Security policy speculation of user uploaded images on content sharing sites
01 Nov 2017-Vol. 263, Iss: 4, pp 042019
About: The article was published on 2017-11-01 and is currently open access. It has received 17 citations till now. The article focuses on the topics: Security policy.
Citations
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13 Feb 2020
TL;DR: The allocation of task and placement of virtual machine problems is explained in the single fog computing environment and the result shows that the proposed framework improves QoS in fog environment.
Abstract: In today's world, large group migration of applications to the fog computing is registered in the information technology world. The main issue in fog computing is providing enhanced quality of service (QoS). QoS management consists of various method used for allocating fog‐user applications in the virtual environment and selecting suitable method for allocating virtual resources to physical resource. The resources allocation in effective manner in the fog environment is also a major problem in fog computing; it occurs when the infrastructure is build using light‐weight computing devices. In this article, the allocation of task and placement of virtual machine problems is explained in the single fog computing environment. The experiment is done and the result shows that the proposed framework improves QoS in fog environment.
16 citations
TL;DR: The proposed hybrid fingerprint extracting using simhash (SH) and Huffman coding (HC) algorithms and GWO based clustering method for de-duplication is compared with the existing methods in terms of accuracy, True Positive Rate (TPR), True negative rate (TNR) and performance time.
Abstract: This paper intends to perform de-duplication for enhancing the storage optimization. Hence, this paper contributes by proposing a hybrid fingerprint extracting using simhash (SH) and Huffman coding (HC) algorithms. Secondly, the data is clustered using the latest technique called as grey wolf optimization (GWO) to extract the metadata. The extracted metadata is stored in metadata server which provides better storage optimization and de-duplication. Euclidean distance based GWO is adopted as it provides minimum Euclidean distance in the GWO based clustering for de-duplication. The proposed GWO based clustering method is compared with the existing methods such as k-means, k-mode, Euclidean distance based Particle Swarm Optimization and Euclidean distance based genetic algorithm in terms of accuracy, True Positive Rate (TPR), True Negative Rate (TNR) and performance time and the significance of the GWO based clustering method is described.
14 citations
TL;DR: Self-Adaptive Grey Wolf Optimization (GWO) is proposed for optimizing 2-dimensional Logistic Chaotic Mapping (2DCM) and the experimental result stated that the proposed method is key sensitive and opposed to the general attacks during the encryption and decryption of images.
Abstract: The development of encryption and decryption plays a vital role in the field of security. Recently, Chaos-based security has suggested the reliable and efficient way of securing the images. In this paper, Self-Adaptive Grey Wolf Optimization (GWO) is proposed for optimizing 2-dimensional Logistic Chaotic Mapping (2DCM). Further, the security analysis of the proposed method is performed using different comparison such as key sensitivity, histogram analysis, adjacent pixel autocorrelation, information entropy, attacks, quality of encryption, Chi square test etc. Moreover, analytical outcomes are compared with the conventional algorithms like standard encryption and decryption, Genetic Algorithm (GA) and GWO. The experimental result stated that the proposed method is key sensitive and opposed to the general attacks during the encryption and decryption of images.
13 citations
TL;DR: A hybrid algorithm termed as genetically modified glowworm swarm is used for both data sanitization and data restoration process, and the dominance of the developed model is proved.
Abstract: Cloud computing is a computing paradigm that provides vibrant accessible infrastructure for data, application and file storage as well. This technology advancement benefits in a significant lessening of consumption cost, application hosting, content storage as well as delivery, and hence the concept appear gradually more in all entities that exploited in the healthcare sector. Under such circumstances, efficient analysis and data extraction from a cloud environment is more challenging. Moreover, the extracted data has to be preserved for privacy. To handle these challenges, this paper has come out with a privacy-preserving algorithm in both data sanitization and data restoration process. Further, several researchers have contributed advancement in the restoration process, yet the accuracy of restoration seems to be very low. As a solution to this problem, this paper uses a hybrid algorithm termed as genetically modified glowworm swarm for both data sanitization and data restoration process. Further, the developed hybridization model compares its performance with other conventional models like conventional glowworm swarm optimization, firefly, particle swarm optimization, artificial bee colony, crow search, group search optimization and genetic algorithm in terms of statistical analysis, sanitization and restoration effectiveness, convergence analysis and key sensitivity analysis, and the dominance of the developed model is proved.
13 citations
TL;DR: An effectual active contour with modified Otsu threshold value to automated discovery of follicles from the ultrasound images is presented and the performances illustrate the betterments of the proposed approach over other techniques.
Abstract: Polycystic ovary syndrome (PCOS) disorder is identified by the presence of a number of follicles present in the ovary of female reproductive system. Ultrasound imaging of the ovary contains essential information about the size, number of follicles and its position. In real time, the detection of PCOS is a difficult task for radiologists due to the various sizes of follicles and is highly connected with blood vessels and tissues. This often results in error diagnosis. For preprocessing various standard filtering techniques are applied on ovary image. Based on the performance, appropriate filter is chosen to remove the noise from the image. This paper presents an effectual active contour with modified Otsu threshold value to automated discovery of follicles from the ultrasound images. The performances of the proposed method illustrate the betterments of the proposed approach over other techniques.
13 citations
References
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10,454 citations
TL;DR: A simulation of a clinical trial of the treatment of coronary artery disease by allocating 1073 patient records from past cases into two “treatment” groups at random failed to show any significant difference in survival between those patients allocated to the two treatments.
Abstract: Many published papers include large numbers of significance tests. These may be difficult to interpret because if we go on testing long enough we will inevitably find something which is “significant.” We must beware of attaching too much importance to a lone significant result among a mass of non-significant ones. It may be the one in 20 which we expect by chance alone.
Lee et al simulated a clinical trial of the treatment of coronary artery disease by allocating 1073 patient records from past cases into two “treatment” groups at random.1 They then analysed the outcome as if it were a genuine trial of two treatments. The analysis was quite detailed and thorough. As we would expect, it failed to show any significant difference in survival between those patients allocated to the two treatments. Patients were then subdivided by two variables which affect prognosis, the number of diseased coronary vessels and whether the left ventricular contraction pattern was normal or abnormal. A significant difference in survival between the two “treatment” groups was found in those patients with three diseased vessels (the maximum) and abnormal ventricular contraction. As this would be the subset of patients with the worst prognosis, the finding would be easy to account for by saying that the superior “treatment” …
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TL;DR: In this paper, a representative sample of the members of the Facebook (a social network for colleges and high schools) at a US academic institution, and compare the survey data to information retrieved from the network itself.
Abstract: Online social networks such as Friendster, MySpace, or the Facebook have experienced exponential growth in membership in recent years. These networks offer attractive means for interaction and communication, but also raise privacy and security concerns. In this study we survey a representative sample of the members of the Facebook (a social network for colleges and high schools) at a US academic institution, and compare the survey data to information retrieved from the network itself. We look for underlying demographic or behavioral differences between the communities of the network's members and non-members; we analyze the impact of privacy concerns on members' behavior; we compare members' stated attitudes with actual behavior; and we document the changes in behavior subsequent to privacy-related information exposure. We find that an individual's privacy concerns are only a weak predictor of his membership to the network. Also privacy concerned individuals join the network and reveal great amounts of personal information. Some manage their privacy concerns by trusting their ability to control the information they provide and the external access to it. However, we also find evidence of members' misconceptions about the online community's actual size and composition, and about the visibility of members' profiles.
1,888 citations
29 Apr 2007
TL;DR: The incentives for annotation in Flickr, a popular web-based photo-sharing system, and ZoneTag, a cameraphone photo capture and annotation tool that uploads images to Flickr are investigated to offer a taxonomy of motivations for annotation along two dimensions (sociality and function).
Abstract: Why do people tag? Users have mostly avoided annotating media such as photos -- both in desktop and mobile environments -- despite the many potential uses for annotations, including recall and retrieval. We investigate the incentives for annotation in Flickr, a popular web-based photo-sharing system, and ZoneTag, a cameraphone photo capture and annotation tool that uploads images to Flickr. In Flickr, annotation (as textual tags) serves both personal and social purposes, increasing incentives for tagging and resulting in a relatively high number of annotations. ZoneTag, in turn, makes it easier to tag cameraphone photos that are uploaded to Flickr by allowing annotation and suggesting relevant tags immediately after capture. A qualitative study of ZoneTag/Flickr users exposed various tagging patterns and emerging motivations for photo annotation. We offer a taxonomy of motivations for annotation in this system along two dimensions (sociality and function), and explore the various factors that people consider when tagging their photos. Our findings suggest implications for the design of digital photo organization and sharing applications, as well as other applications that incorporate user-based annotation.
912 citations
20 Jul 2009
TL;DR: This work examines the difficulty of collecting profile and graph information from the popular social networking website Facebook and describes several novel ways in which data can be extracted by third parties, and demonstrates the efficiency of these methods on crawled data.
Abstract: Preventing adversaries from compiling significant amounts of user data is a major challenge for social network operators. We examine the difficulty of collecting profile and graph information from the popular social networking website Facebook and report two major findings. First, we describe several novel ways in which data can be extracted by third parties. Second, we demonstrate the efficiency of these methods on crawled data. Our findings highlight how the current protection of personal data is inconsistent with user's expectations of privacy.
242 citations