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ردیف | عنوان | نوع |
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1 |
Blockchain-based fair payment smart contract for public cloud storage auditing
قرارداد هوشمند پرداخت عادلانه مبتنی بر بلاکچین برای ممیزی ذخیره سازی ابر عمومی-2019 Cloud storage plays an important role in today’s cloud ecosystem. Increasingly clients tend to outsource their data to the cloud. In spite of its copious advantages, integrity has always been a significant issue. The audit method is commonly used to ensure integrity in cloud scenarios. However, traditional auditing schemes expect a third-party auditor (TPA), which is not always available in the real world. Also, the former scheme implies a limited pay- as-you-go service, as it requires the client to pay for the service in advance. In this paper, we aim to address the aforementioned drawback by adopting blockchain to replace TPA and designing a blockchain-based fair payment smart contract for public cloud storage auditing. In our system, data owner and cloud service provider (CSP) will run a blockchain-based smart contract. The contract ensures that the CSP is required to submit data possession proof regularly. The CSP gets paid only if the verification is passed; otherwise, it gets no remuneration but has to pay the penalties. To reduce the number of interactions in the execution of contract, we present the notion of non-interactive public provable data possession and design a blockchain-based smart contract for public cloud storage auditing based on this primitive. Keywords: Blockchain | Smart contract | Public auditing | Fair payment | Cloud storage |
مقاله انگلیسی |
2 |
Privacy-preserving and sparsity-aware location-based prediction method for collaborative recommender systems
روش پیشگویی مبتنی بر مکان حفظ و حفظ حریم خصوصی و کمبود آگاهی برای سیستمهای توصیه گر مشترک-2019 With the rapid growth of public cloud offerings, how to design effective prediction models that
provide appropriate recommendations for potential users has become more and more important. In
dynamic cloud environment, both of user behaviors and service performance are sensitive to contextual
information, such as geographic location information. In addition, the increasing number of attacks
and security threats also brought the problem that how to protect critical information assets such as
sensitive data, cloud resources and communication in a more effective and secure manner. In view
of these challenges, we propose a privacy-preserving and sparsity-aware location-based prediction
method for collaborative recommender systems. Specifically, our method is designed as a three-phase
process: Firstly, two privacy-preserving mechanisms, i.e., a randomized data obfuscation technique and
a region aggregation strategy are presented to protect the private information of users and deal with
the data sparsity problem. Then a location-aware latent factor model based on tensor factorization
is applied to explore the spatial similarity relationships between services. Finally, predictions are
made based on both global and spatial nearest neighbors. Experiments are designed and conducted
to validate the effectiveness of our proposal. The experimental results show that our method achieves
decent prediction accuracy on the premise of privacy preservation. Keywords: Location-aware recommendation | Privacy-preserving | Data sparsity | Tensor factorizati |
مقاله انگلیسی |
3 |
Detailed analysis and improvement of an efficient and secure identity-based public auditing for dynamic outsourced data with proxy
تجزیه و تحلیل دقیق و بهبود ممیزی عمومی مبتنی بر هویت کارآمد و ایمن برای داده های برون سپاری پویا با پروکسی-2019 For data owners of restricted cloud access with a delegated proxy, public auditing technology for cloud data integrity, plays critical roles in ensuring powerful productivity that flexible cloud services provide for their business. In order to address the scalability of data owners and storage clouds for secure public auditing, Yu et al. (2017) proposed an Identity-Based Public Auditing for Dynamic Outsourced Data with Proxy Processing (https://doi.org/10.3837/tiis.2017.10.019), which also overcomes complicated public key certificates management issue. In this article, we figure out that this scheme is vulnerable to data loss attack where clouds could pass integrity auditing without original data. Meanwhile, a threat of system security is demonstrated, i.e., any entities are able to recover proxy private keys and impersonate proxy to forge proxy tag, with two arbitrary data tag pairs of same data owner. To enable secure identity-based batch public auditing with proxy processing, we propose an improved scheme without these security flaws and prove its security under CDH hard problem in the random oracle model. With complexity anal- ysis, our scheme shows better efficiency over identity-based proxy-oriented data uploading and remote data integrity checking in public cloud (ID-PUIC) in a single owner effort on a single cloud. Especially, we give the detailed analysis for how efficiently the attacks on Yu et al.’s scheme could be launched with an experiment, and demonstrate complete reduction on probability and time for proving security of our improved scheme. For potential application in big data storage, we first evaluate the error detection probability varying on number of auditing blocks, and then conduct detailed performance analysis by simulating our scheme and ID-PUIC scheme on the different number of data owners and storage clouds, with up to 10 6 data blocks Keywords: Cloud storage | Proxy | Public data auditing | Identity-based cryptography | Provable security |
مقاله انگلیسی |
4 |
Blockchain-based fair payment smart contract for public cloud storage auditing
قرارداد هوشمند پرداخت عادلانه مبتنی بر بلاکچین برای ممیزی ذخیره سازی ابر عمومی-2019 Cloud storage plays an important role in today’s cloud ecosystem. Increasingly clients tend to outsource their data to the cloud. In spite of its copious advantages, integrity has always been a significant issue. The audit method is commonly used to ensure integrity in cloud scenarios. However, traditional auditing schemes expect a third-party auditor (TPA), which is not always available in the real world. Also, the former scheme implies a limited pay- as-you-go service, as it requires the client to pay for the service in advance. In this paper, we aim to address the aforementioned drawback by adopting blockchain to replace TPA and designing a blockchain-based fair payment smart contract for public cloud storage auditing. In our system, data owner and cloud service provider (CSP) will run a blockchain-based smart contract. The contract ensures that the CSP is required to submit data possession proof regularly. The CSP gets paid only if the verification is passed; otherwise, it gets no remuneration but has to pay the penalties. To reduce the number of interactions in the execution of contract, we present the notion of non-interactive public provable data possession and design a blockchain-based smart contract for public cloud storage auditing based on this primitive.. Keywords: Blockchain | Smart contract | Public auditing | Fair payment | Cloud storage |
مقاله انگلیسی |
5 |
Pipeline-integrity: Scaling the use of authenticated data structures up to the cloud
پایپ لاین-یکپارچگی: مقیاس استفاده از ساختارهای داده معتبر تا ابر-2019 Public cloud storage services are widely adopted for their scalability and low cost. However, delegating
the management of the storage has serious implications from the security point of view. We focus
on integrity verification of query results based on the use of Authenticated Data Structures (ADS).
An ADS enables efficient updates of a cryptographic digest, when data changes, and efficient query
verification against this digest. Since, the digest can be updated (and usually signed) exclusively with
the intervention of a trusted party, the adoption of this approach is source of a serious performance
degradation, in particular when the trusted party is far from the server that stores the ADS.
In this paper, we show a protocol for a key–value storage service that provides ADS-enabled
integrity-protected queries and updates without impairing scalability, even in the presence of large
network latencies between trusted clients and an untrusted server. Our solution complies with the
principle of the cloud paradigm in which services should be able to arbitrarily scale with respect to
number of clients, requests rates, and data size keeping response time limited. We formally prove
that our approach is able to detect server misbehaviour in a setting whose consistency rules are only
slightly weaker than those guaranteed by previous results. We provide experimental evidence for the
feasibility and scalability of our approach. Keywords: Authenticated data structures | Scalability | Cloud | Integrity | Pipeline | Fork-linearisability |
مقاله انگلیسی |
6 |
Multimedia recommendation and transmission system based on cloud platform
توصیه و انتقال سیستم های چند رسانه ای بر اساس پلت فرم ابر-2017 This paper presents a movie recommendation system according to scores that the users provide. In view
of the movie evaluation system, the impacts of access control and multimedia security are analyzed, and
a secure hybrid cloud storage architecture is presented. Mobile-Edge Computing (MEC) technology is
used in the public cloud which guarantees the high efficiency requirements of the transmission of the
multimedia content. The processes of the system including registration, user login, role assignment, data
encryption and data decryption are also described. At last, the performance of the proposed scheme is
analyzed which further shows that the various possible attacks can be mitigated via the proposed system.
Keywords: Cloud computing | Cloud storage security | Mobile Edge Computing | Multimedia data |
مقاله انگلیسی |
7 |
Efficient task scheduling for budget constrained parallel applications on heterogeneous cloud computing systems
زمانبندی وطایف کارآمد برای برنامه های کاربردی موازی با محدودیت در سیستم های رایانه ای ناهمگن-2017 As the cost-driven public cloud services emerge, budget constraint is one of the primary design issues
in large-scale scientific applications executed on heterogeneous cloud computing systems. Minimizing
the schedule length while satisfying the budget constraint of an application is one of the most important
quality of service requirements for cloud providers. A directed acyclic graph (DAG) can be used to describe
an application consisted of multiple tasks with precedence constrains. Previous DAG scheduling methods
tried to presuppose the minimum cost assignment for each task to minimize the schedule length of budget
constrained applications on heterogeneous cloud computing systems. However, our analysis revealed
that the preassignment of tasks with the minimum cost does not necessarily lead to the minimization
of the schedule length. In this study, we propose an efficient algorithm of minimizing the schedule length
using the budget level (MSLBL) to select processors for satisfying the budget constraint and minimizing
the schedule length of an application. Such problem is decomposed into two sub-problems, namely,
satisfying the budget constraint and minimizing the schedule length. The first sub-problem is solved by
transferring the budget constraint of the application to that of each task, and the second sub-problem is
solved by heuristically scheduling each task with low-time complexity. Experimental results on several
real parallel applications validate that the proposed MSLBL algorithm can obtain shorter schedule lengths
while satisfying the budget constraint of an application than existing methods in various situations.
Keywords: Budget constraint | Heterogeneous clouds | Parallel application | Schedule length |
مقاله انگلیسی |
8 |
The operational cost minimization in distributed clouds via community-aware user data placements of social networks
کمینه سازی هزینه های عملیاتی در ابرهای توزیع شده از طریق جایگذاری داده های کاربر جامعه اگاه در شبکه های اجتماعی-2017 With the increasing popularity of Online Social Networking (OSN) and public cloud platforms, cloud ser
vice providers such as Facebook and Google desperately need efficient placements of large-volume user
data of social networks into their distributed clouds to enable the placed user data to be not only easily
accessed and updated but also highly available, reliable and scalable, in order to minimize their opera
tional costs of accommodating various social networks. In this paper, we investigate the problem of user
data placements of social networks into a distributed cloud with the aim to minimize the operational
cost of a cloud service provider, where the distributed cloud consists of multiple datacenters located at
different geographical regions and interconnected by Internet links. We first devise a fast yet scalable
algorithm for the user data placement problem. The key ingredient of this algorithm is the use of the
community concept, by grouping users of a social network into different communities and placing the
master replicas of user data of the users in the same community to a datacenter, and replicating their
slave replicas of the user data into nearby datacenters. We then deal with the dynamic maintenance of
the placed user data in an evolving social network, where new users can join in the network and exist
ing users can leave from the network at any time, or existing users can change their read and update
rates over time. We finally conduct extensive experiments to evaluate the efficiency of the proposed al
gorithms through simulations, using three real social network datasets: Facebook, Twitter and WikiVote.
Experimental results demonstrate that the proposed algorithms significantly outperform state-of-the-arts
in terms of the operational cost, yet run much faster.
Keywords: Community identification | Distributed clouds | User data placements | Optimization algorithms | Online social networks | Community maintenance |
مقاله انگلیسی |
9 |
SecureNoSQL: An approach for secure search of encrypted NoSQL databases in the public cloud
SecureNoSQL: یک رویکرد برای جستجوی امن از پایگاه داده های NoSQL کدگذاری شده در ابر عمومی-2017 While many schemes have been proposed to search encrypted relational databases, less attention has
been paid to NoSQL databases. In this paper we report on the design and the implementation of a security
scheme called “SecureNoSQL” for searching encrypted cloud NoSQL databases. Our solution is one of the
first efforts covering not only data confidentiality, but also the integrity of the datasets residing on a cloud
server. In our system a secure proxy carries out the required transformations and the cloud server is not
modified. The construction is applicable to all NoSQL data models and, in our experiments, we present
its application to a Document-store data model. The contributions of this paper include: (1) a descriptive
language based on a subset of JSON notations; (2) a tool to create and parse a security plan consisting of
cryptographic modules, data elements, and mappings of cryptographic modules to the data fields; and
(3) a query and data validation mechanism based on the security plan.
Keywords: Search over encrypted data | Database as a service | NoSQL | Encryption | Cloud computing | Security | Query processing | Data integrity |
مقاله انگلیسی |
10 |
MemEFS: A network-aware elastic in-memory runtime distributed file system
MemEFS: یک سیستم فایلی توزیع شده اجرای زمانی الاستیک حافظه ای مطلع از شبکه-2017 Scientific domains such as astronomy or bioinformatics produce increasingly large amounts of data that
need to be analyzed. Such analyses are modeled as scientific workflows — applications composed of
many individual tasks that exhibit data dependencies. Typically, these applications suffer from significant
variability in the interplay between achieved parallelism and data footprint. To efficiently tackle the data
deluge, cost effective solutions need to be deployed by extending private computing infrastructures with
public cloud resources. To achieve this, two key features for such systems need to be addressed: elasticity
and network adaptability. The former improves compute resource utilization efficiency, while the latter
improves network utilization efficiency, since public clouds suffer from significant bandwidth variability.
This paper extends our previous work on MemEFS, an in-memory elastic distributed file system by adding
network adaptability. Our results show that MemEFS’ elasticity increases the resource utilization efficiency
by up to 65%. Regarding the network adaptation policy, MemEFS achieves up to 50% speedup compared
to its network-agnostic counterpart.
Keywords: In-memory file system | Distributed hashing | Elasticity | calable computing | Network variability | Network adaptation | High-performance I/O | Large-scale scientific computing | Big data and HPC systems | Big data for e-Science | Large-scale systems for computational | sciences |
مقاله انگلیسی |