Privacy Policies and Measurement - The fundamental target of tone mapping is to duplicate the given scene or an image close to the 64000 world brilliance coordinating the human read inside the show gadgets. Therapeutic imaging utilizes that is procedures to downsize commotion and sharpness subtleties to upgrade the visual delineation of the picture. Because details play such an important role in determining proof and treating disease, it s critical to concentrate on the most important options when displaying medical images. It could be a method for reducing the unpredictability of high-dimensional data. You ll be able to use essential part analysis to rough out high- dimensional data with fewer measurements. Each measurement is regarded as the most important component and refers to a direct blend of the underlying components, as well as the amount of data. This data can be used to solve a wide range of problems that happen on a regular basis. It also highlighted how Big Data may be used to analyse Internet and image data sources effectively. concerns of privacy, methods for securing the components of pattern environments and systems, Edges, on the other hand, which nearly always square measure fascinating options of associate degree image) are also characterized by sharp transitions in grey levels, therefore averaging filters have the undesirable facet result that they blur edges. Another application of this kind of method includes the smoothing of false contours that result from victimization associate degree meagerly range of grey levels.

Privacy Policies and Measurement - The Function-as-a-Service cloud computing paradigm has made large-scale application development convenient and efficient as developers no longer need to deploy or manage the necessary infrastructure themselves. However, as a consequence of this abstraction, developers lose insight into how their code is executed and data is processed. Cloud providers currently offer little to no assurance of the integrity of customer data. One approach to robust data integrity verification is the analysis of data provenance—logs that describe the causal history of data, applications, users, and non-person entities. This paper introduces ProProv, a new domain-specific language and graphical user interface for specifying policies over provenance metadata to automate provenance analyses.

Privacy Policies and Measurement - The emergence of mobile edge computing (MEC) imposes an unprecedented pressure on privacy protection, although it helps the improvement of computation performance including energy consumption and computation delay by computation offloading. To this end, we propose a deep reinforcement learning (DRL)-based computation offloading scheme to optimize jointly privacy protection and computation performance. The privacy exposure risk caused by offloading history is investigated, and an analysis metric is defined to evaluate the privacy level. To find the optimal offloading strategy, an algorithm combining actor-critic, off-policy, and maximum entropy is proposed to accelerate the learning rate. Simulation results show that the proposed scheme has better performance compared with other benchmarks.

Privacy Policies and Measurement - Email is one of the oldest and most popular applications on today’s Internet and is used for business and private communication. However, most emails are still susceptible to being intercepted or even manipulated by the servers transmitting the messages. Users with S/MIME certificates can protect their email messages. In this paper, we investigate the market for S/MIME certificates and analyse the impact of the ordering and revocation processes on the users’ privacy. We complete those processes for each vendor and investigate the number of requests, the size of the data transfer, and the number of trackers on the vendor’s Web site. We further collect all relevant documents, including privacy policies, and report on their number of words, readability, and quality. Our results show that users must make at least 86 HTTP requests and transfer at least 1.35 MB to obtain a certificate and 178 requests and 2.03 MB to revoke a certificate. All but one vendor employ third-party tracking during these processes, which causes between 43 and 354 third-party requests. Our results further show that the vendors’ privacy policies are at least 1701 words long which requires a user approximately 7 minutes to read. The longest policy requires approximately half an hour to be read. Measurements of the readability of all vendors’ privacy policies indicate that users need a level of education that is nearly equivalent to a bachelor’s degree to comprehend the texts. We also report on the quality of the policies and find that the vendors achieve compliance scores between 45 \% and 90 \%. With our method, vendors can measure their impact on the users’ privacy and create better products. On the other hand, users benefit from an analysis of all S/MIME certificate vendors in that they can make an informed choice of their vendor based on the objective metrics obtained by our study. Ultimately, the results help to increase the prevalence of encrypted emails and render society less susceptible to surveillance.

Privacy Policies and Measurement - With increased reliance of digital storage for personal, financial, medical, and policy information, a greater demand for robust digital authentication and cybersecurity protection measures results. Current security options include alpha-numeric passwords, two factor authentication, and bio-metric options such as fingerprint or facial recognition. However, all of these methods are not without their drawbacks. This projects leverages the fact that the use of physical handwritten signatures is still prevalent in society, and the thoroughly trained process and motions of handwritten signatures is unique for every individual. Thus, a writing stylus that can authenticate its user via inertial signature detection is proposed, which classifies inertial measurement features for user identification. The current prototype consists of two triaxial accelerometers, one mounted at each of the stylus’ terminal ends. Features extracted from how the pen is held, stroke styles, and writing speed can affect the stylus tip accelerations which leads to a unique signature detection and to deter forgery attacks. Novel, manual spatiotemporal features relating to such metrics were proposed and a multi-layer perceptron was utilized for binary classification. Results of a preliminary user study are promising with overall accuracy of 95.7\%, sensitivity of 100\%, and recall rate of 90\%.

Privacy Policies and Measurement - Although the number of smart Internet of Things (IoT) devices has grown in recent years, the public s perception of how effectively these devices secure IoT data has been questioned. Many IoT users do not have a good level of confidence in the security or privacy procedures implemented within IoT smart devices for protecting personal IoT data. Moreover, determining the level of confidence end users have in their smart devices is becoming a major challenge. In this paper, we present a study that focuses on identifying privacy concerns IoT end users have when using IoT smart devices. We investigated multiple smart devices and conducted a survey to identify users privacy concerns. Furthermore, we identify five IoT privacy-preserving (IoTPP) control policies that we define and employ in comparing the privacy measures implemented by various popular smart devices. Results from our study show that the over 86\% of participants are very or extremely concerned about the security and privacy of their personal data when using smart IoT devices such as Google Nest Hub or Amazon Alexa. In addition, our study shows that a significant number of IoT users may not be aware that their personal data is collected, stored or shared by IoT devices.

Privacy Policies and Measurement - We report on the ideas and experiences of adapting Brane, a workflow execution framework, for use cases involving medical data exchange and processing. These use cases impose new requirements on the system to enforce policies encoding safety properties, ranging from access control to legal regulations pertaining to data privacy. Our approach emphasizes users’ control over the extent to which they cooperate in distributed execution, at the cost of revealing information about their policies.

Privacy Policies and Measurement - It is estimated that over 1 billion Closed-Circuit Television (CCTV) cameras are operational worldwide. The advertised main benefits of CCTV cameras have always been the same; physical security, safety, and crime deterrence. The current scale and rate of deployment of CCTV cameras bring additional research and technical challenges for CCTV forensics as well, as for privacy enhancements.

Privacy Policies and Measurement - Modelling and analyzing the massive policy discourse networks are of great importance in critical policy studies and have recently attracted increasing research interests. Yet, the effective representation scheme, quantitative policymaking metrics and the proper analysis methods remain largely unexplored. To address above challenges, with the Latent Dirichlet Allocation embedding, we proposed a government policy network, which models multiple entity types and complex relationships in between. Specifically, we have constructed the government policy network based on approximately 700 rural innovation and entrepreneurship policies released by the Chinese central government and eight provinces’ governments in the past eight years. We verified that the entity degree in the policy network is subject to the power-law distribution. Moreover, we propose a metric to evaluate the coordination between the central and local departments, namely coordination strength. And we find that this metric effectively reflects the coordination relationship between central and local departments. This study could be considered as a theoretical basis for applications such as policy discourse relationship prediction and departmental collaborative analysis.

Privacy Policies and Measurement - First introduced as a way of recording client-side state, third-party vendors have proliferated widely on the Web, and have become a fundamental part of the Web ecosystem. However, there is widespread concern that third-party vendors are being abused to track and profile individuals online for commercial, analytical and various other purposes. This paper builds the platform called “PRIVIS”, aiming at providing unique insights on how the privacy ecosystem is structured and affected through the analysis of data that stems from real users. First, to showcase what can be learned from this ecosystem through a datadriven analysis across the country, time and first-party categories, PRIVIS visualises data gathered from over 10K Chrome installers. It also equips participants with the means to collect and analyze their own data so that they could assess how their browsing habits are shared with third parties from their perspectives. Based on real-user datasets, the third-party quantity is not the only measure of web privacy risks. The measure proposed in this paper is how well thirdparty providers know their users. Second, PRIVIS studies the interplay between user location, special periods (after epidemic outbreak) and the overall number of third parties observed. The visualisation suggests that lockdown policies facilitate the growth in the number of third parties. Collectively, there are more active third-party activities, compared with both before the lockdowns and the corresponding periods in the previous year. And throughout the lockdown stages, the first lockdown performs the most aggressive.

Managing electricity effectively also means knowing as accurately as possible when, where and how electricity is used. Detailed metering and timely allocation of consumption can help identify specific areas where energy consumption is excessive and therefore requires action and optimization. All those interested in the measurement process (distributors, sellers, wholesalers, managers, ultimately customers and new prosumer figures - producers / consumers -) have an interest in monitoring and managing energy flows more efficiently, in real time.Smart meter plays a key role in sending data containing consumer measurements to both the producer and the consumer, thanks to chain 2. It allows you to connect consumption and production, during use and the customer’s identity, allowing billing as Time-of-Use or Real-Time Pricing, and through the new two-way channel, this information is also made available to the consumer / prosumer himself, enabling new services such as awareness of energy consumption at the very moment of energy use.This is made possible by latest generation devices that "talk" with the end user, which use chain 2 and the power line for communication.However, the implementation of smart meters and related digital technologies associated with the smart grid raises various concerns, including, privacy. This paper provides a comparative perspective on privacy policies for residential energy customers, moreover, it will be possible to improve security through the blockchain for the introduction of smart contracts.