scholarly journals End user concern about security and privacy threats

2007 ◽  
Author(s):  
Joshua B. Gross ◽  
Mary Beth Rosson
Keyword(s):  
Security And Privacy ◽  
End User ◽  
Privacy Threats

Updates in deep learning research in ophthalmology

2021 ◽  
Vol 135 (20) ◽  
pp. 2357-2376
Author(s):  
Wei Yan Ng ◽  
Shihao Zhang ◽  
Zhaoran Wang ◽  
Charles Jit Teng Ong ◽  
Dinesh V. Gunasekeran ◽  
...  
Keyword(s):  
Deep Learning ◽  
Critical Role ◽  
Disease Classification ◽  
Age Related Macular Degeneration ◽  
Security And Privacy ◽  
Generative Adversarial Networks ◽  
End User ◽  
Ethical Assessment ◽  
Age Related ◽  
Patient Consent

Abstract Ophthalmology has been one of the early adopters of artificial intelligence (AI) within the medical field. Deep learning (DL), in particular, has garnered significant attention due to the availability of large amounts of data and digitized ocular images. Currently, AI in Ophthalmology is mainly focused on improving disease classification and supporting decision-making when treating ophthalmic diseases such as diabetic retinopathy, age-related macular degeneration (AMD), glaucoma and retinopathy of prematurity (ROP). However, most of the DL systems (DLSs) developed thus far remain in the research stage and only a handful are able to achieve clinical translation. This phenomenon is due to a combination of factors including concerns over security and privacy, poor generalizability, trust and explainability issues, unfavorable end-user perceptions and uncertain economic value. Overcoming this challenge would require a combination approach. Firstly, emerging techniques such as federated learning (FL), generative adversarial networks (GANs), autonomous AI and blockchain will be playing an increasingly critical role to enhance privacy, collaboration and DLS performance. Next, compliance to reporting and regulatory guidelines, such as CONSORT-AI and STARD-AI, will be required to in order to improve transparency, minimize abuse and ensure reproducibility. Thirdly, frameworks will be required to obtain patient consent, perform ethical assessment and evaluate end-user perception. Lastly, proper health economic assessment (HEA) must be performed to provide financial visibility during the early phases of DLS development. This is necessary to manage resources prudently and guide the development of DLS.

scholarly journals A survey of secure middleware for the Internet of Things

2017 ◽  
Author(s):  
Paul Fremantle ◽  
Philip Scott
Keyword(s):  
Internet Of Things ◽  
Literature Review ◽  
Security And Privacy ◽  
The Internet ◽  
Privacy Threats ◽  
Strong Focus ◽  
Security Properties ◽  
Iot Platforms ◽  
The Internet Of Things ◽  
Structured Literature Review

The rapid growth of small Internet connected devices, known as the Internet of Things (IoT), is creating a new set of challenges to create secure, private infrastructures. This paper reviews the current literature on the challenges and approaches to security and privacy in the Internet of Things, with a strong focus on how these aspects are handled in IoT middleware. We focus on IoT middleware because many systems are built from existing middleware and these inherit the underlying security properties of the middleware framework. The paper is composed of three main sections. Firstly, we propose a matrix of security and privacy threats for IoT. This matrix is used as the basis of a widespread literature review aimed at identifying requirements on IoT platforms and middleware. Secondly, we present a structured literature review of the available middleware and how security is handled in these middleware approaches. We utilise the requirements from the first phase to evaluate. Finally, we draw a set of conclusions and identify further work in this area.

scholarly journals A survey of secure middleware for the Internet of Things

2017 ◽  
Author(s):  
Paul Fremantle ◽  
Philip Scott
Keyword(s):  
Internet Of Things ◽  
Literature Review ◽  
Security And Privacy ◽  
The Internet ◽  
Privacy Threats ◽  
Strong Focus ◽  
Security Properties ◽  
Iot Platforms ◽  
The Internet Of Things ◽  
Structured Literature Review

The rapid growth of small Internet connected devices, known as the Internet of Things (IoT), is creating a new set of challenges to create secure, private infrastructures. This paper reviews the current literature on the challenges and approaches to security and privacy in the Internet of Things, with a strong focus on how these aspects are handled in IoT middleware. We focus on IoT middleware because many systems are built from existing middleware and these inherit the underlying security properties of the middleware framework. The paper is composed of three main sections. Firstly, we propose a matrix of security and privacy threats for IoT. This matrix is used as the basis of a widespread literature review aimed at identifying requirements on IoT platforms and middleware. Secondly, we present a structured literature review of the available middleware and how security is handled in these middleware approaches. We utilise the requirements from the first phase to evaluate. Finally, we draw a set of conclusions and identify further work in this area.

Impact of Big Data on Security

2018 ◽  
pp. 326-350
Author(s):  
Kasarapu Ramani
Keyword(s):  
Big Data ◽  
Defense Mechanisms ◽  
Security And Privacy ◽  
End User ◽  
Sensitive Data ◽  
Insider Threats ◽  
Security Issues ◽  
Commercial Importance ◽  
Multi Level ◽  
Access Privileges

Big data has great commercial importance to major businesses, but security and privacy challenges are also daunting this storage, processing, and communication. Big data encapsulate organizations' most important and sensitive data with multi-level complex implementation. The challenge for any organization is securing access to the data while allowing end user to extract valuable insights. Unregulated access privileges to the big data leads to loss or theft of valuable and sensitive. Privilege escalation leads to insider threats. Also, the computing architecture of big data is not focusing on session recording; therefore, it is becoming a challenge to identify potential security issues and to take remedial and mitigation mechanisms. Therefore, various big data security issues and their defense mechanisms are discussed in this chapter.

The Security and Privacy Protection in RFID

2012 ◽  
Vol 430-432 ◽  
pp. 1755-1758
Author(s):  
Chun Chang Fu ◽  
Wei Lin He
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Security And Privacy ◽  
Automatic Identification ◽  
Present System ◽  
Privacy Threats ◽  
Wide Range ◽  
Frequency Identification ◽  
Radio Frequency Identification Technology ◽  
Privacy Issues

Radio frequency identification technology is an automatic identification technology started in the 1990s. With the RFID technology in a wide range of applications in different areas, it offers the security and privacy threats and caused a great deal of attention. At present, system security and privacy issues have become one of the main factors restricted the wide application of radio frequency identification technology. Aimed at the problem, this article discussed the safety of the privacy issues.

scholarly journals A State-of-the-Art Review on the Security of Mainstream IoT Wireless PAN Protocol Stacks

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 579 ◽  
Author(s):  
Georgios Kambourakis ◽  
Constantinos Kolias ◽  
Dimitrios Geneiatakis ◽  
Georgios Karopoulos ◽  
Georgios Michail Makrakis ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Relevant Literature ◽  
Transportation Systems ◽  
Security And Privacy ◽  
Area Network ◽  
Privacy Concerns ◽  
Privacy Threats ◽  
Heterogeneous Nature ◽  
The Internet Of Things ◽  
Significant Attention

Protocol stacks specifically designed for the Internet of Things (IoT) have become commonplace. At the same time, security and privacy concerns regarding IoT technologies are also attracting significant attention given the risks that are inherently associated with the respective devices and their numerous applications, ranging from healthcare, smart homes, and cities, to intelligent transportation systems and industrial automation. Considering the still heterogeneous nature of the majority of IoT protocols, a major concern is to find common references for investigating and analyzing their security and privacy threats. To this end, and on top of the current literature, this work provides a comprehensive, vis-à-vis comparison of the security aspects of the thus far most widespread IoT Wireless Personal Area Network (WPAN) protocols, namely BLE, Z-Wave, ZigBee, Thread, and EnOcean. A succinct but exhaustive review of the relevant literature from 2013 up to now is offered as a side contribution.

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