Efficient TPA-based auditing scheme for secure cloud storage

In recent years, how to design efficient auditing protocol to verify the integrity of users’ data, which is stored in cloud services provider (CSP), becomes a research focus. Homomorphic message authentication code (MAC) and homomorphic signature are two popular techniques to respectively design private and public auditing protocols. On the one hand, it is not suitable for the homomorphic-MAC-based auditing protocols to be outsourced to third-party auditor (TPA), who has more professional knowledge and computational abilities, although they have high efficiencies. On the other hand, the homomorphic-signature-based ones are very suitable for employing TPA without compromising user’s signing key but have very low efficiency (compared to the former case). In this paper, we propose a new auditing protocol, which perfectly combines the advantages of above two cases. In particular, it is almost as efficient as a homomorphic-MAC-based protocol proposed by Zhang et al. recently. Moreover, it is also suitable for outsourcing to TPA because it does not compromise the privacy of users’ signing key, which can be seen from our security analysis. Finally, numerical analysis and experimental results demonstrate the high-efficiency of our protocol.

     

MHB*T based dynamic data integrity auditing in cloud storage

Cluster Computing - Integrity audit technology is proposed to protect data in remote cloud servers from being tampered with. However, the challenge is that the computational complexity is too large...     

Enabling secure auditing and deduplicating data without owner-relationship exposure in cloud storage

The public cloud storage auditing with deduplication has been studied to assure the data integrity and improve the storage efficiency for cloud storage in recent years. The cloud, however, has to store the link between the file and its data owners to support the valid data downloading in previous schemes. From this file-owner link, the cloud server can identify which users own the same file. It might expose the sensitive relationship among data owners of this multi-owners file, which seriously harms the data owners’ privacy. To address this problem, we propose an identity-protected secure auditing and deduplicating data scheme in this paper. In the proposed scheme, the cloud cannot learn any useful information on the relationship of data owners. Different from existing schemes, the cloud does not need to store the file-owner link for supporting valid data downloading. Instead, when the user downloads the file, he only needs to anonymously submit a credential to the cloud, and can download the file only if this credential is valid. Except this main contribution, our scheme has the following advantages over existing schemes. First, the proposed scheme achieves the constant storage, that is, the storage space is fully independent of the number of the data owners possessing the same file. Second, the proposed scheme achieves the constant computation. Only the first uploader needs to generate the authenticator for each file block, while subsequent owners do not need to generate it any longer. As a result, our scheme greatly reduces the storage overhead of the cloud and the computation overhead of data owners. The security analysis and experimental results show that our scheme is secure and efficient.     

A novel task scheduling approach based on dynamic queues and hybrid meta-heuristic algorithms for cloud computing environment

Task scheduling is one of the most challenging aspects to improve the overall performance of cloud computing and optimize cloud utilization and Quality of Service (QoS). This paper focuses on Task Scheduling optimization using a novel approach based on Dynamic dispatch Queues (TSDQ) and hybrid meta-heuristic algorithms. We propose two hybrid meta-heuristic algorithms, the first one using Fuzzy Logic with Particle Swarm Optimization algorithm (TSDQ-FLPSO), the second one using Simulated Annealing with Particle Swarm Optimization algorithm (TSDQ-SAPSO). Several experiments have been carried out based on an open source simulator (CloudSim) using synthetic and real data sets from real systems. The experimental results demonstrate the effectiveness of the proposed approach and the optimal results is provided using TSDQ-FLPSO compared to TSDQ-SAPSO and other existing scheduling algorithms especially in a high dimensional problem. The TSDQ-FLPSO algorithm shows a great advantage in terms of waiting time, queue length, makespan, cost, resource utilization, degree of imbalance, and load balancing.     

A flexible fine-grained dynamic access control approach for cloud computing environment

Cluster Computing - As a pioneering surge of ICT technologies, offering computing resources on-demand, the exceptional evolution of Cloud computing has not gone unnoticed by the IT world. At the...     

Energy and resource efficient workflow scheduling in a virtualized cloud environment

High energy consumption (EC) is one of the leading and interesting issue in the cloud environment. The optimization of EC is generally related to scheduling problem. Optimum scheduling strategy is used to select the resources or tasks in such a way that system performance is not violated while minimizing EC and maximizing resource utilization (RU). This paper presents a task scheduling model for scheduling the tasks on virtual machines (VMs). The objective of the proposed model is to minimize EC, maximize RU, and minimize workflow makespan while preserving the task’s deadline and dependency constraints. An energy and resource efficient workflow scheduling algorithm (ERES) is proposed to schedule the workflow tasks to the VMs and dynamically deploy/un-deploy the VMs based on the workflow task’s requirements. An energy model is presented to compute the EC of the servers. Double threshold policy is used to perceive the server’ status i.e. overloaded/underloaded or normal. To balance the workload on the overloaded/underloaded servers, live VM migration strategy is used. To check the effectiveness of the proposed algorithm, exhaustive simulation experiments are conducted. The proposed algorithm is compared with power efficient scheduling and VM consolidation (PESVMC) algorithm on the accounts of RU, energy efficiency and task makespan. Further, the results are also verified in the real cloud environment. The results demonstrate the effectiveness of the proposed ERES algorithm.

     

STACRP: a secure trusted auction oriented clustering based routing protocol for MANET

In mobile ad hoc network?(MANET) nodes have a tendency to drop others’ packet to conserve its own energy. If most of the nodes in a network start to behave in this way, either a portion of the network would be isolated or total network functionality would be hampered. This behavior is known as selfishness. Therefore, selfishness mitigation and enforcing cooperation between nodes is very important to increase the availability of nodes and overall throughput and to achieve the robustness of the network. Both credit and reputation based mechanisms are used to attract nodes to forward others’ packets. In light of this, we propose a game theoretic routing model, Secure Trusted Auction oriented Clustering based Routing Protocol (STACRP), to provide trusted framework for MANET. Two auction mechanisms procurement and Dutch are used to determine the forwarding cost-per-hop for intermediate nodes. Our model is lightweight in terms of computational and communication requirements, yet powerful in terms of flexibility in managing trust between nodes of heterogeneous deployments. It manages trust locally with minimal overhead in terms of extra messages. STACRP organizes the network into 1-hop disjoint clusters and elects the most qualified and trustworthy nodes as Clusterhead. The trust is quantified with carefully chosen parameters having deep impact on network functionality. The trust model is analyzed using Markov chain and is proven as continuous time Markov chain. The security analysis of the model is analyzed to guarantee that the proposed approach achieves a secure reliable routing solution for MANETs. The proposed model have been evaluated with a set of simulations that show STACRP detects selfish nodes and enforces cooperation between nodes and achieves better throughput and packet delivery ratio with lees routing overhead compare to AODV.     

An efficient and reproducible protocol for production of AFLP markers in tree genomes using fluorescent capillary detection

An optimized protocol for the development and discovery of polymorphic AFLP markers in tree species is described. The protocol was optimized for the production of fluorescently labeled PCR products and analysis using a capillary sequencer. This approach has been demonstrated to be efficient and reproducible for tree species with complex genomes. The most important modification was in the selective amplification step. Instead of using a traditional step down PCR, a fixed and higher annealing temperature was employed, improving the reproducibility and sensitivity of the protocol. The levels of polymorphisms detected with the optimized protocol on three woody species are in agreement with those previously reported in the literature for tree species.     

An intelligent trust sensing scheme with metaheuristic based secure routing protocol for Internet of Things

Cluster Computing - The Internet of Things (IoT) defines the network of physical objects, commonly used to interconnect and communicate with other devices through the internet. Security is highly...     

A convenient and efficient protocol for isolating high-quality RNA from latex of Hevea brasiliensis (para rubber tree)

Isolating high-quality RNA from latex of H. brasiliensis is a prerequisite to elucidating the molecular mechanisms of rubber biosynthesis and its regulation. Here, an improved protocol was developed for latex collection, transportation, storage, and RNA isolation. Compared with existing ones, our protocol eliminated liquid nitrogen for latex collection and subsequent low-temperature (− 70 °C) condition for latex storage, making it more convenient and feasible when latex was collected in remote sampling sites, and latex storage and RNA isolation were conducted in poorly-equipped laboratories. Different methods (UV absorbance scans, denaturing gel electrophoresis, autoradiograph monitoring of cDNA synthesis) were used to confirm the high quality of the RNA prepared with this protocol, whose usefulness was further verified by several practical applications, including construction of one high-quality cDNA library, cloning of the full-length cDNAs of 3 novel Hevea sucrose transporter genes, and semi-quantitative RT-PCR analysis of two rubber-biosynthesis essential genes and one sucrose transporter gene.     

A convenient and efficient protocol for isolating high-quality RNA from latex of Hevea brasiliensis (para rubber tree)

Isolating high-quality RNA from latex of H. brasiliensis is a prerequisite to elucidating the molecular mechanisms of rubber biosynthesis and its regulation. Here, an improved protocol was developed for latex collection, transportation, storage, and RNA isolation. Compared with existing ones, our protocol eliminated liquid nitrogen for latex collection and subsequent low-temperature (-70 degrees C) condition for latex storage, making it more convenient and feasible when latex was collected in remote sampling sites, and latex storage and RNA isolation were conducted in poorly-equipped laboratories. Different methods (UV absorbance scans, denaturing gel electrophoresis, autoradiograph monitoring of cDNA synthesis) were used to confirm the high quality of the RNA prepared with this protocol, whose usefulness was further verified by several practical applications, including construction of one high-quality cDNA library, cloning of the full-length cDNAs of 3 novel Hevea sucrose transporter genes, and semi-quantitative RT-PCR analysis of two rubber-biosynthesis essential genes and one sucrose transporter gene.     

Blockchain based secure,efficient and coordinated energy trading and data sharing between electric vehicles

Cluster Computing - In this study, a secure and coordinated blockchain based energy trading system for Electric Vehicles (EVs) is presented. The major goals of this study are to provide secure and...     

PEDAL: a dynamic analysis tool for efficient concurrency bug reproduction in big data environment

Concurrency bugs usually manifest under very rare conditions, and reproducing such bugs can be a challenging task. To reproduce concurrency bugs with a given input, one would have to explore the vast interleaving space, searching for erroneous schedules. The challenges are compounded in a big data environment. This paper explores the topic of concurrency bug reproduction using runtime data. We approach the concurrency testing and bug reproduction problem differently from existing literature, by emphasizing on the preemptable synchronization points. In our approach, a light-weight profiler is implemented to monitor program runs, and collect synchronization points where thread scheduler could intervene and make scheduling decisions. Traces containing important synchronization API calls and shared memory accesses are recorded and analyzed. Based on the preemptable synchronization points, we build a reduced preemption set (RPS) to narrow down the search space for erroneous schedules. We implement an optimized preemption-bounded schedule search algorithm and an RPS directed search algorithm, in order to reproduce concurrency bugs more efficiently. Those schedule exploration algorithms are integrated into our prototype, Profile directed Event driven Dynamic AnaLysis (PEDAL). The runtime data consisting of synchronization points is used as a source of feedback for PEDAL. To demonstrate utility, we evaluate the performance of PEDAL against those of two systematic concurrency testing tools. The findings demonstrate that PEDAL can detect concurrency bugs more quickly with given inputs, and consuming less memory. To prove its scalability in a big data environment, we use PEDAL to analyze several real concurrency bugs in large scale multithread programs, namely: Apache, and MySQL.     

Simplified and efficient DNA extraction protocol for Meliolaceae specimens

Meliolaceae is an obligate biotrophic fungal family which cannot be cultured in artificial media. This has resulted in a lack of DNA sequence data in public databases to better resolve species taxonomy. The main criterion for specific classification, therefore, relied heavily on host association. Fresh collections from living leaves of Croton persimilis and Tamarindus indica with black colonies in Mae Fah Luang University, Thailand yielded a new species, Irenopsis crotonicola sp. nov., and a new record of Meliola tamarindi. These taxa are described and phenotypic comparisons are made with known species. To better classify the putative novel species that cannot be cultivated, we outline the protocol to extract DNA from fruiting bodies and generate new phylogenetic data. The results indicate that this direct DNA extraction method is suitable to yield quality DNA sufficient for polymerase chain reaction (PCR) amplifications of several commonly used DNA regions in fungal systematics. The 28S rDNA phylogram generated confirms the position of our taxa within Meliolaceae and indicate a close relationship of I. crotonicola sp. nov. to I. walsurae. Sequences of tef, β-tubulin, and GPDH regions of Meliolaceae are provided as well.     

OPSA: an optimized prediction based scheduling approach for scientific applications in cloud environment

Cluster Computing - Cloud computing has attracted scientists to deploy scientific applications by offering services such as Infrastructure-as-a-service (IaaS), Software-as-a-service (SaaS), and...     

An effective meta-heuristic based multi-objective hybrid optimization method for workflow scheduling in cloud computing environment

Cluster Computing - Cloud computing is an emerging distributed computing model that offers computational capability over internet. Cloud provides a huge level collection of powerful and scalable...     

SHARE-ABE: an efficient and secure data sharing framework based on ciphertext-policy attribute-based encryption and Fog computing

Attribute-based encryption (ABE) is an access control mechanism that ensures efficient data sharing among dynamic groups of users by setting up access structures indicating who can access what. However, ABE suffers from expensive computation and privacy issues in resource-constrained environments such as IoT devices. In this paper, we present SHARE-ABE, a novel collaborative approach for preserving privacy that is built on top of Ciphertext-Policy Attribute-Based Encryption (CP-ABE). Our approach uses Fog computing to outsource the most laborious decryption operations to Fog nodes. The latter collaborate to partially decrypt the data using an original and efficient chained architecture. Additionally, our approach preserves the privacy of the access policy by introducing false attributes. Furthermore, we introduce a new construction of a collaboration attribute that allows users within the same group to combine their attributes while satisfying the access policy. Experiments and analyses of the security properties demonstrate that the proposed scheme is secure and efficient especially for resource-constrained IoT devices.