Private Memoirs of IoT Devices: Safeguarding User Privacy in the IoT Era

Chen, Dong; Bovornkeeratiroj, Phuthipong; Irwin, David; Shenoy, Prashant

doi:10.1109/icdcs.2018.00133

Cited by 22 publications

(10 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…PSNR(X, Y) = 10 log 10 (2 n − 1) 2 MSE(X, Y) (7) where MSE means mean square error operation, and n denotes the number of bits per pixel (generally n = 8). 2) Structural Similarity Index (SSIM): As a common image standard evaluation index, SSIM can evaluate the similarity between two images from different perspectives, including brightness, contrast, and structure.…”

Section: ) Video Restorationmentioning

confidence: 99%

Real-Time Mask Identification for COVID-19: An Edge-Computing-Based Deep Learning Framework

Kong

Wang

et al. 2021

IEEE Internet Things J.

View full text Add to dashboard Cite

During the outbreak of the Coronavirus disease 2019 (COVID-19), while bringing various serious threats to the world, it reminds us that we need to take precautions to control the transmission of the virus. The rise of the Internet of Medical Things (IoMT) has made related data collection and processing, including healthcare monitoring systems, more convenient on the one hand, and requirements of public health prevention are also changing and more challengeable on the other hand. One of the most effective nonpharmaceutical medical intervention measures is mask wearing. Therefore, there is an urgent need for an automatic real-time mask detection method to help prevent the public epidemic. In this article, we put forward an edge computingbased mask (ECMask) identification framework to help public health precautions, which can ensure real-time performance on the low-power camera devices of buses. Our ECMask consists of three main stages: 1) video restoration; 2) face detection; and 3) mask identification. The related models are trained and evaluated on our bus drive monitoring data set and public data set. We construct extensive experiments to validate the good performance based on real video data, in consideration of detection accuracy and execution time efficiency of the whole video analysis, which have valuable application in COVID-19 prevention.

show abstract

Section: ) Video Restorationmentioning

confidence: 99%

Real-Time Mask Identification for COVID-19: An Edge-Computing-Based Deep Learning Framework

Kong

Wang

et al. 2021

IEEE Internet Things J.

View full text Add to dashboard Cite

show abstract

“…Privacy: IoT vendors mostly conduct a massive data collection strategy to produce useful insights for their services. They often perform this operation by sacrificing users' privacy [13], threatening the trust and usability of overall IoT systems. Blockchain cannot fully solve this problem; however, it can help users achieve pseudonymity.…”

Section: Non-repudiationmentioning

confidence: 99%

Blockchain-Based Continued Integrity Service for IoT Big Data Management: A Comprehensive Design

Oktian

Lee

2020

Electronics

View full text Add to dashboard Cite

The state-of-the-art centralized Internet of Things (IoT) data flow pipeline has started aging since it cannot cope with the vast number of newly connected IoT devices. As a result, the community begins the transition to a decentralized pipeline to encourage data and resource sharing. However, the move is not trivial. With many instances allocating data or service arbitrarily, how can we guarantee the correctness of IoT data or processes that other parties offer. Furthermore, in case of dispute, how can the IoT data assist in determining which party is guilty of faulty behavior. Finally, the number of Service Level Agreement (SLA) increases as the number of sharing grows. The problem then becomes how we can provide a natural SLA generation and verification that we can automate instead of going through a manual and tedious legalization process through a trusted third party. In this paper, we explore blockchain solutions to answer those issues and propose continued data integrity services for IoT big data management. Specifically, we design five integrity protocols across three phases of IoT operations—during the transmission of IoT data (data in transit), when we physically store the data in the database (data at rest), and at the time of data processing (data in process). In each phase, we first lay out our motivations and survey the related blockchain solutions from the literature. We then use curated papers from our surveys as building blocks in designing the protocol. Using our proposal, we augment the overall value of IoT data and commands, generated in the IoT system, as they are now tamper-proof, verifiable, non-repudiable, and more robust.

show abstract

“…IoT devices can leak sensitive information, as shown by recent studies [96]. For example, the data collected by smart switches, smart thermostats, and smart power meters can leak information, including information about whether a home is being occupied [97], [98].…”

Section: Security and Privacy In The Internet Of Thingsmentioning

confidence: 99%

“…rooftop solar panels) can reveal home location [99], [100]. In solar energy analytics, energy data can leak location information, which may cause location-based privacy attacks [96]. In critical fields (military, as an example), the privacy threat is very dangerous, because IoT devices can leak sensitive information that the enemy can exploit.…”

Section: Security and Privacy In The Internet Of Thingsmentioning

confidence: 99%

“…For instance, Strava fitness app posts a map of its users' activity on the internet. Security researchers showed that this public activity map imposes a severe threat to the U.S national security by indirectly revealing the locations and behaviors or attitudes of the U.S military bases and personnel in Syria and Iraq [96], [101]. In healthcare, many IoT applications were developed to serve this sector, including apps used for sensing glucose level, monitoring blood pressure, monitoring ECG, etc.…”

Section: Security and Privacy In The Internet Of Thingsmentioning

confidence: 99%

See 1 more Smart Citation

Systematic Review of Existing IoT Architectures Security and Privacy Issues and Concerns

Alshohoumi¹,

Sarrab²,

AlHamadani³

et al. 2019

IJACSA

View full text Add to dashboard Cite

Internet of things (IoT) has become one of the most prominent technologies that the world has been witnessing nowadays. It provides great solutions to humanity in many significant fields of life. IoT refers to a collection of sensors or object in the universe with the capability of communicating with each other through the internet without human intervention. Currently, there is no standard IoT architecture. As it is in its infancy, IoT is surrounded by numerous security and privacy concerns. Thus, to avoid such concerns that may hinder its deployment, an IoT architecture has to be carefully designed to incorporate security and privacy solutions. In this paper, a systematic literature review was conducted to trace the evolvement of IoT architectures from its initial development in 2008 until 2018. The Comparison among these architectures is based on terms of the architectural stack, covered issues, the technology used and considerations of security and privacy aspects. The findings of the review show that the initial IoT architectures did not provide a comprehensive meaning for IoT that describe its nature, whereas the recent IoT architectures convey a comprehensive meaning of IoT, starting from data collection, followed by data transmission and processing, and ending with data dissemination. Moreover, the findings reveal that IoT architecture has evolved gradually across the years, through improving architecture stack with new solutions to mitigate IoT challenges such as scalability, interoperability, extensibility, management, etc. with lack consideration of security solutions. The findings disclose that none of the discussed IoT architectures considers privacy concerns, which indeed considered as a critical factor of IoT sustainability and success. Therefore, there is an inevitable need to consider security and privacy solutions when designing IoT architecture.

show abstract

Private Memoirs of IoT Devices: Safeguarding User Privacy in the IoT Era

Cited by 22 publications

References 15 publications

Real-Time Mask Identification for COVID-19: An Edge-Computing-Based Deep Learning Framework

Real-Time Mask Identification for COVID-19: An Edge-Computing-Based Deep Learning Framework

Blockchain-Based Continued Integrity Service for IoT Big Data Management: A Comprehensive Design

Systematic Review of Existing IoT Architectures Security and Privacy Issues and Concerns

Contact Info

Product

Resources

About