scholarly journals Protecting Metadata of Access Indicator and Region of Interests for Image Files

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
JeongYeon Kim

With popularity of social network services, the security and privacy issues over shared contents receive many attentions. Besides, multimedia files have additional concerns of copyright violation or illegal usage to share over communication networks. For image file management, JPEG group develops new image file format to enhance security and privacy features. Adopting a box structure with different application markers, new standards for privacy and security provide a concept of replacement substituting a private part of the original image or metadata with an alternative public data. In this paper, we extend data protection features of new JPEG formats to remote access control as a metadata. By keeping location information of access control data as a metadata in image files, the image owner can allow or deny other’s data consumption regardless where the media file is. License issue also can be resolved by applying new access control schemes, and we present how new formats protect commercial image files against unauthorized accesses.

Author(s):  
Kayalvili S ◽  
Sowmitha V

Cloud computing enables users to accumulate their sensitive data into cloud service providers to achieve scalable services on-demand. Outstanding security requirements arising from this means of data storage and management include data security and privacy. Attribute-based Encryption (ABE) is an efficient encryption system with fine-grained access control for encrypting out-sourced data in cloud computing. Since data outsourcing systems require flexible access control approach Problems arises when sharing confidential corporate data in cloud computing. User-Identity needs to be managed globally and access policies can be defined by several authorities. Data is dual encrypted for more security and to maintain De-Centralization in Multi-Authority environment.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xiaofeng Lu ◽  
Songbing Fu ◽  
Cheng Jiang ◽  
Pietro Lio

IoT technology has been widely valued and applied, and the resulting massive IoT data brings many challenges to the traditional centralized data management, such as performance, privacy, and security challenges. This paper proposes an IoT data access control scheme that combines attribute-based encryption (ABE) and blockchain technology. Symmetric encryption and ABE algorithms are utilized to realize fine-grained access control and ensure the security and openness of IoT data. Moreover, blockchain technology is combined with distributed storage to solve the storage bottleneck of blockchain systems. Only the hash values of the data, the hash values of the ciphertext location, the access control policy, and other important information are stored on the blockchain. In this scheme, smart contract is used to implement access control. The results of experiments demonstrate that the proposed scheme can effectively protect the security and privacy of IoT data and realize the secure sharing of data.


2021 ◽  
Vol 4 ◽  
Author(s):  
Lavanya Elluri ◽  
Aritran Piplai ◽  
Anantaa Kotal ◽  
Anupam Joshi ◽  
Karuna Pande Joshi

The entire scientific and academic community has been mobilized to gain a better understanding of the COVID-19 disease and its impact on humanity. Most research related to COVID-19 needs to analyze large amounts of data in very little time. This urgency has made Big Data Analysis, and related questions around the privacy and security of the data, an extremely important part of research in the COVID-19 era. The White House OSTP has, for example, released a large dataset of papers related to COVID research from which the research community can extract knowledge and information. We show an example system with a machine learning-based knowledge extractor which draws out key medical information from COVID-19 related academic research papers. We represent this knowledge in a Knowledge Graph that uses the Unified Medical Language System (UMLS). However, publicly available studies rely on dataset that might have sensitive data. Extracting information from academic papers can potentially leak sensitive data, and protecting the security and privacy of this data is equally important. In this paper, we address the key challenges around the privacy and security of such information extraction and analysis systems. Policy regulations like HIPAA have updated the guidelines to access data, specifically, data related to COVID-19, securely. In the US, healthcare providers must also comply with the Office of Civil Rights (OCR) rules to protect data integrity in matters like plasma donation, media access to health care data, telehealth communications, etc. Privacy policies are typically short and unstructured HTML or PDF documents. We have created a framework to extract relevant knowledge from the health centers’ policy documents and also represent these as a knowledge graph. Our framework helps to understand the extent to which individual provider policies comply with regulations and define access control policies that enforce the regulation rules on data in the knowledge graph extracted from COVID-related papers. Along with being compliant, privacy policies must also be transparent and easily understood by the clients. We analyze the relative readability of healthcare privacy policies and discuss the impact. In this paper, we develop a framework for access control decisions that uses policy compliance information to securely retrieve COVID data. We show how policy compliance information can be used to restrict access to COVID-19 data and information extracted from research papers.


2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Peter Sungu Nyakomitta ◽  
Vincent Omollo Nyangaresi ◽  
Solomon Odhiambo Ogara

Wireless sensor networks convey mission critical data that calls for adequate privacy and security protection. To accomplish this objective, numerous intrusion detection schemes based on machine learning approaches have been developed. In addition, authentication and key agreements techniques have been developed using techniques such as elliptic curve cryptography, bilinear pairing operations, biometrics, fuzzy verifier and Rabin cryptosystems. However, these schemes have either high false positive rates, high communication, computation, storage or energy requirements, all of which are not ideal for battery powered sensor nodes. Moreover, majority of these algorithms still have some security and privacy challenges that render them susceptible to various threats. In this paper, a WSN authentication algorithm is presented that is shown to be robust against legacy WSN privacy and security attacks such as sidechannel, traceability, offline guessing, replay and impersonations. From a performance perspective, the proposed algorithm requires the least computation overheads and average computation costs among its peers.


Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1663
Author(s):  
Adam Ibrahim Abdi ◽  
Fathy Elbouraey Eassa ◽  
Kamal Jambi ◽  
Khalid Almarhabi ◽  
Abdullah Saad AL-Malaise AL-Ghamdi

The Internet of Things paradigm is growing rapidly. In fact, controlling this massive growth of IoT globally raises new security and privacy issues. The traditional access control mechanisms provide security to IoT systems such as DAC (discretionary access control) and mandatory access control (MAC). However, these mechanisms are based on central authority management, which raises some issues such as absence of scalability, single point of failure, and lack of privacy. Recently, the decentralized and immutable nature of blockchain technology integrated with access control can help to overcome privacy and security issues in the IoT. This paper presents a review of different access control mechanisms in IoT systems. We present a comparison table of reviewed access control mechanisms. The mechanisms’ scalability, distribution, security, user-centric, privacy and policy enforcing are compared. In addition, we provide access control classifications. Finally, we highlight challenges and future research directions in developing decentralized access control mechanisms for IoT systems.


2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S836-S836
Author(s):  
London Thompson ◽  
Csilla Farkas

Abstract In this research, we study the privacy and security capabilities provided by telehealth devices. Our aim is to evaluate how vulnerable these popular devices are in the presence of malicious cyber attackers. As older adults increasingly rely on telehealth devices, it is crucial that cybersecurity aspects of these devices are clearly communicated to them. Moreover, older adults frequently lack the technical expertise to evaluate the security and privacy capabilities of the devices. The lack of control over telehealth devices is a major concern for older adults. Older adults view certain limitations within these devices as decreasing their privacy and security. These limitations include the lack of control over accepting calls, taking screenshots, and assigning access privileges. For large scale adaptation of telehealth devices by older adults, it is crucial that these devices not only satisfy their intended purpose but also exhibit user friendly features and strong security and privacy capabilities. Modeling cyber threats against telehealth devices is not studied sufficiently . Malicious actors may compromise telehealth devices and create further threats to security and privacy of the users. In this research, we studied the cyber threats against telehealth devices. We built a threat model that ranks cyber threats based on their impact. We investigated how the operating system of popular devices supports access control. We found that none of the current technologies support location-based access control. We claim that this represents a major limitation and that supporting location-based access control is necessary to ensure users’ privacy in their own home.


10.29007/jlq6 ◽  
2019 ◽  
Author(s):  
Thabang Mofokeng

The technology devices introduced in recent years are not only vulnerable to Internet risks but are also unable to elevate the growth of B2C e-commerce. These concerns are particularly relevant today, as the world transitions into the Fourth Industrial Revolution. To date, existing research has largely focused on obstacles to customer loyalty. Studies have tested e-commerce models guided by the establishment of trusting, satisfied and loyal consumers in various international contexts. In South Africa, however, as an emerging market, there has been limited research on the success factors of online shopping.This study examines the influence of security and privacy on trust, seen as a moderator of customer satisfaction, which in turn, has an effect on loyalty towards websites. Based on an exhaustive review of literature, a conceptual model is proposed on the relationships between security and privacy on the one hand, and customer trust, satisfaction and loyalty on the other. A total of 250 structured, self-administered questionnaires was distributed to a purposively selected sample of respondents using face-to-face surveys in Johannesburg, South Africa. A multivariate data analysis technique was used to draw inferences from the data. With an 80.1% response rate, the findings showed that privacy and security do influence customer trust; security strongly influences customer trust and weakly influences satisfaction. In South Africa, customer loyalty towards websites is strongly determined by satisfaction and weakly determined by trust. Trust significantly moderates the effect of customer satisfaction on loyalty. The study implications and limitations are presented and future research directions are suggested.


2021 ◽  
Vol 20 (2) ◽  
pp. 1-24
Author(s):  
Stef Verreydt ◽  
Koen Yskout ◽  
Wouter Joosen

Electronic consent (e-consent) has the potential to solve many paper-based consent approaches. Existing approaches, however, face challenges regarding privacy and security. This literature review aims to provide an overview of privacy and security challenges and requirements proposed by papers discussing e-consent implementations, as well as the manner in which state-of-the-art solutions address them. We conducted a systematic literature search using ACM Digital Library, IEEE Xplore, and PubMed Central. We included papers providing comprehensive discussions of one or more technical aspects of e-consent systems. Thirty-one papers met our inclusion criteria. Two distinct topics were identified, the first being discussions of e-consent representations and the second being implementations of e-consent in data sharing systems. The main challenge for e-consent representations is gathering the requirements for a “valid” consent. For the implementation papers, many provided some requirements but none provided a comprehensive overview. Blockchain is identified as a solution to transparency and trust issues in traditional client-server systems, but several challenges hinder it from being applied in practice. E-consent has the potential to grant data subjects control over their data. However, there is no agreed-upon set of security and privacy requirements that must be addressed by an e-consent platform. Therefore, security- and privacy-by-design techniques should be an essential part of the development lifecycle for such a platform.


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