29,394 research outputs found
Flexible Yet Secure De-Duplication Service for Enterprise Data on Cloud Storage
The cloud storage services bring forth infinite storage capacity and flexible access capability to store and share
large-scale content. The convenience brought forth has attracted both individual and enterprise users to outsource data service to a cloud provider. As the survey shows 56% of the usages of cloud storage applications are for data back up and up to 68% of data backup are user assets. Enterprise tenants would need to protect their data privacy before uploading them to the cloud and expect a reasonable performance while they try to reduce the operation cost in terms of cloud storage, capacity and I/Os matter as well
as systems’ performance, bandwidth and data protection. Thus, enterprise tenants demand secure and economic data storage yet flexible access on their cloud data.
In this paper, we propose a secure de-duplication solution
for enterprise tenants to leverage the benefits of cloud storage while reducing operation cost and protecting privacy. First, the solution uses a proxy to do flexible group access control which supports secure de-duplication within a group; Second, the solution supports scalable clustering of proxies to support large-scale data access; Third, the solution can be integrated with cloud storage seamlessly. We implemented and tested our solution by integrating it with Dropbox. Secure de-duplication in a group is performed at low data transfer latency and small
storage overhead as compared to de-duplication on plaintext
An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
The biological immune system (BIS) is characterized by networks of cells, tissues, and
organs communicating and working in synchronization. It also has the ability to learn,
recognize, and remember, thus providing the solid foundation for the development
of Artificial Immune System (AIS). Since the emergence of AIS, it has proved itself
as an area of computational intelligence. Real-Valued Negative Selection Algorithm
with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated
its potentials in the field of anomaly detection. The V-Detectors algorithm depends
greatly on the random detectors generated in monitoring the status of a system.
These randomly generated detectors suffer from not been able to adequately cover
the non-self space, which diminishes the detection performance of the V-Detectors
algorithm. This research therefore proposed CSDE-V-Detectors which entail the
use of the hybridization of Cuckoo Search (CS) and Differential Evolution (DE) in
optimizing the random detectors of the V-Detectors. The DE is integrated with CS
at the population initialization by distributing the population linearly. This linear
distribution gives the population a unique, stable, and progressive distribution process.
Thus, each individual detector is characteristically different from the other detectors.
CSDE capabilities of global search, and use of L´evy flight facilitates the effectiveness
of the detector set in the search space. In comparison with V-Detectors, cuckoo search,
differential evolution, support vector machine, artificial neural network, na¨ıve bayes,
and k-NN, experimental results demonstrates that CSDE-V-Detectors outperforms
other algorithms with an average detection rate of 95:30% on all the datasets. This
signifies that CSDE-V-Detectors can efficiently attain highest detection rates and
lowest false alarm rates for anomaly detection. Thus, the optimization of the randomly
detectors of V-Detectors algorithm with CSDE is proficient and suitable for anomaly
detection tasks
An empirical investigation of Network-Oriented Behaviors in Business-to-Business Markets
This study is concerned with the extent to which network-oriented behaviors directly and/or indirectly affect firm
performance. It argues that a firm's interaction behaviors in relation to an embedded network structure are key
mechanisms that facilitate the development of important organizational capabilities in dealing with business
partners. Such network-oriented behaviors, which are aimed at affecting the position of a company in the
network, are consequently important drivers of firm performance, rather than the network structure alone. We
develop a conceptual model that captures network-oriented behaviors as a driving force of firm performance
in relation to three other key organizational behaviors, i.e., customer-oriented, competitor-oriented and
relationship-oriented behaviors. We test the hypothesized model using a dataset of 354 responses collected
via an on-line questionnaire from UK managers, whose organizations operate in business-to-business markets
in either the manufacturing or services sectors. This study provides four key findings. First, a firm's networkoriented
behaviors positively affect the development of customer-oriented and competitor-oriented behaviors.
Secondly, they also foster relationship coordination with its important business partners within the network.
Thirdly, the effective management of the firm's portfolio of relationships is found to mediate the positive impact
of network-oriented behaviors on firm profitability. Lastly, closeness to end-users amplifies the positive effect of
network-oriented behaviors on relationship portfolio effectiveness
eWOM & Referrals in Social Network Services
If a few decades ago the development of the Internet was instrumental in the interconnection between markets, nowadays the services provided by Web 2.0, such as social network sites (SNS) are the cutting edge. A proof of this trend is the exponential growth of social network users. The main objective of this work is to explore the mechanisms that promote the transmission and reception (WOM and referrals) of online opinions, in the context of the
SNS, by buyers of travel services. The research includes some research lines: technology acceptance model (TAM), Social Identification Theory and Word-of-Mouth communication in virtual environment (eWOM). Based on these theories an explicative model has been proposed applying SEM analysis to a sample of SNS users’ of tourist service buyers. The results support the majority of the hypotheses and some relevant practical and theoretical
implications have been pointed out for tourist managers
The Impacts of Privacy Rules on Users' Perception on Internet of Things (IoT) Applications: Focusing on Smart Home Security Service
Department of Management EngineeringAs communication and information technologies advance, the Internet of Things (IoT) has changed the way people live. In particular, as smart home security services have been widely commercialized, it is necessary to examine consumer perception. However, there is little research that explains the general perception of IoT and smart home services. This article will utilize communication privacy management theory and privacy calculus theory to investigate how options to protect privacy affect how users perceive benefits and costs and how those perceptions affect individuals??? intentions to use of smart home service. Scenario-based experiments were conducted, and perceived benefits and costs were treated as formative second-order constructs. The results of PLS analysis in the study showed that smart home options to protect privacy decreased perceived benefits and increased perceived costs. In addition, the perceived benefits and perceived costs significantly affected the intention to use smart home security services. This research contributes to the field of IoT and smart home research and gives practitioners notable guidelines.ope
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