scholarly journals TrustChain: A Privacy Preserving Blockchain with Edge Computing

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Upul Jayasinghe ◽  
Gyu Myoung Lee ◽  
Áine MacDermott ◽  
Woo Seop Rhee
Keyword(s):  
Real Time ◽  
Personal Data ◽  
Privacy Preserving ◽  
Edge Computing ◽  
Security And Privacy ◽  
Privacy Concerns ◽  
Massive Scale ◽  
Potential Alternative ◽  
Iot Devices ◽  
Scarcity Of Resources

Recent advancements in the Internet of Things (IoT) has enabled the collection, processing, and analysis of various forms of data including the personal data from billions of objects to generate valuable knowledge, making more innovative services for its stakeholders. Yet, this paradigm continuously suffers from numerous security and privacy concerns mainly due to its massive scale, distributed nature, and scarcity of resources towards the edge of IoT networks. Interestingly, blockchain based techniques offer strong countermeasures to protect data from tampering while supporting the distributed nature of the IoT. However, the enormous amount of energy consumption required to verify each block of data make it difficult to use with resource-constrained IoT devices and with real-time IoT applications. Nevertheless, it can expose the privacy of the stakeholders due to its public ledger system even though it secures data from alterations. Edge computing approaches suggest a potential alternative to centralized processing in order to populate real-time applications at the edge and to reduce privacy concerns associated with cloud computing. Hence, this paper suggests the novel privacy preserving blockchain called TrustChain which combines the power of blockchains with trust concepts to eliminate issues associated with traditional blockchain architectures. This work investigates how TrustChain can be deployed in the edge computing environment with different levels of absorptions to eliminate delays and privacy concerns associated with centralized processing and to preserve the resources in IoT networks.

IoT in Healthcare

2020 ◽  
pp. 1-22
Author(s):  
V. Jeevika Tharini ◽  
S. Vijayarani
Keyword(s):  
Health Sector ◽  
Information Privacy ◽  
Security And Privacy ◽  
Healthcare Industry ◽  
Security Attacks ◽  
Privacy And Security ◽  
Privacy Concerns ◽  
Security Issues ◽  
Iot Devices ◽  
Individual Information

One of the best-known features of IoT is automation. Because of this, IoT is a much-needed field for many applications, namely emergency and healthcare domains. IoT has made many revolutionary changes in the healthcare industry. IoT paves the way to numerous advancements for healthcare. The possibilities of IoT have reached their peak in the commercial industry and health sector. In recent years, serious concerns have been raised over the control and access of one's individual information. Privacy and security of the IoT devices can be compromised by intruders. Apart from the numerous benefits of IoTs, there are several security and privacy concerns to consider. A brief overview of different kinds of security attacks, solution for the attacks, privacy and security issues are discussed in this chapter.

scholarly journals Internet of Things: A Comprehensive Study on Machine Learning-based Intrusion Detection approaches

2021 ◽  
Author(s):  
Priyanka Gupta ◽  
Lokesh Yadav ◽  
Deepak Singh Tomar
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Real Time ◽  
Detection System ◽  
Research Work ◽  
Security And Privacy ◽  
Iot Security ◽  
Advantages And Disadvantages ◽  
Iot Devices

The Internet of Things (IoT) connects billions of interconnected devices that can exchange information with each other with minimal user intervention. The goal of IoT to become accessible to anyone, anytime, and anywhere. IoT has engaged in multiple fields, including education, healthcare, businesses, and smart home. Security and privacy issues have been significant obstacles to the widespread adoption of IoT. IoT devices cannot be entirely secure from threats; detecting attacks in real-time is essential for securing devices. In the real-time communication domain and especially in IoT, security and protection are the major issues. The resource-constrained nature of IoT devices makes traditional security techniques difficult. In this paper, the research work carried out in IoT Intrusion Detection System is presented. The Machine learning methods are explored to provide an effective security solution for IoT Intrusion Detection systems. Then discussed the advantages and disadvantages of the selected methodology. Further, the datasets used in IoT security are also discussed. Finally, the examination of the open issues and directions for future trends are also provided.

scholarly journals Staying at the Edge of Privacy: Edge Computing and Impersonal Extraction

2020 ◽  
Vol 8 (2) ◽  
pp. 270-279 ◽  
Author(s):  
Luke Munn
Keyword(s):  
Real Time ◽  
Personal Data ◽  
Edge Computing ◽  
License Plate ◽  
Process Data ◽  
Detection Model ◽  
Major Shift ◽  
Self Driving Cars ◽  
A Site ◽  
Key Questions

From self-driving cars to smart city sensors, billions of devices will be connected to networks in the next few years. These devices will collect vast amounts of data which needs to be processed in real-time, overwhelming centralized cloud architectures. To address this need, the industry seeks to process data closer to the source, driving a major shift from the cloud to the ‘edge.’ This article critically investigates the privacy implications of edge computing. It outlines the abilities introduced by the edge by drawing on two recently published scenarios, an automated license plate reader and an ethnic facial detection model. Based on these affordances, three key questions arise: what kind of data will be collected, how will this data be processed at the edge, and how will this data be ‘completed’ in the cloud? As a site of intermediation between user and cloud, the edge allows data to be extracted from individuals, acted on in real-time, and then abstracted or sterilized, removing identifying information before being stored in conventional data centers. The article thus argues that edge affordances establish a fundamental new ‘privacy condition’ while sidestepping the safeguards associated with the ‘privacy proper’ of personal data use. Responding effectively to these challenges will mean rethinking person-based approaches to privacy at both regulatory and citizen-led levels.

scholarly journals A Research on impact of Blockchain in Healthcare

2019 ◽  
Vol 8 (9S2) ◽  
pp. 35-40
Keyword(s):  
Third Party ◽  
Security And Privacy ◽  
Privacy Concerns ◽  
Blockchain Technology ◽  
Location Sharing ◽  
Authentication And Authorization ◽  
Promising Solution ◽  
Iot Devices ◽  
Remote Patient ◽  
Education Science

Blockchain refers to a distributed ledger technology that represents an innovation in recording and sharing information without the need for a trusted third party. Blockchain technology offers new tools for security and privacy concerns. Marching towards digitization and analytics, this technology emerges as a promising solution for authentication and authorization issues. It sounds so amazing that this technology that originated with cryptocurrencies could not only be applied in digital contracts, financial and public records, and property ownership but also in medicine, education, science and so on. The use case of this technology springs up in every possible direction. This article first analyses the need for this breakthrough technology and explains how this technology works. This work presents a review on various types of blockchain, the consensus mechanisms used, their advantages and limitations. It provides an overview on the various use cases of this technology. This work mainly focuses on its application in Healthcare. The goal of this article is to analyze the usage of Blockchain technology in various fields of Healthcare such as Electronic Health Record, Health Insurance, Biomedical Research, Drug Supply, Medical Education, Remote Patient Monitoring, Interoperability, Location Sharing etc., It investigates the current research trends and finds the gaps and limitations of these approaches. Moreover, it proposes some enhancements to fill in the gaps in the present approach. This work also analyses the importance of Wearable Internet of Things (IoT) devices in HealthCare and the integration of these devices with Blockchain. Finally, this work concludes by comparing Blockchain 3.0 with previous versions.

scholarly journals Preserving Data Privacy in the Internet of Medical Things Using Dual Signature ECDSA

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Maria-Dolores Cano ◽  
Antonio Cañavate-Sanchez
Keyword(s):  
Elliptic Curve ◽  
Private Information ◽  
Data Privacy ◽  
Edge Computing ◽  
Security And Privacy ◽  
The Internet ◽  
Consumer Privacy ◽  
Digital Signature Algorithm ◽  
Internet Of Medical Things ◽  
Iot Devices

The disclosure of personal and private information is one of the main challenges of the Internet of Medical Things (IoMT). Most IoMT-based services, applications, and platforms follow a common architecture where wearables or other medical devices capture data that are forwarded to the cloud. In this scenario, edge computing brings new opportunities to enhance the operation of IoMT. However, despite the benefits, the inherent characteristics of edge computing require countermeasures to address the security and privacy issues that IoMT gives rise to. The restrictions of IoT devices in terms of battery, memory, hardware resources, or computing capabilities have led to a common agreement for the use of elliptic curve cryptography (ECC) with hardware or software implementations. As an example, the elliptic curve digital signature algorithm (ECDSA) is widely used by IoT devices to compute digital signatures. On the other hand, it is well known that dual signature has been an effective method to provide consumer privacy in classic e-commerce services. This article joins both approaches. It presents a novel solution to enhanced security and the preservation of data privacy in communications between IoMT devices and the cloud via edge computing devices. While data source anonymity is achieved from the cloud perspective, integrity and origin authentication of the collected data is also provided. In addition, computational requirements and complexity are kept to a minimum.

Trust in an Enterprise World

2019 ◽  
pp. 2145-2167
Author(s):  
Fotios I. Gogoulos ◽  
Anna Antonakopoulou ◽  
Georgios V. Lioudakis ◽  
Dimitra I. Kaklamani ◽  
Iakovos S. Venieris
Keyword(s):  
Information Management ◽  
Business Models ◽  
Management Practices ◽  
Personal Data ◽  
Security And Privacy ◽  
Protection Measures ◽  
Privacy Concerns ◽  
Modern Enterprise ◽  
Individual Participation ◽  
Corporate Information

Web 2.0 technologies have fundamentally reshaped everyday users' perceptions regarding online services by strengthening the importance of individual participation. This profound change is expanding to substantially affect modern enterprise operations and especially corporate information management practices. Well-established business models are upgraded to capture value from the establishment of dynamic coalitions and virtual organizations among remote stakeholders. However, these collaboration formulations dictate the concentration, use, and circulation of corporate information and sensitive personal data, and thus ignite severe security and privacy concerns. Enterprises against this background are more than willing to invest in terms cost and time in order to enforce the necessary countermeasures and thus build and maintain the trustworthiness of involved operations. This chapter studies how legislation and inherent characteristics of this new collaboration paradigm affect the qualities of trust and highlights prominent features of security and privacy protection measures that can deal with emerging trust issues.

Privacy Dangers of Wearables and the Internet of Things

2016 ◽  
pp. 379-402 ◽  
Author(s):  
Scott Amyx
Keyword(s):  
Data Protection ◽  
Data Privacy ◽  
Security And Privacy ◽  
Employee Privacy ◽  
Privacy Concerns ◽  
Business Operations ◽  
Managerial Implications ◽  
Iot Devices ◽  
Privacy Issues ◽  
The Internet Of Things

This chapter identifies concerns about, and the managerial implications of, data privacy issues related to wearables and the IoT; it also offers some enterprise solutions to the complex concerns arising from the aggregation of the massive amounts of data derived from wearables and IoT devices. Consumer and employee privacy concerns are elucidated, as are the problems facing managers as data management and security become an important part of business operations. The author provides insight into how companies are currently managing data as well as some issues related to data security and privacy. A number of suggestions for improving the approach to data protection and addressing concerns about privacy are included. This chapter also examines trending issues in the areas of data protection and the IoT, and contains thought-provoking discussion questions pertaining to business, wearables/IoT data, and privacy issues.

Trust in an Enterprise World

2019 ◽  
pp. 1442-1463
Author(s):  
Fotios I. Gogoulos ◽  
Anna Antonakopoulou ◽  
Georgios V. Lioudakis ◽  
Dimitra I. Kaklamani ◽  
Iakovos S. Venieris
Keyword(s):  
Information Management ◽  
Business Models ◽  
Management Practices ◽  
Personal Data ◽  
Security And Privacy ◽  
Protection Measures ◽  
Privacy Concerns ◽  
Modern Enterprise ◽  
Individual Participation ◽  
Corporate Information

Web 2.0 technologies have fundamentally reshaped everyday users' perceptions regarding online services by strengthening the importance of individual participation. This profound change is expanding to substantially affect modern enterprise operations and especially corporate information management practices. Well-established business models are upgraded to capture value from the establishment of dynamic coalitions and virtual organizations among remote stakeholders. However, these collaboration formulations dictate the concentration, use, and circulation of corporate information and sensitive personal data, and thus ignite severe security and privacy concerns. Enterprises against this background are more than willing to invest in terms cost and time in order to enforce the necessary countermeasures and thus build and maintain the trustworthiness of involved operations. This chapter studies how legislation and inherent characteristics of this new collaboration paradigm affect the qualities of trust and highlights prominent features of security and privacy protection measures that can deal with emerging trust issues.

A Secure and Privacy-Preserving Approach to Protect User Data across Cloud based Online Social Networks

2021 ◽  
pp. 560-585
Author(s):  
Neelu khare ◽  
Kumaran U.
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Data Access ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Privacy Concerns ◽  
Attribute Based Encryption ◽  
User Data ◽  
Trapdoor Function

The tremendous growth of social networking systems enables the active participation of a wide variety of users. This has led to an increased probability of security and privacy concerns. In order to solve the issue, the article defines a secure and privacy-preserving approach to protect user data across Cloud-based online social networks. The proposed approach models social networks as a directed graph, such that a user can share sensitive information with other users only if there exists a directed edge from one user to another. The connectivity between data users data is efficiently shared using an attribute-based encryption (ABE) with different data access levels. The proposed ABE technique makes use of a trapdoor function to re-encrypt the data without the use of proxy re-encryption techniques. Experimental evaluation states that the proposed approach provides comparatively better results than the existing techniques.

Privacy Preserving in Smart Cities Using Various Computing Technologies

2022 ◽  
pp. 47-54
Author(s):  
T. N. Gayathri ◽  
M. Rajasekharababu
Keyword(s):  
Real Time ◽  
Smart Cities ◽  
Privacy Preserving ◽  
Synthetic Dataset ◽  
Smart Environment ◽  
Sensitive Data ◽  
Daily Lives ◽  
Simulation Results ◽  
Iot Devices ◽  
High Possibility

IoT has influenced our daily lives through various applications. The high possibility of sensing and publishing sensitive data in the smart environment leads to significant issues: (1) privacy-preserving and (2) real-time services. Privacy is a complex and a subjective notion as its understanding and perception differ among individuals, hence the observation that current studies lack addressing these challenges. This chapter proposes a new privacy-preserving method for IoT devices in the smart city by leveraging ontology, a data model, at the edge of the network. Based on the simulation results using Protege and Visual Studio on a synthetic dataset, the authors find that the solution provides privacy at real-time while addressing heterogeneity issue so that many IoT devices can afford it. Thus, the proposed solution can be widely used for smart cities.

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