal battery limitation by taking advantage of the popularity of mobile devices for the processing cyber-physical-social big data. MCC consists of service-oriented architecture, agent-client architecture, and collaborative architecture, with job splitting and allocation as the critical factor. As such, job allocation techniques considering the performance resources of mobile devices have been studied. Note, however, that there is a problem of job reallocation due to continuous battery consumption, since the studies consider only the performance resources of mobile devices at the time of job allocation or take into account the performance resources and remaining battery power only. This paper proposes the job allocation mechanism (JAM) for battery consumption minimization of cyber-physical-social big data processing in MCC, which continuously reflects the battery consumption rate to process jobs with mobile devices only without an external cloud server in a collaborative architecture-based MCC environment. JAM allocates jobs considering the periodic measurement of battery consumption and surplus resource to minimize the problem of job reallocation due to battery rundown of the mobile devices. This paper designs and implements a system for verifying JAM and demonstrated that the job processing speed increased in an MCC environment for cyber-physical-social big data.

Computation offloading frameworks partition an application's execution between a cloud server and the mobile device to minimize its completion time on the mobile device. An important component of an offloading framework is the partitioning algorithm that decides which tasks to execute on mobile device or cloud server. The partitioning algorithm schedules tasks of a mobile application for execution either on mobile device or cloud server to minimize the application finish time. Most offloading frameworks partition parallel applications devices using an optimization solver which takes a lot of time. We show that by allowing duplicate execution of selected tasks on both the mobile device and the remote cloud server, a polynomial algorithm exists to determine a schedule that minimizes the completion time. We use simulation on both random data and traces to show the savings in both finish time and scheduling time over existing approaches. Our trace-driven simulation on benchmark applications shows that our algorithm reduces the scheduling time by 8 times compared to a standard optimization solver while guaranteeing minimum makespan.

The popularity of mobile devices has been growing at a very fast rate and it is evident from the fact that it is possessed by almost each and every person and some may have even more than a single mobile device. MCC helps in computation and running of various complex applications on the mobile device and also offloads to the cloud when it requires lot of resources for computation or storage purposes. However, as energy is limited in the mobile device, processing of complex applications using big data is a challenge that needs to be addressed using energy efficient architectures. In this work, we mainly focuses on identifying energy-aware issues for handling big data in Mobile Cloud Computing (MCC) environment and their current solutions. Also, we have included the review of few techniques available to handle big data in mobile devices. This chapter will also include a brief discussion of techniques available to process big data in MCC in an energy efficient manner. Finally, we conclude with an analysis of identified issues for handling big data in MCC and future scope of research.