Search results for: different dimension of privacy

Authors: N. A. Badrul

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People are concerned that they are vulnerable as a result of what is exposed about them on the internet. Users are increasingly aware of their privacy and are making various efforts to protect their personal information. However, besides individuals themselves, organisations are also exposing personal information of their staff to the general public by publishing it on their official website. This practice may put individuals at risk and particularly vulnerable to threats. This preliminary study explores explicitly the amount and types of personal information disclosure from organisational websites. Threats and risks related to the disclosures are discussed. In general, all the examined organisational websites discloses personal information with varies identifiable degree of data.

Keywords: personal information, privacy, e-government, information disclosure

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Authors: Saeedeh Shahbazkhany

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Cancer is a terrible disease that, if not diagnosed early, therapy can be difficult while it is easily medicable if it is diagnosed in early stages. So it is very important for cancer diagnosis that medical procedures are performed. In this paper we introduce a new method. In this method, we only need pictures of healthy cells and cancer cells. In fact, where we suspect cancer, we take a picture of cells or tissue in that area, and then take some pictures of the surrounding tissues. Then, fractal dimension of images are calculated and compared. Cancer can be easily detected by comparing the fractal dimension of images. In this method, we use Matlab software.

Keywords: Matlab software, fractal dimension, cancer, surrounding tissues, cells or tissue, new method

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Authors: Dhananjay Singh, M. Abdullah-Al-Wadud

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The Internet of Things is a concept of a large scale ecosystem of wireless actuators. The actuators are defined as things in the IoT, those which contribute or produces some data to the ecosystem. However, ubiquitous data collection, data security, privacy preserving, large volume data processing, and intelligent analytics are some of the key challenges into the IoT technologies. In order to solve the security requirements, challenges and threats in the IoT, we have discussed a message authentication mechanism for IoT applications. Finally, we have discussed data encryption mechanism for messages authentication before propagating into IoT networks.

Keywords: Internet of Things (IoT), message authentication, privacy, security

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Authors: Devika Tanna

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'Biometrics' means 'life measurement' but the term is usually associated with the use of unique physiological characteristics to identify an individual. It is important to secure the privacy of digital face image that is stored in central database. To impart privacy to such biometric face images, first, the digital face image is split into two host face images such that, each of it gives no idea of existence of the original face image and, then each cover image is stored in two different databases geographically apart. When both the cover images are simultaneously available then only we can access that original image. This can be achieved by using the XM2VTS and IMM face database, an adaptive algorithm for spatial greyscale. The algorithm helps to select the appropriate host images which are most likely to be compatible with the secret image stored in the central database based on its geometry and appearance. The encryption is done using GEVCS which results in a reconstructed image identical to the original private image.

Keywords: adaptive algorithm, database, host images, privacy, visual cryptography

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Authors: Farbod Behnaminia, Saeed Samet

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The COVID-19 pandemic has paralyzed many lives until a vaccine was available, which caused the so-called “new normal.” According to the World Health Organization (WHO), COVID-19 is an infectious disease. It can cause significant illness or death in anyone. Governments and health officials tried to impose rules and regulations to avoid and slow down transmission. Therefore, software engineers worldwide developed applications to trace and track patients’ movements and notify others, mainly using Bluetooth. In this way, everyone could be informed whether they come in close contact with someone who has COVID-19 and takes proper safety precautions. Because most of the applications use technologies that can potentially reveal the user’s identity and location, researchers have debated privacy preservation and how to improve user privacy during such pandemics. Thanks to Distributed Ledger Technology (DLT), there have been some proposed methods to develop privacy-preserving Patient Tracking Systems in the last two years. As an instance of the DLT, Blockchain is like a decentralized peer-to-peer database that maintains a record of transactions. Transactions are immutable, transparent, and anonymous in this system. We conducted a comprehensive evaluation of the literature by looking for papers in the relevant field and dividing them into pre- and post-pandemic systems. Additionally, we discussed the many uses of blockchain technology in pandemic control. We found that two major obstacles facing blockchain implementation across many healthcare systems are scalability and privacy. The Polkadot platform is presented, along with a review of its efficacy in tackling current concerns. A more scalable healthcare system is achievable in the near future using Polkadot as well as a much more privacy-preserving environment.

Keywords: blockchain, electronic record management, EHR, privacy-preserving, patient tracking, COVID-19, trust and confidence, Polkadot

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Authors: Abdullah Al Mamun, Talal Alkharobi

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As data size is growing up, people are became more familiar to store big amount of secret information into cloud storage. Companies are always required to need transfer massive business files from one end to another. We are going to lose privacy if we transmit it as it is and continuing same scenario repeatedly without securing the communication mechanism means proper encryption. Although asymmetric key encryption solves the main problem of symmetric key encryption but it can only encrypt limited size of data which is inapplicable for large data encryption. In this paper we propose a probable approach of pretty good privacy for encrypt big data using both symmetric and asymmetric keys. Our goal is to achieve encrypt huge collection information and transmit it through a secure communication channel for committing the business and personal privacy. To justify our method an experimental dataset from three different platform is provided. We would like to show that our approach is working for massive size of various data efficiently and reliably.

Keywords: big data, cloud computing, cryptography, hadoop, public key

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Authors: Yunyong Guo, Man Wang, Bryan Guo, Nathan Guo

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This paper introduces an advanced security and privacy model tailored for Telehealth systems, emphasizing end-to-end protection across IoT, Fog, and Cloud components. The proposed model integrates encryption, key management, intrusion detection, and privacy-preserving measures to safeguard patient data. A comprehensive simulation study evaluates the model's effectiveness in scenarios such as unauthorized access, physical breaches, and insider threats. Results indicate notable success in detecting and mitigating threats yet underscore areas for refinement. The study contributes insights into the intricate balance between security and usability in Telehealth environments, setting the stage for continued advancements.

Keywords: cloud, enhancing security, fog, IoT, telehealth

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Authors: Razieh Khalafi

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Myocardial infarction (MI) or acute myocardial infarction (AMI), commonly known as a heart attack, occurs when blood flow stops to part of the heart causing damage to the heart muscle. An ECG can often show evidence of a previous heart attack or one that's in progress. The patterns on the ECG may indicate which part of your heart has been damaged, as well as the extent of the damage. In chaos theory, the correlation dimension is a measure of the dimensionality of the space occupied by a set of random points, often referred to as a type of fractal dimension. In this research by considering ECG signal as a random walk we work on forecasting the oncoming heart attack by analyzing the ECG signals using the correlation dimension. In order to test the model a set of ECG signals for patients before and after heart attack was used and the strength of model for forecasting the behavior of these signals were checked. Results shows this methodology can forecast the ECG and accordingly heart attack with high accuracy.

Keywords: heart attack, ECG, random walk, correlation dimension, forecasting

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Authors: Suman Podder

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As Australian ‘Open Banking’ allows customers to share their financial data with accredited Third-Party Providers (‘TPPs’), it is necessary to evaluate whether the regulators have achieved the balance between protecting customer data privacy and promoting data-related innovation. Recognising the need to increase customers’ influence on their own data, and the benefits of data-related innovation, the Australian Government introduced ‘Consumer Data Right’ (‘CDR’) to the banking sector through Open Banking regulation. Under Open Banking, TPPs can access customers’ banking data that allows the TPPs to tailor their products and services to meet customer needs at a more competitive price. This facilitated access and use of customer data will promote innovation by providing opportunities for new products and business models to emerge and grow. However, the success of Open Banking depends on the willingness of the customers to share their data, so the regulators have augmented the protection of data by introducing new privacy safeguards to instill confidence and trust in the system. The dilemma in policymaking is that, on the one hand, lenient data privacy laws will help the flow of information, but at the risk of individuals’ loss of privacy, on the other hand, stringent laws that adequately protect privacy may dissuade innovation. Using theoretical and doctrinal methods, this paper examines whether the privacy safeguards under Open Banking will add to the compliance burden of the participating financial institutions, resulting in the undesirable effect of stifling other policy objectives such as innovation. The contribution of this research is three-fold. In the emerging field of customer data sharing, this research is one of the few academic studies on the objectives and impact of Open Banking in the Australian context. Additionally, Open Banking is still in the early stages of implementation, so this research traces the evolution of Open Banking through policy debates regarding the desirability of customer data-sharing. Finally, the research focuses not only on the customers’ data privacy and juxtaposes it with another important objective of promoting innovation, but it also highlights the critical issues facing the data-sharing regime. This paper argues that while it is challenging to develop a regulatory framework for protecting data privacy without impeding innovation and jeopardising yet unknown opportunities, data privacy and innovation promote different aspects of customer welfare. This paper concludes that if a regulation is appropriately designed and implemented, the benefits of data-sharing will outweigh the cost of compliance with the CDR.

Keywords: consumer data right, innovation, open banking, privacy safeguards

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Authors: Razi Khalafi

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Myocardial Infarction (MI) or acute Myocardial Infarction (AMI), commonly known as a heart attack, occurs when blood flow stops to part of the heart causing damage to the heart muscle. An ECG can often show evidence of a previous heart attack or one that's in progress. The patterns on the ECG may indicate which part of your heart has been damaged, as well as the extent of the damage. In chaos theory, the correlation dimension is a measure of the dimensionality of the space occupied by a set of random points, often referred to as a type of fractal dimension. In this research by considering ECG signal as a random walk we work on forecasting the oncoming heart attack by analysing the ECG signals using the correlation dimension. In order to test the model a set of ECG signals for patients before and after heart attack was used and the strength of model for forecasting the behaviour of these signals were checked. Results show this methodology can forecast the ECG and accordingly heart attack with high accuracy.

Keywords: heart attack, ECG, random walk, correlation dimension, forecasting

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Authors: Andrei Bogdan Stanescu, Laura Diaconescu

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With the increasing concerns about data breaches and privacy violations, organizations seek robust security measures to protect sensitive information. This research paper highlights the importance of implementing the Zero-Trust Security methodology using Passwordless Authentication Gateways that leverage Keycloak, an open-source Identity and Access Management (IAM) software, as a solution to address the security challenges these organizations face. The paper presents the successful implementation and deployment of such a solution in a mid-size, privacy-oriented organization. The implementation resulted in significant security improvements, reducing the risk of unauthorized access and potential data breaches. Moreover, user feedback indicated enhanced convenience and streamlined authentication experiences. The results of this study bring solid contributions in the field of cybersecurity and provide practical insights for organizations aiming to strengthen their security practices.

Keywords: identity and access management, passwordless authentication, privacy, zero-trust security

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Authors: Amir Hajian, Sepehr Damavandinejadmonfared

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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

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Authors: Amir Farouk Ahmed Ali Hussin

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Social media, such as Facebook, LinkedIn and Ex-Twitter have experienced exponential growth and a remarkable adoption rate in recent years. They give fantastic means of online social interactions and communications with family, friends, and colleagues from around the corner or across the globe, and they have become an important part of daily digital interactions for more than one and a half billion users around the world. The personal information sharing practices that social network providers encourage have led to their success as innovative social interaction platforms. Moreover, these practices have outcome in concerns with respect to privacy and security from different stakeholders. Guiding these privacy and security concerns in social networks is a must for these networks to be sustainable. Real security and privacy tools may not be enough to address existing concerns. Some points should be followed to protect users from the existing risks. In this research, we have checked the various privacy and security issues and concerns pertaining to social media. However, we have classified these privacy and security issues and presented a thorough discussion of the effects of these issues and concerns on the future of the social networks. In addition, we have presented a set of points as precaution measures that users can consider to address these issues.

Keywords: international legal, consultation mix, legal research, small and medium-sized enterprises, strategic International law, strategy alignment, house of laws, deployment, production strategy, legal strategy, business strategy

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Authors: Kyung-Ja Cho, Sun Jin Park

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This study examined what effective dimension affects facial attractiveness. Two orthogonal dimensions, sharp-soft and babyish-mature, were used to rate the levels of facial attractiveness in 20’s women. This research also investigated the sex difference on the effect of effective dimension of face on attractiveness. The test subjects composed of 15 males and 18 females. They looked 330 photos of women in 20s. Then they rated the levels of the effective dimensions of faces with sharp-soft and babyish-mature, and the attraction with charmless-charming. The respond forms were Likert scales, the answer was scored from 1 to 9. As a result of multiple regression analysis, the subject reported the milder and younger appearance as more attractive. Both male and female subjects showed the same evaluation. This result means that two effective dimensions have the effect on estimating attractiveness.

Keywords: affective dimension of faces, facial attractiveness, sharp-soft, babyish-mature

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Authors: H. Parveen Begam, M. A. Maluk Mohamed

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Grid computing is an environment that allows sharing and coordinated use of diverse resources in dynamic, heterogeneous and distributed environment using Virtual Organization (VO). Security is a critical issue due to the open nature of the wireless channels in the grid computing which requires three fundamental services: authentication, authorization, and encryption. The privacy and anonymity are considered as an important factor while communicating over publicly spanned network like web. To ensure a high level of security we explored an extension of onion routing, which has been used with dynamic token exchange along with protection of privacy and anonymity of individual identity. To improve the performance of encrypting the layers, the elliptic curve cryptography is used. Compared to traditional cryptosystems like RSA (Rivest-Shamir-Adelman), ECC (Elliptic Curve Cryptosystem) offers equivalent security with smaller key sizes which result in faster computations, lower power consumption, as well as memory and bandwidth savings. This paper presents the estimation of the performance improvements of onion routing using ECC as well as the comparison graph between performance level of RSA and ECC.

Keywords: grid computing, privacy, anonymity, onion routing, ECC, RSA

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Authors: Nidal F. Shilbayeh, Sameh T. Khuffash, Mohammad H. Allymoun, Reem Al-Saidi

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There is a real threat on the VIPs personal pages on the Social Network Sites (SNS). The real threats to these pages is violation of privacy and theft of identity through creating fake pages that exploit their names and pictures to attract the victims and spread of lies. In this paper, we propose a new secure architecture that improves the trusting and finds an effective solution to reduce fake pages and possibility of recognizing VIP pages on SNS. The proposed architecture works as a third party that is added to Facebook to provide the trust service to personal pages for VIPs. Through this mechanism, it works to ensure the real identity of the applicant through the electronic authentication of personal information by storing this information within content of their website. As a result, the significance of the proposed architecture is that it secures and provides trust to the VIPs personal pages. Furthermore, it can help to discover fake page, protect the privacy, reduce crimes of personality-theft, and increase the sense of trust and satisfaction by friends and admirers in interacting with SNS.

Keywords: social network sites, online social network, privacy, trust, security and authentication

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Authors: Mitra Saberi, Saeideh Fakhari, Amir Karam, Ali Ahmadabadi

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Geomorphology is the scientific study of the characteristics of form and shape of the Earth's surface. The existence of types of landforms and their variation is mainly controlled by changes in the shape and position of land and topography. In fact, the interest and application of fractal issues in geomorphology is due to the fact that many geomorphic landforms have fractal structures and their formation and transformation can be explained by mathematical relations. The purpose of this study is to identify and analyze the fractal behavior of landforms of macro geomorphologic regions of Iran, as well as studying and analyzing topographic and landform characteristics based on fractal relationships. In this study, using the Iranian digital elevation model in the form of slopes, coefficients of deposition and alluvial fan, the fractal dimensions of the curves were calculated through the box counting method. The morphometric characteristics of the landforms and their fractal dimension were then calculated for 4criteria (height, slope, profile curvature and planimetric curvature) and indices (maximum, Average, standard deviation) using ArcMap software separately. After investigating their correlation with fractal dimension, two-way regression analysis was performed and the relationship between fractal dimension and morphometric characteristics of landforms was investigated. The results show that the fractal dimension in different pixels size of 30, 90 and 200m, topographic curves of different landform units of Iran including mountain, hill, plateau, plain of Iran, from1.06in alluvial fans to1.17in The mountains are different. Generally, for all pixels of different sizes, the fractal dimension is reduced from mountain to plain. The fractal dimension with the slope criterion and the standard deviation index has the highest correlation coefficient, with the curvature of the profile and the mean index has the lowest correlation coefficient, and as the pixels become larger, the correlation coefficient between the indices and the fractal dimension decreases.

Keywords: box counting method, fractal dimension, geomorphology, Iran, landform

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Authors: Renata Mekovec, Dijana Peras, Ruben Picek

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The advent of the Internet, mobile devices and social media is revolutionizing the experience of retail customers by linking multiple sources through various channels. Omnichannel retailing is a retailing that combines multiple channels to allow customers to seamlessly leverage all the distribution information online and offline while shopping. Therefore, today data are an asset more critical than ever for all organizations. Nonetheless, because of its heterogeneity through platforms, developers are currently facing difficulties in dealing with personal data. Considering the possibilities of omnichannel communication, this paper presents channel categorization that could enhance the customer experience of omnichannel center called hyper center. The purpose of this paper is fundamentally to describe the connection between the omnichannel hyper center and the customer, with particular attention to privacy protection. The first phase was finding the most appropriate channels of communication for hyper center. Consequently, a selection of widely used communication channels has been identified and analyzed with regard to the effect requirements for optimizing user experience. The evaluation criteria are divided into 3 groups: general, user profile and channel options. For each criterion the weight of importance for omnichannel communication was defined. The most important thing was to consider how the hyper center can make user identification while respecting the privacy protection requirements. The study carried out also shows what customer experience across digital networks would look like, based on an omnichannel approach owing to privacy protection principles.

Keywords: personal data, privacy protection, omnichannel communication, retail

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Authors: Isabell Koinig, Sandra Diehl

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In recent years, the health-care context has not been left unaffected by technological developments. In recent years, the Internet of Medical Things (IoMT)has not only led to a collaboration between disease management and advanced care coordination but also to more personalized health care and patient empowerment. With more than 40 % of all health technology being IoMT-related by 2020, questions regarding privacy become more prevalent, even more so during COVID-19when apps allowing for an intensive tracking of people’s whereabouts and their personal contacts cause privacy advocates to protest and revolt. There is a widespread tendency that even though users may express concerns and fears about their privacy, they behave in a manner that appears to contradict their statements by disclosing personal data. In literature, this phenomenon is discussed as a privacy paradox. While there are some studies investigating the privacy paradox in general, there is only scarce research related to the privacy paradox in the health sector and, to the authors’ knowledge, no empirical study investigating young people’s attitudes toward data security when using wearables and health apps. The empirical study presented in this paper tries to reduce this research gap by focusing on the area of digital and mobile health. It sets out to investigate the degree of importance individuals attribute to protecting their privacy and individual privacy protection strategies. Moreover, the question to which degree individuals between the ages of 20 and 30 years are willing to grant commercial parties access to their private data to use digital health services and apps are put to the test. To answer this research question, results from 6 focus groups with 40 participants will be presented. The focus was put on this age segment that has grown up in a digitally immersed environment. Moreover, it is particularly the young generation who is not only interested in health and fitness but also already uses health-supporting apps or gadgets. Approximately one-third of the study participants were students. Subjects were recruited in August and September 2019 by two trained researchers via email and were offered an incentive for their participation. Overall, results indicate that the young generation is well informed about the growing data collection and is quite critical of it; moreover, they possess knowledge of the potential side effects associated with this data collection. Most respondents indicated to cautiously handle their data and consider privacy as highly relevant, utilizing a number of protective strategies to ensure the confidentiality of their information. Their willingness to share information in exchange for services was only moderately pronounced, particularly in the health context, since health data was seen as valuable and sensitive. The majority of respondents indicated to rather miss out on using digital and mobile health offerings in order to maintain their privacy. While this behavior might be an unintended consequence, it is an important piece of information for app developers and medical providers, who have to find a way to find a user base for their products against the background of rising user privacy concerns.

Keywords: digital health, privacy, privacy paradox, IoMT

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Authors: Sadegh Marzban, Mohamad Sobhan Sheikh Andalibi, Farnaz Ghassemi, Farzad Towhidkhah

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Parkinson's disease (PD), which is characterized by the tremor at rest, rigidity, akinesia or bradykinesia and postural instability, affects the quality of life of involved individuals. The concept of a fractal is most often associated with irregular geometric objects that display self-similarity. Fractal dimension (FD) can be used to quantify the complexity and the self-similarity of an object such as tremor. In this work, we are aimed to propose a new method for evaluating hyperkinetic movements such as tremor, by using the FD and other correlated parameters in patients who are suffered from PD. In this study, we used 'the tremor data of Physionet'. The database consists of fourteen participants, diagnosed with PD including six patients with high amplitude tremor and eight patients with low amplitude. We tried to extract features from data, which can distinguish between patients before and after medication. We have selected fractal dimensions, including correlation dimension, box dimension, and information dimension. Lilliefors test has been used for normality test. Paired t-test or Wilcoxon signed rank test were also done to find differences between patients before and after medication, depending on whether the normality is detected or not. In addition, two-way ANOVA was used to investigate the possible association between the therapeutic effects and features extracted from the tremor. Just one of the extracted features showed significant differences between patients before and after medication. According to the results, correlation dimension was significantly different before and after the patient's medication (p=0.009). Also, two-way ANOVA demonstrates significant differences just in medication effect (p=0.033), and no significant differences were found between subject's differences (p=0.34) and interaction (p=0.97). The most striking result emerged from the data is that correlation dimension could quantify medication treatment based on tremor. This study has provided a technique to evaluate a non-linear measure for quantifying medication, nominally the correlation dimension. Furthermore, this study supports the idea that fractal dimension analysis yields additional information compared with conventional spectral measures in the detection of poor prognosis patients.

Keywords: correlation dimension, non-linear measure, Parkinson’s disease, tremor

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Authors: Nkiru I. Ibeakuzie, Paul D. J. Watson, John F. Pescatore

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In roadway construction, the cost of soil-cement stabilization per unit area is significantly influenced by the binder content, hence the need to optimise cement usage. This research work will characterize the influence of soil fractal geometry on properties of cement-stabilized soil, and strive to determine a correlation between mechanical proprieties of cement-stabilized soil and the mass fractal dimension Dₘ indicated by particle size distribution (PSD) of aggregate mixtures. Since strength development in cemented soil relies not only on cement content but also on soil PSD, this study will investigate the possibility of reducing cement content by changing the PSD of soil, without compromising on strength, reduced permeability, and compressibility. A series of soil aggregate mixes will be prepared in the laboratory. The mass fractal dimension Dₘ of each mix will be determined from sieve analysis data prior to stabilization with cement. Stabilized soil samples will be tested for strength, permeability, and compressibility.

Keywords: fractal dimension, particle size distribution, cement stabilization, cement content

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Authors: Amrashaa Singh

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In the digital age and the large cyberspace, Data Protection and Privacy have become major issues in this technological era. There was a time when social media and online shopping websites were treated as a blessing for the people. But now the tables have turned, and the people have started to look at them with suspicion. They are getting aware of the privacy implications, and they do not feel as safe as they used to initially. When Edward Snowden informed the world about the snooping United States Security Agencies had been doing, that is when the picture became clear for the people. After the Cambridge Analytica case where the data of Facebook users were stored without their consent, the doubts arose in the minds of people about how safe they actually are. In India, the case of spyware Pegasus also raised a lot of concerns. It was used to snoop on a lot of human right activists and lawyers and the company which invented the spyware claims that it only sells it to the government. The paper will be dealing with the privacy concerns in the Indian perspective with an analytical methodology. The Supreme Court here had recently declared a right to privacy a Fundamental Right under Article 21 of the Constitution of India. Further, the Government is also working on the Data Protection Bill. The point to note is that India is still a developing country, and with the bill, the government aims at data localization. But there are doubts in the minds of many people that the Government would actually be snooping on the data of the individuals. It looks more like an attempt to curb dissenters ‘lawfully’. The focus of the paper would be on these issues in India in light of the European Union (EU) General Data Protection Regulation (GDPR). The Indian Data Protection Bill is also said to be loosely based on EU GDPR. But how helpful would these laws actually be is another concern since the economic and social conditions in both countries are very different? The paper aims at discussing these concerns, how good or bad is the intention of the government behind the bill, and how the nations can act together and draft common regulations so that there is some uniformity in the laws and their application.

Keywords: Article 21, data protection, dissent, fundamental right, India, privacy

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Authors: Abraham Terán Salcedo, Didier Samayoa Ochoa

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This work presents a numerical implementation of a method for estimating the box-counting dimension of self-avoiding curves on a planar space, fractal objects captured on digital images; this method is named fractioning estimator. Classical methods of digital image processing, such as noise filtering, contrast manipulation, and thresholding, among others, are used in order to obtain binary images that are suitable for performing the necessary computations of the fractioning estimator. A user interface is developed for performing the image processing operations and testing the fractioning estimator on different captured images of real-life fractal objects. To analyze the results, the estimations obtained through the fractioning estimator are compared to the results obtained through other methods that are already implemented on different available software for computing and estimating the box-counting dimension.

Keywords: box-counting, digital image processing, fractal dimension, numerical method

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Authors: Tomy Prihananto, Damar Apri Sudarmadi

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Indonesia recognizes the right to privacy as a human right. Indonesia provides legal protection against data management activities because the protection of personal data is a part of human rights. This paper aims to describe the arrangement of data management and data management in Indonesia. This paper is a descriptive research with qualitative approach and collecting data from literature study. Results of this paper are comprehensive arrangement of data that have been set up as a technical requirement of data protection by encryption methods. Arrangements on encryption and protection of personal data are mutually reinforcing arrangements in the protection of personal data. Indonesia has two important and immediately enacted laws that provide protection for the privacy of information that is part of human rights.

Keywords: Indonesia, protection, personal data, privacy, human rights, encryption

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Authors: Nicole Christiansen, Hanne Marie Motzfeldt

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In recent years, more and more HR professionals have been using cyber-vetting in job recruitment in an effort to find the perfect match for the company. These practices are growing rapidly, accessing a vast amount of data from social networks, some of which is privileged and protected information. Thus, there is a risk that the right to privacy is becoming a duty to manage your private data. This paper investigates to which degree a job applicant's fundamental rights are protected adequately in current and future legislation in the EU. This paper argues that current data protection regulations and forthcoming regulations on the use of AI ensure sufficient protection. However, even though the regulation on paper protects employees within the EU, the recruitment sector may not pay sufficient attention to the regulation as it not specifically targeting this area. Therefore, the lack of specific labor and employment regulation is a concern that the social partners should attend to.

Keywords: AI, cyber vetting, data protection, job recruitment, online privacy

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Authors: Amir Rashid

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Cloud Computing frameworks empower organizations to cut expenses by outsourcing computation resources on-request. As of now, customers of Cloud service providers have no methods for confirming the privacy and ownership of their information and data. To address this issue we propose the platform of a trusted cloud computing program (TCCP). TCCP empowers Infrastructure as a Service (IaaS) suppliers, for example, Amazon EC2 to give a shout box execution condition that ensures secret execution of visitor virtual machines. Also, it permits clients to bear witness to the IaaS supplier and decide if the administration is secure before they dispatch their virtual machines. This paper proposes a Trusted Cloud Computing Platform (TCCP) for guaranteeing the privacy and trustworthiness of computed data that are outsourced to IaaS service providers. The TCCP gives the deliberation of a shut box execution condition for a client's VM, ensuring that no cloud supplier's authorized manager can examine or mess up with its data. Furthermore, before launching the VM, the TCCP permits a client to dependably and remotely acknowledge that the provider at backend is running a confided in TCCP. This capacity extends the verification of whole administration, and hence permits a client to confirm the data operation in secure mode.

Keywords: cloud security, IaaS, cloud data privacy and integrity, hybrid cloud

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Authors: Hadi Farhadian, Homayoon Katibeh

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Groundwater inflow to the tunnels is one of the most important problems in tunneling operation. The objective of this study is the investigation of model dimension effects on tunnel inflow assessment in discontinuous rock masses using numerical modeling. In the numerical simulation, the model dimension has an important role in prediction of water inflow rate. When the model dimension is very small, due to low distance to the tunnel border, the model boundary conditions affect the estimated amount of groundwater flow into the tunnel and results show a very high inflow to tunnel. Hence, in this study, the two-dimensional universal distinct element code (UDEC) used and the impact of different model parameters, such as tunnel radius, joint spacing, horizontal and vertical model domain extent has been evaluated. Results show that the model domain extent is a function of the most significant parameters, which are tunnel radius and joint spacing.

Keywords: water inflow, tunnel, discontinues rock, numerical simulation

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Authors: Lorna Goulden, Kai M. Hermsen, Jari Isohanni, Mirko Ross, Jef Vanbockryck

Abstract:

This article introduces disposable identities, with reference use cases and explores possible technical approaches. The proposed approach, when fully developed as an open-source toolkit, enables developers of mobile or web apps to employ a self-sovereign identity and data privacy framework, in order to rebuild trust in digital services by providing greater transparency, decentralized control, and GDPR compliance. With a user interface for the management of self-sovereign identity, digital authorizations, and associated data-driven transactions, the advantage of Disposable Identities is that they may also contain verifiable data such as the owner’s photograph, official or even biometric identifiers for more proactive prevention of identity abuse. These Disposable Identities designed for decentralized privacy management can also be time, purpose and context-bound through a secure digital contract; with verification functionalities based on tamper-proof technology.

Keywords: dentity, trust, self-sovereign, disposable identity, privacy toolkit, decentralised identity, verifiable credential, cybersecurity, data driven business, PETs, GDPRdentity, trust, self-sovereign, disposable identity, privacy toolkit, decentralised identity, verifiable credential, cybersecurity, data driven business, PETs, GDPRI

Procedia PDF Downloads 192

Authors: Rimmy Yadav, Anmol Preet Kaur

Abstract:

Big Data has demonstrated the vast potential in streamlining, deciding, spotting business drifts in different fields, for example, producing, fund, Information Technology. This paper gives a multi-disciplinary diagram of the research issues in enormous information and its procedures, instruments, and system identified with the privacy, data storage management, network and energy utilization, adaptation to non-critical failure and information representations. Other than this, result difficulties and openings accessible in this Big Data platform have made.

Keywords: big data, privacy, data management, network and energy consumption

Procedia PDF Downloads 277

Authors: Abdelbaky Abouzeid

Abstract:

The study aimed at determining the effect of using the active learning on achievement and attitudes toward studying the human rights course for the Bahrain Teachers College students and the extent to which any differences of statistical significance according to gender and section can exist. To achieve the objectives of the study, the researcher developed and implemented research tools such as academic achievement test and the scale of attitudes towards the study of the Human Rights Course. The scale of attitudes towards Human Rights was constructed of 40 items investigating four dimensions; the cognitive dimension, the behavioral dimension, the affective dimension, and course quality dimension. The researcher then applied some of the active learning strategies in teaching this course to all students of the first year of the Bahrain Teachers College (102 male and female students) after excluding two students who did not complete the course requirements. Students were divided into five groups. These strategies included interactive lecturing, presentations, role playing, group projects, simulation, brainstorming, concept maps and mind maps, reflection and think-pair-share. The course was introduced to students during the second semester of the academic year 2016-2017. The study findings revealed that the use of active learning strategies affected the achievement of students of Bahrain Teachers College in the Human Rights course. The results of the T-test showed statistically significant differences on the pre-test and post-test in favor of the post-test. No statistically significant differences in the achievement of students according to the section and gender were found. The results also indicated that the use of active learning strategies had a positive effect on students' attitudes towards the study of the Human Rights Course on all the scale’s items. The general average reached (4.26) and the percentage reached (85.19%). Regarding the effect of using active learning strategies on students’ attitudes towards all the four dimensions of the scale, the study concluded that the behavioral dimension came first; the quality of the course came second, the cognitive dimension came third and in the fourth place came the affective dimension. No statistically significant differences in the attitude towards studying the Human Rights Course for the students according to their sections or gender were found. Based on the findings of the study, the researchers suggested some recommendations that can contribute to the development of teaching Human Rights Course at the University of Bahrain.

Keywords: attitudes, academic achievement, human rights, behavioral dimension, cognitive dimension, affective dimension, quality of the course

Procedia PDF Downloads 178