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IEEE International Conference on Ubiquitous computing and Communications

作者： Qiongjie Yao Xiaofei Liao Hai Jin Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781509001552

The stacked autoencoder is a deep learning model that consists of multiple autoencoders. This model has been widely applied in numerous machine learning applications. A significant amount of effort has been made to increase the size of the deep learning model with respect to the size of the training dataset and the parameter of the model to improve performance. However, training a large deep learning model is highly time consuming. Recent studies have applied the CPU cluster with thousands of machines as well as the single GPU or the GPU cluster, to train large scale deep learning models. As a high-performance coprocessor like GPU, the Xeon Phi can be an alternative tool for training large scale deep learning models on a single machine. The Xeon Phi can be recognized as a small cluster which features about 60 cores, and each core supports four hardware threads. Massive parallelism offsets the low computing capacity of every core, but challenges an efficient parallel autoencoders design. In this paper, we analyze the training algorithm of autoencoders based on the matrix operation and point out the thread oversubscription problem, which results in performance degradation. Based on the observation, we propose our map-reduce implementation of autoencoders on the Xeon Phi coprocessor. Our basic idea is to parallelize multiple autoencoder model replicas with bulk synchronous parallel (BSP) communication model where the parameters are updated after the computations of all replicas are completed. Each thread is responsible for one model replica, and all replicas work together on the same mini-batch. This data parallelism method is suitable for training autoencoders on the Xeon Phi, and can extend to asynchronous parallel training method without thread oversubscription. In our experiment the speedup is four times higher than that of sequential implementation. Enlarging the size of the autoencoder model, our method still gets stable speedup.

关键词： Deep Learning Autoencoder Xeon Phi Mapreduce BSP

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Ciphertext-Policy Attribute-Based Encryption with Short Keys

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Chinese Journal of Electronics 2014年第4期23卷 655-660页

作者： XU Peng TANG Yong JIANG Wenbin JIN Hai ZOU Deqing Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology

Ciphertext-policy attribute-based encryption(CP-ABE)allows a user with some attributes to decrypt the ciphertexts associated with these *** several CP-ABE schemes with the constant size ciphertext were proposed to reduce the communication cost,their master public and secret keys still have the size linear in the total number of *** schemes are unpractical for the attribute-scalable and many-attributes scenario.A new CP-ABE scheme is *** attribute is mapped to a mathematical value by a combination *** master public and secret keys of the proposed CP-ABE scheme have the size linear in the binary size of a hash function’s *** has the comparable performance with existing schemes in the aspects like the time costs of encryption and decryption,the expressiveness of access policy and the provable security.

关键词： Ciphertext-policy attribute-based encryption Expressiveness policy Provable security

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Scheme for Ensuring Data Security on Cloud Data Storage in a Semi-trusted Third Party Auditor

Scheme for Ensuring Data Security on Cloud Data Storage in a...

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International Conference on Computer Science and Network Technology

作者： Zaid Alaa Hussien Hai Jin Zaid Ameen Abduljabbar Mohammed Abdulridha Hussain Salah H. Abbdal Deqing Zou Cluster and Grid Computing Lab Big Data Technology and System Lab Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781467381741

Cloud computing is a promising information technology service that allocates and reallocates resources when a client requires virtual data storage and network facility at any time and place. Cloud computing provides large data storage and management services at the lowest cost. Thus, it is crucial for many organizations and clients who seek such services. Data security and integrity are necessary and play important roles. However, these two issues are facing significant challenges. Therefore, a robust scheme is required to ensure security and privacy while transmitting or storing data in the cloud storage environment. We propose an efficient and robust scheme to ensure data security in a semi-trusted third party auditor. Our scheme adopts an advanced encryption standard to support data owner privacy, a cryptography hash function to maintain data owner integrity, and elliptic curve cryptography to ensure data confidentiality, correctness, and security when transmitting data over unsecure channels. A security analysis confirms that our scheme can withstand man-in-the-middle attack and provides data correctness.

关键词： Cloud storage data security elliptic curve cryptography hash function integrity semi-trusted third party auditor Data Security Elliptic curve cryptography cryptography Cloud computing computer information security Data Storage Scheme auditor Third party customers Management services Transmitting Data

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Robust image document authentication code with autonomous biometrie key generation, selection, and updating in cloud environment

Robust image document authentication code with autonomous bi...

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International Symposium on Information Assurance and Security (IAS)

作者： Zaid Ameen Abduljabbar Hai Jin Zaid Alaa Hussien Ali A. Yassin Mohammed Abdulridha Hussain Salah H. Abbdal Deqing Zou Cluster and Grid Computing Lab Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China University of Basrah Basrah Iraq Southern Technical University Basrah Iraq

Recently, security issues are obstructing the development and using of cloud computing services. Authentication and integrity play an important role in the cloud security, and numerous concerns have been raised to recognize any tampering with exchanges of the image document between two entities (sender and receiver) within the cloud environment. However, none of the existing solutions reduce the probability of known attacks by combining cryptographic hash function with a strong factor that should be periodically changed. For this reason, in this paper we propose a robust one-time image document authentication scheme based on combining non-interactive onetime biometric key and a robust wavelet-based cryptographic hashing scheme. The result of the combination is one-time image document authentication code (OMAC). OMAC is hidden in an image document as a cover image through reversible data embedding steganography. The proposed scheme has several important security attributes, such as key agreement, biometric key management, robust OMAC, invulnerability, and efficiency. In biometric key management, key generation, key selection, and key update algorithms are performed autonomously by the sender and the receiver; thus, no interaction between them is needed.

关键词： Authentication Cryptography Biomedical imaging Robustness Receivers Cloud computing

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A Secured Scheme for Geographical Distance Computation over Encrypted Cloud Data

A Secured Scheme for Geographical Distance Computation over ...

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International Conference on Computer Science and Network Technology

作者： Zaid Ameen Abduljabbar Hai Jin Ayad Ibrahim Aqeel Noori Mohammed Abdulridha Hussain Zaid Alaa Hussien Deqing Zou Salah H. Abbdal Cluster and Grid Computing Lab Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China University of Basrah Basrah Iraq

ISBN: (纸本)9781467381741

Popular service providers, such as Google and Amazon, have turned their vast resources into a cloud computing model and enforced their businesses to run applications on the servers of such new model. To ensure security and privacy in this environments, customers have to encrypt their data before uploading them into the cloud servers. Unfortunately, modern unbreakable encryption methods are inadequate because they do not have the ability to execute database queries on the encrypted data. In this paper, we address the problem of how to calculate the geographical distance over an encrypted dataset. Specifically, the data owner, Alice, sends her encrypted dataset of geographical locations into the cloud server. At any time, Bob would like to check the proximity of his submitted query from the locations of Alice. Our proposed scheme enables the untrusted server to perform such task without compromising the privacy of either the dataset of Alice or the query of Bob. Among various distance metrics, we employ the efficient principle of approximate matching to obtain the proximity between query and data locations. Furthermore, we use the inner product similarity to formalize such principle for similarity measurement. Several experiments have been conducted to investigate the overhead and the efficiency of the proposed scheme.

关键词： Cloud computing Privacy preserving Geographical distance Cloud computing Servers distance metric approximate match Dataset CLOUDS Clouds data querying similar measure Uploading Privacy cryptography Geographical Locations

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QoS-Aware Service Selection for Customisable Multi-tenant Service-Based Systems: Maturity and Approaches

QoS-Aware Service Selection for Customisable Multi-tenant Se...

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IEEE International Conference on Cloud computing, CLOUD

作者： Qiang He Jun Han Feifei Chen Yanchun Wang Rajesh Vasa Yun Yang Hai Jin School of Software and Electrical Engineering Swinburne University of Technology Melbourne Australia Services Computing Technology and Systems Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Multi-tenant service-based systems (SBSs) have become a major paradigm in software engineering in the cloud environment. Instead of serving a single end-user, a multitenant SBS provides multiple tenants with similar and yet customised functionalities with potentially different quality-of service (QoS) values. Thus, existing approaches to service selection for single-tenant SBSs are no longer suitable. Furthermore, the target multi-tenancy maturity level also needs to be considered in the service selection approach for an SBS. In this paper, we propose three novel QoS-aware service selection approaches for composing multi-tenant SBSs that achieve three different multi-tenancy maturity levels. Extensive and comprehensive experiments are conducted and the experimental results show that our approaches outperform the existing approach in both effectiveness and efficiency.

关键词： Optimization Engines Throughput Rails Insurance Linear programming

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Energy Minimization for Cellular Network Interfaces with Dynamic Link Quality

Energy Minimization for Cellular Network Interfaces with Dyn...

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International Conference on Computer Communications and Networks (ICCCN)

作者： Xiao Lei Zaiyang Tang Peng Li Hai Jin Song Guo Xiaofei Liao Feng Lu Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Aizu Daigaku Aizuwakamatsu Fukushima JP School of Computer Science and Engineering The University of Aizu Japan

It has been recognized that cellular network interfaces are not energy efficient because of tail energy after each transmission. Although many research efforts have been made to reduce tail energy, they ignore the dynamic of link quality caused by user mobility or network congestion, which would lead to limited improvement without quality-of-experience guarantee. In this paper, we study to minimize energy consumption of the cellular network interface with a sequence of download/upload requests. Given accurate estimation of achievable link rate, we design a dynamic-programming (DP) based algorithm to obtain the optimal solution. Without the knowledge of dynamic link quality and future requests, an online algorithm is proposed to approximate the optimal solution. Finally, we conduct extensive simulations using real traces to evaluate the performance of our proposals, and the results show that 29% energy can be saved by using our algorithm under typical network settings.

关键词： Heuristic algorithms Energy consumption Algorithm design and analysis Network interfaces Bandwidth Minimization Data communication

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Boosting mapreduce with network-aware task assignment 4th

Boosting mapreduce with network-aware task assignment

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4th International Conference on Cloud computing, CloudComp 2013

作者： Xu, Fei Liu, Fangming Zhu, Dekang Jin, Hai Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783319055053

Running MapReduce in a shared cluster has become a recent trend to process large-scale data analytical applications while improving the cluster utilization. However, the network sharing among various applications can make the network bandwidth for MapReduce applications constrained and heterogeneous. This further increases the severity of network hotspots in racks, and makes existing task assignment policies which focus on the data locality no longer effective. To deal with this issue, this paper develops a model to analyze the relationship between job completion time and the assignment of both map and reduce tasks across racks. We further design a network-aware task assignment strategy to shorten the completion time of MapReduce jobs in shared clusters. It integrates two simple yet effective greedy heuristics that minimize the completion time of map phase and reduce phase, respectively. With large-scale simulations driven by Facebook job traces, we demonstrate that the network-aware strategy can shorten the average completion time of MapReduce jobs, as compared to the state-of-the-art task assignment strategies, yet with an acceptable computational overhead. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014.

关键词： MapReduce

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Automatic detection and recognition of silicosis in chest radiograph

Automatic detection and recognition of silicosis in chest ra...

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作者： Zhu, Lei Zheng, Ran Jin, Hai Zhang, Qin Zhang, Wei Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

Silicosis remains one of the most harmful occupational respiratory diseases. It threatens the workers exposed to dust environment. Chest radiograph is the main available image source for silicosis diagnosis according to the diagnostic criteria of pneumoconiosis (DCP). Automatic detection and recognition of silicosis in chest radiograph has great importance on aiding the process of silicosis diagnosis. This paper proposes a multi-scale opacity detection approach to detect all suspected opacities from the chest radiograph. A support vector machine (SVM) based computer-aided silicosis diagnosis is proposed to recognize silicosis opacity from a large amount of candidate regions, and gives processing result for radiologist reference. Comprehensive experiments conducted on real world chest radiographs demonstrate that the proposed approach can reveal changes of silicosis pathology well, and it can be adopted as an effective tool for automatic silicosis diagnosis. © 2014 - IOS Press and the authors.

关键词： Support vector machines

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An Efficient and Robust One-TimeMessage Authentication CodeScheme using Feature Extraction of Iris in Cloud computing

An Efficient and Robust One-TimeMessage Authentication CodeS...

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2014 International Conference on Cloud computing and Internet of Things (CCIOT)(2014年第一届云计算和物联网国际会议)

作者： Mohammed Abdulridha Hussain ZaidAmeen Abduljabbar Deqing Zou Hai Jin Ali A.Yassin ZaidAlaa Hussien Cluster and Grid Computing Lab Services Computing Technology and System Lab School of Computer Scien 1Cluster and Grid Computing Lab Services Computing Technology and System Lab School of Computer Scie University of Basrah BasrahIraq Cluster and Grid Computing Lab Services Computing Technology and System Lab School of Computer Scien

Cloud computing suffers from a number of problems in terms of security *** and integrity play an important role in the security field and numerous concerns have been raised to recognizeor protect any tampering with exchanges of text between two entities(sender and receiver)within the cloud *** schemes in this area can be vulnerable to well known methods of attack such as replay attack,forgery attack,dictionary,insider,and modification attacks.A robust scheme is therefore required to detect or prevent any modification or manipulation of a message during *** this paper,we propose a new message authentication code(MAC)based on feature extraction of the user's iris in order to assure the integrity of the user's *** are extracted from the user's iris to generate a message code for each user's login and to prohibit malicious attacks such as replay,forgery and insider *** proposed scheme enjoysseveral important security attributes such as a user's one time bio-key,robust message anonymity,data integrity for a user's message,phase key agreement,bio-key management,and one time message code for each user's ***,our security analysis and experimental results demonstrate and prove the invulnerability and efficiency of our proposed scheme.

关键词： Cloud computing Iris Features Extraction One Time Bio-key One Tim Message Authentication Code MAC.

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