A highly secure Multi- Factor authentication system using biometrics to enhance privacy in Internet of Things (IOT)

2019 ◽  
pp. 26-34
Author(s):  
Vijay M ◽  
Indumathi G
Keyword(s):  
Internet Of Things ◽  
Gabor Filter ◽  
Recognition Rate ◽  
Texture Features ◽  
Data Access ◽  
Security And Privacy ◽  
Smart Device ◽  
Validation Parameters ◽  
Palm Print ◽  
Registration Phase

Authentication is becoming critical in the Internet of Things (IoT) environment because of its many applications and services have been emerging in the areas such as smart city, healthcare, industry etc. Security and privacy plays a vital role in IoT because their services can be accessed through smart device applications by the user from everywhere and at any time. Hence a multi-factor based authentication can provide high security in IOT environment. This security system incorporates most of the valuable methods such as cryptography, steganography and pattern recognition for authentication process. Among various biometric traits, palm vein is more efficient because it has essential sufficient features points for individual unique identification. The system employs registration phase and authentication phase.  The registration phase enrolls person privacy data with their biometric and the obtained data’s are encrypted with the help of Elliptical Curve Cryptography (ECC) and this confidential information is embedded into person palm print image using bits substitution procedure. In authentication phase, recognition will be performed through three levels such as password, palm print and One Time Password (OTP). Using these three levels the matching can be done. The texture features can be obtained by using Multi Block Local Binary Pattern (MB-LBP) and Gabor filter. To afford high authentication, OTP method is also appended. This system provides better information security and texture analysis rather than previous approaches. Thus this multiple level approach ensures a fool proof and a reliable way for data access. Results are in terms of some validation parameters like false acceptance ratio, false rejection ratio and recognition rate. Observing from results, it is clear that the proposed approach outperform many existing methods. As a result, the proposed scheme has strong security, reliability and enhanced computational efficiency.

scholarly journals Accelerating Health Data Sharing: A Solution Based on the Internet of Things and Distributed Ledger Technologies (Preprint)

2019 ◽  
Author(s):  
Xiaochen Zheng ◽  
Shengjing Sun ◽  
Raghava Rao Mukkamala ◽  
Ravi Vatrapu ◽  
Joaquín Ordieres-Meré
Keyword(s):  
Health Care ◽  
Internet Of Things ◽  
Data Sharing ◽  
Data Access ◽  
Health Data ◽  
Security And Privacy ◽  
Access Management ◽  
Related Data ◽  
Distributed Ledger ◽  
Health Related

BACKGROUND Huge amounts of health-related data are generated every moment with the rapid development of Internet of Things (IoT) and wearable technologies. These big health data contain great value and can bring benefit to all stakeholders in the health care ecosystem. Currently, most of these data are siloed and fragmented in different health care systems or public and private databases. It prevents the fulfillment of intelligent health care inspired by these big data. Security and privacy concerns and the lack of ensured authenticity trails of data bring even more obstacles to health data sharing. With a decentralized and consensus-driven nature, distributed ledger technologies (DLTs) provide reliable solutions such as blockchain, Ethereum, and IOTA Tangle to facilitate the health care data sharing. OBJECTIVE This study aimed to develop a health-related data sharing system by integrating IoT and DLT to enable secure, fee-less, tamper-resistant, highly-scalable, and granularly-controllable health data exchange, as well as build a prototype and conduct experiments to verify the feasibility of the proposed solution. METHODS The health-related data are generated by 2 types of IoT devices: wearable devices and stationary air quality sensors. The data sharing mechanism is enabled by IOTA’s distributed ledger, the Tangle, which is a directed acyclic graph. Masked Authenticated Messaging (MAM) is adopted to facilitate data communications among different parties. Merkle Hash Tree is used for data encryption and verification. RESULTS A prototype system was built according to the proposed solution. It uses a smartwatch and multiple air sensors as the sensing layer; a smartphone and a single-board computer (Raspberry Pi) as the gateway; and a local server for data publishing. The prototype was applied to the remote diagnosis of tremor disease. The results proved that the solution could enable costless data integrity and flexible access management during data sharing. CONCLUSIONS DLT integrated with IoT technologies could greatly improve the health-related data sharing. The proposed solution based on IOTA Tangle and MAM could overcome many challenges faced by other traditional blockchain-based solutions in terms of cost, efficiency, scalability, and flexibility in data access management. This study also showed the possibility of fully decentralized health data sharing by replacing the local server with edge computing devices.

Smart Internet of Things (IoT) Applications

2019 ◽  
pp. 33-42
Author(s):  
Rahul Verma
Keyword(s):  
Internet Of Things ◽  
Cyber Physical Systems ◽  
Security And Privacy ◽  
Smart Device ◽  
The Internet ◽  
Iot Applications ◽  
Individual Concepts ◽  
The World ◽  
Iot Devices ◽  
The Internet Of Things

The internet of things (IoT) is the new buzzword in technological corridors with most technology companies announcing a smart device of sorts that runs on internet of things (IoT). Cities around the world are getting “smarter” every day through the implementation of internet of things (IoT) devices. Cities around the world are implementing individual concepts on their way to becoming smart. The services are automated and integrated end to end using internet of things (IoT) devices. The chapter presents an array of internet of things (IoT) applications. Also, cyber physical systems are becoming more vulnerable since the internet of things (IoT) attacks are common and threatening the security and privacy of such systems. The main aim of this chapter is to bring more research in the application aspects of smart internet of things (IoT).

Texture Features in Palmprint Recognition System

2021 ◽  
Vol 10 (1) ◽  
pp. 41-57
Author(s):  
C. Naveena ◽  
Shreyas Rangappa ◽  
Chethan H. K.
Keyword(s):  
Gabor Filter ◽  
Median Filter ◽  
Texture Features ◽  
Recognition System ◽  
Personal Identification ◽  
Palmprint Recognition ◽  
Sum Rule ◽  
Palm Print

This paper describes the algorithm used for personal identification based on features extracted from the palmprint. The local Gabor XOR (LGXP) features is built using Gabor filter with orientation. Initially, the palm print images are preprocessed using median filter. The algorithm is then modified, where features are extracted with different orientations of the Gabor filter called the multiple orientation LGXP (MOLGXP) features. The PCA feature is extracted and fused with MOLGXP and PCA using sum rule.

scholarly journals Design of Deep Learning Algorithm for IoT Application by Image based Recognition

2021 ◽  
Vol 3 (3) ◽  
pp. 276-290
Author(s):  
I Jeena Jacob ◽  
P Ebby Darney
Keyword(s):  
Feature Extraction ◽  
Deep Learning ◽  
Internet Of Things ◽  
Image Recognition ◽  
Research Work ◽  
Recognition Rate ◽  
Security And Privacy ◽  
The Internet ◽  
Learning Method ◽  
The Internet Of Things

The Internet of Things (IoT) is an ecosystem comprised of multiple devices and connections, a large number of users, and a massive amount of data. Deep learning is especially suited for these scenarios due to its appropriateness for "big data" difficulties and future concerns. Nonetheless, guaranteeing security and privacy has emerged as a critical challenge for IoT administration. In many recent cases, deep learning algorithms have proven to be increasingly efficient in performing security assessments for IoT devices without resorting to handcrafted rules. This research work integrates principal component analysis (PCA) for feature extraction with superior performance. Besides, the primary objective of this research work is to gather a comprehensive survey data on the types of IoT deployments, along with security and privacy challenges with good recognition rate. The deep learning method is performed through PCA feature extraction for improving the accuracy of the process. Our other primary goal in this study paper is to achieve a high recognition rate for IoT based image recognition. The CNN approach was trained and evaluated on the IoT image dataset for performance evaluation using multiple methodologies. The initial step would be to investigate the application of deep learning for IoT image acquisition. Additionally, when it comes to IoT image registering, the usefulness of the deep learning method has been evaluated for increasing the appropriateness of image recognition with good testing accuracy. The research discoveries on the application of deep learning in the Internet of Things (IoT) system are summarized in an image-based identification method that introduces a variety of appropriate criteria.

A Survey on Internet of Things : Applications and Layered Wise Security Issues

2019 ◽  
pp. 171-180
Author(s):  
Uppuluri Sirisha ◽  
G. Lakshme Eswari
Keyword(s):  
Quality Of Life ◽  
Internet Of Things ◽  
Security And Privacy ◽  
Global Network ◽  
Business Growth ◽  
Paper Briefly ◽  
Smart Meters ◽  
Security Issues ◽  
Data Points

This paper briefly introduces Internet of Things(IOT) as a intellectual connectivity among the physical objects or devices which are gaining massive increase in the fields like efficiency, quality of life and business growth. IOT is a global network which is interconnecting around 46 million smart meters in U.S. alone with 1.1 billion data points per day[1]. The total installation base of IOT connecting devices would increase to 75.44 billion globally by 2025 with a increase in growth in business, productivity, government efficiency, lifestyle, etc., This paper familiarizes the serious concern such as effective security and privacy to ensure exact and accurate confidentiality, integrity, authentication access control among the devices.

Multi-Disciplinary Opinions Focused on Healthcare Sector for Global Pandemic: COVID-19 (Preprint)

2020 ◽  
Author(s):  
Vinod Kumar Verma
Keyword(s):  
Internet Of Things ◽  
Research Community ◽  
Security And Privacy ◽  
Healthcare Sector ◽  
The Internet ◽  
Thought Process ◽  
Related Information ◽  
Global Pandemic ◽  
The People ◽  
The Internet Of Things

BACKGROUND COVID- 19 pandemics has affected the life of every human being in this world dramatically. The daily routine of the human has been changed to an uncertain extent. Some of the people are affected by the COVID-19, and some of the people are in fear of this epidemic. This has completely changed the thorough process of the people, and now, they are looking for solutions of this pandemic at different levels of the human addressable areas. These areas include medicine, vaccination, precautions, psychology, technology-assisted solutions like information technology, etc. There is a need to think in the direction of technology compliant solutions in the era of COVID-19 pandemic. OBJECTIVE The objective of this paper is to discuss the existing views and focus on the recommendations for the enhancement in the current situation from COVID-19. METHODS Based on the literature, perceptions, challenges, and viewpoints, the following opinions are suggested to the research community for the prevention and elimination of global pandemic COVID-19. The research community irrespective of the discipline focus on the following: 1. The comprehensive thought process for the designing of the internet of things (IoT) based solutions for healthcare applications used in the prevention from COVID-19. 2. Strategies for restricting outbreak of COVID-19 with the emerging trends in Ehealthcare applications. Which should be the optimal strategy to deal with a global pandemic? 3. Explorations on the data analysis as derived from the advanced data mining and warehousing associated with IoT. Besides, cloud-based technologies can be incorporated for the global spread of healthcare-related information to serve the community of different countries in the world. 4. The most adaptable method and technology can be deployed for the development of innovative solutions for COVID-19 related people like smart, patient-centric healthcare information systems. 5. Implementation of smart solutions like wearable technology for mask and PPE along with their disposal can be considered to deal with a global epidemic like COVID-19. This will lead to the manufacturing and incorporation of wearable technologies in the healthcare sector by industries. 6. A Pervasive thought process can be standardized for dealing with global pandemic like COVID-19. In addition, research measures should be considered for the security and privacy challenges of IoT services carrying healthcare-related information. These areas and directions are diverse but, in parallel, the need for healthy bonding and correlation between the people like researchers and scientists irrespective of their discipline. The discipline may vary from medical, engineering, computing, finance, and management, etc. In addition, standard protocols and interoperability measures can be worked out for the exchange of information in the global pandemic situations. RESULTS Recommendations Discussed CONCLUSIONS In this paper, the opinions have been discussed in the multi-disciplinary areas of research like COVID-19 challenges, medicines and vaccines, precautionary measures, technology assistance, and the Internet of Things. These opinions and discussion serve as an integrated platform for researchers and scientists to think about future perspectives to deal with healthcare-related COVID-19 pandemic situation. This includes the original, significant, and visionary automation based ideas, innovations, scientific designs, and applications focusing on Inter-disciplinary technology compliant solutions like IoT, vaccinations, manufacturing, preventive measures, etc. for the improvement of efficiency and reliability of existing healthcare systems. For the future, there is dire need to strengthen the technology not only in the one area but also for the interdisciplinary areas to recover from the pandemic situation rapidly and serve the community.

Open Issues and Security Challenges of Data Communication Channels in Distributed Internet of Things (IoT): A Survey

2018 ◽  
Vol 3 (1) ◽  
pp. 22-32 ◽  
Author(s):  
Ernest Ezema ◽  
Azizol Abdullah ◽  
Nor Fazlida Binti Mohd
Keyword(s):  
Internet Of Things ◽  
Radio Frequency Identification ◽  
Industrial Revolution ◽  
Security And Privacy ◽  
The Internet ◽  
Ongoing Research ◽  
Advantages And Disadvantages ◽  
Exchange Information ◽  
The Internet Of Things ◽  
Open Issues

The concept of the Internet of Things (IoT) has evolved over time. The introduction of the Internet of Things and Services into the manufacturing environment has ushered in a fourth industrial revolution: Industry 4.0. It is no doubt that the world is undergoing constant transformations that somehow change the trajectory and history of humanity. We can illustrate this with the first and second industrial revolutions and the information revolution. IoT is a paradigm based on the internet that comprises many interconnected technologies like RFID (Radio Frequency Identification) and WSAN (Wireless Sensor and Actor Networks) to exchange information. The current needs for better control, monitoring and management in many areas, and the ongoing research in this field, have originated the appearance and creation of multiple systems like smart-home, smart-city and smart-grid. The IoT services can have centralized or distributed architecture. The centralized approach provides is where central entities acquire, process, and provide information while the distributed architectures, is where entities at the edge of the network exchange information and collaborate with each other in a dynamic way. To understand the two approaches, it is necessary to know its advantages and disadvantages especially in terms of security and privacy issues. This paper shows that the distributed approach has various challenges that need to be solved. But also, various interesting properties and strengths. In this paper we present the main research challenges and the existing solutions in the field of IoT security, identifying open issues, the industrial revolution and suggesting some hints for future research.

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