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Register a new userA note on achieving security, robust cheating resistance, and high-efficiency for outsourcing large matrix multiplication computation to a malicious cloud
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Added by
Zhengjun Cao
Publication date
2016
fields
Informatics Engineering
and research's language is
English
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We show that the Lei et al.s scheme [Information Sciences, 280 (2014), 205-217] fails, because the verifying equation does not hold over the infinite field R. For the field R, the computational errors should be considered seriously. We also remark that the incurred communication cost in the scheme could be overtake the computational gain, which makes it somewhat artificial.
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We show that the verifying equations in the scheme [Theoretical Computer Science, 562 (2015), 112-121] cannot filter out some malformed values returned by the malicious servers. We also remark that the two untrusted programs model adopted in the scheme is somewhat artificial, and discuss some reasonable scenarios for outsourcing computations.
Nowadays, machine learning based Automatic Speech Recognition (ASR) technique has widely spread in smartphones, home devices, and public facilities. As convenient as this technology can be, a considerable security issue also raises -- the users speech content might be exposed to malicious ASR monitoring and cause severe privacy leakage. In this work, we propose HASP -- a high-performance security enhancement approach to solve this security issue on mobile devices. Leveraging ASR systems vulnerability to the adversarial examples, HASP is designed to cast human imperceptible adversarial noises to real-time speech and effectively perturb malicious ASR monitoring by increasing the Word Error Rate (WER). To enhance the practical performance on mobile devices, HASP is also optimized for effective adaptation to the human speech characteristics, environmental noises, and mobile computation scenarios. The experiments show that HASP can achieve optimal real-time security enhancement: it can lead an average WER of 84.55% for perturbing the malicious ASR monitoring, and the data processing speed is 15x to 40x faster compared to the state-of-the-art methods. Moreover, HASP can effectively perturb various ASR systems, demonstrating a strong transferability.
With the support of cloud computing, large quantities of data collected from various WSN applications can be managed efficiently. However, maintaining data security and efficiency of data processing in cloud-WSN (C-WSN) are important and challenging issues. In this paper, we present an efficient data outsourcing scheme based on CP-ABE, which can not only guarantee secure data access, but also reduce overall data processing time. In our proposed scheme, a large file is divided into several data blocks by data owner (DO) firstly. Then, the data blocks are encrypted and transferred to the cloud server in parallel. For data receiver (DR), data decryption and data transmission is also processed in parallel. In addition, data integrity can be checked by DR without any master key components. The security analysis shows that the proposed scheme can meet the security requirement of C-WSN. By performance evaluation, it shows that our scheme can dramatically improve data processing efficiency compared to the traditional CP-ABE method.
The complexity of matrix multiplication (hereafter MM) has been intensively studied since 1969, when Strassen surprisingly decreased the exponent 3 in the cubic cost of the straightforward classical MM to log 2 (7) $approx$ 2.8074. Applications to some fundamental problems of Linear Algebra and Computer Science have been immediately recognized, but the researchers in Computer Algebra keep discovering more and more applications even today, with no sign of slowdown. We survey the unfinished history of decreasing the exponent towards its information lower bound 2, recall some important techniques discovered in this process and linked to other fields of computing, reveal sample surprising applications to fast computation of the inner products of two vectors and summation of integers, and discuss the curse of recursion, which separates the progress in fast MM into its most acclaimed and purely theoretical part and into valuable acceleration of MM of feasible sizes. Then, in the second part of our paper, we cover fast MM in realistic symbolic computations and discuss applications and implementation of fast exact matrix multiplication. We first review how most of exact linear algebra can be reduced to matrix multiplication over small finite fields. Then we highlight the differences in the design of approximate and exact implementations of fast MM, taking into account nowadays processor and memory hierarchies. In the concluding section we comment on current perspectives of the study of fast MM.
Cloud computing as a potential paradigm offers tremendous advantages to enterprises. With the cloud computing, the markets entrance time is reduced, computing capabilities is augmented and computing power is really limitless. Usually, to use the full power of cloud computing, cloud users has to rely on external cloud service provider for managing their data. Nevertheless, the management of data and services are probably not fully trustworthy. Hence, data owners are uncomfortable to place their sensitive data outside their own system .i.e., in the cloud. Bringing transparency, trustworthiness and security in the cloud model, in order to fulfill clients requirements are still ongoing. To achieve this goal, our paper introduces two levels security framework: Cloud Service Provider (CSP) and Cloud Service User (CSU). Each level is responsible for a particular task of the security. The CSU level includes a proxy agent and a trust agent, dealing with the first verification. Then a second verification is performed at the CSP level. The framework incorporates a trust model to monitor users behaviors. The use of mobile agents will exploit their intrinsic features such as mobility, deliberate localization and secure communication channel provision. This model aims to protect users sensitive information from other internal or external users and hackers. Moreover, it can detect policy breaches, where the users are notified in order to take necessary actions when malicious access or malicious activity would occur.
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