This document summarizes several feature extraction methods for iris recognition systems. It discusses supervised, unsupervised, and semi-supervised learning approaches for iris recognition. It also reviews related literature on iris recognition techniques, including using wavelet transforms, SVM classifiers, and other feature extraction methods. Tables in the document compare different biometric traits and traditional biometric systems, as well as summarize reviewed articles on iris recognition with their main contributions. The methodology section describes the typical four steps of an iris recognition system: image acquisition, preprocessing, feature extraction, and matching/recognition. It also discusses various iris recognition methods and their performance measures.
ENCRYPTION BASED WATERMARKING TECHNIQUE FOR SECURITY OF MEDICAL IMAGEijcsit
This paper proposes an encryption-based image watermarking scheme for medical images using a customized quantization of wavelet coefficient and a crypto system based on the chaotic cipher of Singular Value Decomposition (SVD). In order to spread the robustness of our algorithm and provide extra security, an improved SVD-CHAOS embedding and extraction procedure has been used to scramble the watermark logo in the preprocessing step of the proposed method. In the process of watermark embedding, an R-level discrete wavelet transform was applied to the host image. The high frequency wavelet coefficients are selected to carry these scrambled-watermarks by using adaptive quantization low bit modulation (LBM). The proposed image watermarking method endures entirety attacks and rightly extracts the hidden watermark without significant degradation in the image quality, Thus, when the Peak Signal to Noise Ratio (PSNR) and Normalized Correlation (NC) performance of the proposed algorithm is compared with other related techniques.
oT applications usually rely on cloud computing services to perform data analysis such as filtering,
aggregation, classification, pattern detection, and prediction. When applied to specific domains, the IoT
needs to deal with unique constraints. Besides the hostile environment such as vibration and electric-
magnetic interference, resulting in malfunction, noise, and data loss, industrial plants often have Internet
access restricted or unavailable, forcing us to design stand-alone fog and edge computing solutions.
The mobile device is one of the fasted growing technologies that is widely used in a diversifying sector.
Mobile devices are used for everyday life, such as personal information exchange – chatting, email,
shopping, and mobile banking, contributing to information security threats. Users' behavior can influence
information security threats. More research is needed to understand users' threat avoidance behavior and
motivation. Using Technology threat avoidance theory (TTAT), this study assessed factors that influenced
mobile device users' threat avoidance motivations and behaviors as it relates to phishing attacks.
VPN usage across the world has increased due to the COVID-19 pandemic. With companies trying to lay
the course through this unfamiliar state, corporations had to implement a Business Continuity Plan which
included several elements to maintain a scalable and robust VPN connection. During this time of
uncertainty, best practices need to be deployed by corporations and government entities more than ever.
The purpose of this study is to highlight the necessary path SD Telecom would take to ensure a secure,
reliable network during global traffic surge. Specific VPN solutions, access needs, and eligibility
requirements vary based on the end user.
HISTOGRAM OF NEIGHBORHOOD TRIPARTITE AUTHENTICATION WITH FINGERPRINT-BASED BI...IJCNCJournal
Internet of Things (IoT) and services is an interesting topic with a wide range of potential applications like smart home systems, health care, telemedicine, and intelligent transportation. Traditionally, key agreement schemes have been evaluated to access IoT services which are highly susceptible to security. Recently, Biometric-based authentication is also used to access IoT services and devices. They are involving a larger amount of memory with increased running time and found to be computationally infeasible. To provide robust authentication for IoT services, Histogram of Neighborhood Tripartite Authentication with Fingerprint Biometrics (HNTA-FB) for IoT services is proposed in this paper. This proposed HNTA-FB method uses binary patterns and a histogram of features to extract the region of interest. To reduce the memory requirements while providing access to IoT services, Histogram of Neighborhood Binary Pattern Pre-processing (HNBPP) model is proposed. The discriminative power of Neighbourhood Binary Pattern Registration (NBPR) is integrated with the normalized sparse representation based on the histogram. Additionally, this work presents a new Tripartite User Authentication model for fingerprint biometric template matching process. When compared with different state-of-the-art methods, the proposed method depicts significantly improved performance in terms of matching accuracy, computational overhead and execution speed and is highly effective in delivering smart home services.
Mining knowledge graphs to map heterogeneous relations between the internet o...IJECEIAES
Patterns for the internet of things (IoT) which represent proven solutions used to solve design problems in the IoT are numerous. Similar to objectoriented design patterns, these IoT patterns contain multiple mutual heterogeneous relationships. However, these pattern relationships are hidden and virtually unidentified in most documents. In this paper, we use machine learning techniques to automatically mine knowledge graphs to map these relationships between several IoT patterns. The end result is a semantic knowledge graph database which outlines patterns as vertices and their relations as edges. We have identified four main relationships between the IoT patterns-a pattern is similar to another pattern if it addresses the same use case problem, a large-scale pattern uses a small- scale pattern in a lower level layer, a large pattern is composed of multiple smaller scale patterns underneath it, and patterns complement and combine with each other to resolve a given use case problem. Our results show some promising prospects towards the use of machine learning techniques to generate an automated repository to organise the IoT patterns, which are usually extracted at various levels of abstraction and granularity.
THE INTERNET OF THINGS: NEW INTEROPERABILITY, MANAGEMENT AND SECURITY CHALLENGESIJNSA Journal
The Internet of Things (IoT) brings connectivity to about every objects found in the physical space. It
extends connectivity to everyday objects. From connected fridges, cars and cities, the IoT creates
opportunities in numerous domains. However, this increase in connectivity creates many prominent
challenges. This paper provides a survey of some of the major issues challenging the widespread adoption
of the IoT. Particularly, it focuses on the interoperability, management, security and privacy issues in the
IoT. It is concluded that there is a need to develop a multifaceted technology approach to IoT security,
management, and privacy.
ENCRYPTION BASED WATERMARKING TECHNIQUE FOR SECURITY OF MEDICAL IMAGEijcsit
This paper proposes an encryption-based image watermarking scheme for medical images using a customized quantization of wavelet coefficient and a crypto system based on the chaotic cipher of Singular Value Decomposition (SVD). In order to spread the robustness of our algorithm and provide extra security, an improved SVD-CHAOS embedding and extraction procedure has been used to scramble the watermark logo in the preprocessing step of the proposed method. In the process of watermark embedding, an R-level discrete wavelet transform was applied to the host image. The high frequency wavelet coefficients are selected to carry these scrambled-watermarks by using adaptive quantization low bit modulation (LBM). The proposed image watermarking method endures entirety attacks and rightly extracts the hidden watermark without significant degradation in the image quality, Thus, when the Peak Signal to Noise Ratio (PSNR) and Normalized Correlation (NC) performance of the proposed algorithm is compared with other related techniques.
oT applications usually rely on cloud computing services to perform data analysis such as filtering,
aggregation, classification, pattern detection, and prediction. When applied to specific domains, the IoT
needs to deal with unique constraints. Besides the hostile environment such as vibration and electric-
magnetic interference, resulting in malfunction, noise, and data loss, industrial plants often have Internet
access restricted or unavailable, forcing us to design stand-alone fog and edge computing solutions.
The mobile device is one of the fasted growing technologies that is widely used in a diversifying sector.
Mobile devices are used for everyday life, such as personal information exchange – chatting, email,
shopping, and mobile banking, contributing to information security threats. Users' behavior can influence
information security threats. More research is needed to understand users' threat avoidance behavior and
motivation. Using Technology threat avoidance theory (TTAT), this study assessed factors that influenced
mobile device users' threat avoidance motivations and behaviors as it relates to phishing attacks.
VPN usage across the world has increased due to the COVID-19 pandemic. With companies trying to lay
the course through this unfamiliar state, corporations had to implement a Business Continuity Plan which
included several elements to maintain a scalable and robust VPN connection. During this time of
uncertainty, best practices need to be deployed by corporations and government entities more than ever.
The purpose of this study is to highlight the necessary path SD Telecom would take to ensure a secure,
reliable network during global traffic surge. Specific VPN solutions, access needs, and eligibility
requirements vary based on the end user.
HISTOGRAM OF NEIGHBORHOOD TRIPARTITE AUTHENTICATION WITH FINGERPRINT-BASED BI...IJCNCJournal
Internet of Things (IoT) and services is an interesting topic with a wide range of potential applications like smart home systems, health care, telemedicine, and intelligent transportation. Traditionally, key agreement schemes have been evaluated to access IoT services which are highly susceptible to security. Recently, Biometric-based authentication is also used to access IoT services and devices. They are involving a larger amount of memory with increased running time and found to be computationally infeasible. To provide robust authentication for IoT services, Histogram of Neighborhood Tripartite Authentication with Fingerprint Biometrics (HNTA-FB) for IoT services is proposed in this paper. This proposed HNTA-FB method uses binary patterns and a histogram of features to extract the region of interest. To reduce the memory requirements while providing access to IoT services, Histogram of Neighborhood Binary Pattern Pre-processing (HNBPP) model is proposed. The discriminative power of Neighbourhood Binary Pattern Registration (NBPR) is integrated with the normalized sparse representation based on the histogram. Additionally, this work presents a new Tripartite User Authentication model for fingerprint biometric template matching process. When compared with different state-of-the-art methods, the proposed method depicts significantly improved performance in terms of matching accuracy, computational overhead and execution speed and is highly effective in delivering smart home services.
Mining knowledge graphs to map heterogeneous relations between the internet o...IJECEIAES
Patterns for the internet of things (IoT) which represent proven solutions used to solve design problems in the IoT are numerous. Similar to objectoriented design patterns, these IoT patterns contain multiple mutual heterogeneous relationships. However, these pattern relationships are hidden and virtually unidentified in most documents. In this paper, we use machine learning techniques to automatically mine knowledge graphs to map these relationships between several IoT patterns. The end result is a semantic knowledge graph database which outlines patterns as vertices and their relations as edges. We have identified four main relationships between the IoT patterns-a pattern is similar to another pattern if it addresses the same use case problem, a large-scale pattern uses a small- scale pattern in a lower level layer, a large pattern is composed of multiple smaller scale patterns underneath it, and patterns complement and combine with each other to resolve a given use case problem. Our results show some promising prospects towards the use of machine learning techniques to generate an automated repository to organise the IoT patterns, which are usually extracted at various levels of abstraction and granularity.
THE INTERNET OF THINGS: NEW INTEROPERABILITY, MANAGEMENT AND SECURITY CHALLENGESIJNSA Journal
The Internet of Things (IoT) brings connectivity to about every objects found in the physical space. It
extends connectivity to everyday objects. From connected fridges, cars and cities, the IoT creates
opportunities in numerous domains. However, this increase in connectivity creates many prominent
challenges. This paper provides a survey of some of the major issues challenging the widespread adoption
of the IoT. Particularly, it focuses on the interoperability, management, security and privacy issues in the
IoT. It is concluded that there is a need to develop a multifaceted technology approach to IoT security,
management, and privacy.
WEARABLE TECHNOLOGY DEVICES SECURITY AND PRIVACY VULNERABILITY ANALYSISIJNSA Journal
Wearable Technology also called wearable gadget, is acategory of technology devices with low processing
capabilities that can be worn by a user with the aim to provide information and ease of access to the master
devices its pairing with. Such examples are Google Glass and Smart watch. The impact of wearable
technology becomes significant when people start their invention in wearable computing, where their
mobile devices become one of the computation sources. However, wearable technology is not mature yet in
term of device security and privacy acceptance of the public. There exists some security weakness that
prompts such wearable devices vulnerable to attack. One of the critical attack on wearable technology is
authentication issue. The low processing due to less computing power of wearable device causethe
developer's inability to equip some complicated security mechanisms and algorithm on the device.In this
study, an overview of security and privacy vulnerabilities on wearable devices is presented.
Internet of things-based photovoltaics parameter monitoring system using Node...IJECEIAES
The use of the internet of things (IoT) in solar photovoltaic (PV) systems is a critical feature for remote monitoring, supervising, and performance evaluation. Furthermore, it improves the long-term viability, consistency, efficiency, and system maintenance of energy production. However, previous researchers' proposed PV monitoring systems are relatively complex and expensive. Furthermore, the existing systems do not have any backup data, which means that the acquired data could be lost if the network connection fails. This paper presents a simple and low-cost IoT-based PV parameter monitoring system, with additional backup data stored on a microSD card. A NodeMCU ESP8266 development board is chosen as the main controller because it is a system-on-chip (SOC) microcontroller with integrated Wi-Fi and low-power support, all in one chip to reduce the cost of the proposed system. The solar irradiance, ambient temperature, PV output voltage and PV output current, are measured with photo-diodes, DHT22, impedance dividers and ACS712. While, the PV output power is a product of the PV voltage and PV current. ThingSpeak, an opensource software, is used as a cloud database and data monitoring tool in the form of interactive graphics. The results showed that the system was designed to be highly accurate, reliable, simple to use, and low-cost.
Secure Modern Healthcare System Based on Internet of Things and Secret Sharin...Eswar Publications
The Internet of Things (IoT), is a concept that describes how objects that we are used in daily life will interact and negotiate with other objects over the internet. The amount of devices with Wi-Fi capabilities and built-in sensors keeps on increasing. IoT combines smart devices to provide smart services and applications like smart cities, smart healthcare, smart home, and digital farm etc. But it is very crucial to secure connected IoT devices and networks because of the nature of IoT system. In this paper, the existing works are analyzed and an IoT based
healthcare system architecture is proposed. An authentication scheme to enhance the security of the proposed healthcare system is also present.
VOICE BIOMETRIC IDENTITY AUTHENTICATION MODEL FOR IOT DEVICESijsptm
Behavioral biometric authentication is considered as a promising approach to securing the internet of things (IoT) ecosystem. In this paper, we investigated the need and suitability of employing voice recognition systems in the user authentication of the IoT. Tools and techniques used in accomplishing voice recognition systems are reviewed, and their appropriateness to the IoT environment are discussed. In the end, a voice recognition system is proposed for IoT ecosystem user authentication. The proposed system has two phases. The first being the enrollment phase consisting of a pre-processing step where the noise is removed from the voice for the enrollment process, the feature extraction step where feature traits are extracted from user’s voice, and the model training step where the voice model is trained for the IoT user. And the second being the phase verifies whether the identity claimer is the owner of the IoT device. Based on the resources limitedness of the IoT technologies, the suitability of text-dependent voice recognition systems is promoted. Likewise, the use of MFCC features is considered in the proposed system.
A Smart Receptionist Implementing Facial Recognition and Voice InteractionCSCJournals
The purpose of this research is to implement a smart receptionist system with facial recognition and voice interaction using deep learning. The facial recognition component is implemented using real time image processing techniques, and it can be used to learn new faces as well as detect and recognize existing faces. The first time a customer uses this system, it will take the person’s facial data to create a unique user facial model, and this model will be triggered if the person comes the second time. The recognition is done in real time and after which voice interaction will be applied. Voice interaction is used to provide a life-like human communication and improve user experience. Our proposed smart receptionist system could be integrated into the self check-in kiosks deployed in hospitals or smart buildings to streamline the user recognition process and provide customized user interactions. This system could also be used in smart home environment where smart cameras have been deployed and voice assistants are in place.
A Novel Security Approach for Communication using IOTIJEACS
The Internet of Things (IOT) is the arrangement of physical articles or "things" introduced with equipment, programming, sensors, and framework accessibility, which enables these things to accumulate and exchange data. Here outlining security convention for the Internet of Things, and execution of this relating security convention on the inserted gadgets. This convention will cover the honesty of messages and verification of every customer by giving a productive confirmation component. By this venture the protected correspondence is executed on implanted gadgets.
State regulation of the IoT in the Russian Federation: Fundamentals and chall...IJECEIAES
The purpose of this section is to study the problems with implementing technical and legal regulations for the development of public administration functions in the Russian Federation when using the internet of things (IoT). The introduction is based on an analysis of regulatory legal acts and presents the main strategic directions for the development of public administration functions in the Russian federation when using IoT. State reports, scientific literature, a system of technical and legal regulation are analyzed, and the main problems of implementing the IoT that impede the achievement of effective public administration are studied. The Russian practice of using IoT in various economic areas is investigated. Based on an analysis of the mechanisms for ensuring data safety of information technology users in the Russian federation, problems were investigated, such as the collecting data through IoT, including publicly available personal data in order to profile human activities, and creating of a digital twin of a person. The social constraints for introducing distributed registry technologies are users' distrust in the field of data privacy protection and mathematical algorithms that are used to establish trust in a digital environment instead of trusted centralized intermediaries; these problems were also analyzed. The Russian approach was analyzed in comparison to European experience in this field. To ensure information security and the possibility of its distribution, the IoT is revealed.
Smart information desk system with voice assistant for universities IJECEIAES
This article aims to develop a smart information desk system through a smart mirror for universities. It is a mirror with extra capabilities of displaying answers for academic inquiries such as asking about the lecturers’ office numbers and hours, exams dates and times on the mirror surface. In addition, the voice recognition feature was used to answer spoken inquiries in audio responds to serve all types of users including disabled ones. Furthermore, the system showed general information such as date, weather, time and the university map. The smart mirror was connected to an outdoor camera to monitor the traffics at the university entrance gate. The system was implemented on a Raspberry Pi 4 model B connected to a two-way mirror and an infrared (IR) touch frame. The results of this study helped to overcome the problem of the information desk absence in the university. Therefore, it helped users to save their time and effort in making requests for important academic information.
Multi-objective NSGA-II based community detection using dynamical evolution s...IJECEIAES
Community detection is becoming a highly demanded topic in social networking-based applications. It involves finding the maximum intraconnected and minimum inter-connected sub-graphs in given social networks. Many approaches have been developed for community’s detection and less of them have focused on the dynamical aspect of the social network. The decision of the community has to consider the pattern of changes in the social network and to be smooth enough. This is to enable smooth operation for other community detection dependent application. Unlike dynamical community detection Algorithms, this article presents a non-dominated aware searching Algorithm designated as non-dominated sorting based community detection with dynamical awareness (NDS-CD-DA). The Algorithm uses a non-dominated sorting genetic algorithm NSGA-II with two objectives: modularity and normalized mutual information (NMI). Experimental results on synthetic networks and real-world social network datasets have been compared with classical genetic with a single objective and has been shown to provide superiority in terms of the domination as well as the convergence. NDS-CD-DA has accomplished a domination percentage of 100% over dynamic evolutionary community searching DECS for almost all iterations.
The internet of things is an emerging technology that is currently present in most processes and devices, allowing to improve the quality of life of people and facilitating the access to specific information and services. The main purpose of the present article is to offer a general overview of internet of things, based on the analysis of recently published work. The added value of this article lies in the analysis of the main recent publications and the diversity of applications of internet of things technology. As a result of the analysis of the current literature, internet of things technology stands out as a facilitator in business and industrial performance but above all in improving the quality of life. As a conclusion to this document, the internet of things is a technology that can overcome the challenges in terms of security, processing capacity and data mobility, as long as the development related to other technologies follows its expected course.
A Bring Your Own Device Risk Assessment ModelCSCJournals
Bring Your Own Device (BYOD), a technology where individuals or employees use their own devices on the organization’s network to perform tasks assigned to them by the organization has been widely embraced. The reasons for adoption are diverse in every organization. In spite of the security control strategies implemented by these organizations to safeguard their information resources, there has been an upsurge in information security breaches as a result of existing vulnerabilities in these systems and the legacy systems in use. Various approaches have been employed to deal with security challenges in BYOD, but according to literature, risk assessment has proved to be the first key step towards improving security of the BYOD environment in an enterprise. Risk assessment models have been proposed by various researchers, although, most are largely influenced by the degree of technological advancement and utilization as well as the working cultures within institutions. The existing models were largely developed in technologically advanced countries and thus do not fit well in developing countries. This study sought to develop flexible BYOD risk assessment model that can be adopted by varied institutions to secure their information resources. The study was carried out in Five (5) purposively selected state universities in Kenya. The research adopted a mixed research design approach with mixed sampling technique utilized to select the participants. Reliability and validity of data collection tools were evaluated and recommended by IT security and network experts. The qualitative and quantitative data was collected by interviewing experts and administering a questionnaire to sampled participants. The developed model was validated both statistically and by experts. The findings revealed that threats and vulnerabilities contributed to 39.9% and 69.2% respectively to the risk of the BYOD environment while Data Encryption (DE) and Software Updates (SU) came out strongly as intervening variables which have a major impact on the relationship between the dependent and independent variables.
27 5 jun17 28apr 15859 ammar final (edti ari baru))IAESIJEECS
The transition from analog technologies to digital technologies has increased the ever-growing concern for protection and authentication of digital content and data. Owners of digital content of any type are seeking and exploring new technologies for the protection of copyrighted multimedia content. Multimedia protection has become an issue in recent years, and to deal with this issue, researchers are continuously searching for and exploring new effective and efficient technologies. This thesis study has been prepared in order to increase the invisibility and durability of invisible watermarking by using the multilayer Discrete Wavelet Transform (DWT) in the frequency plane and embedding two marks into an image for the purpose of authentication and copyright when digital content travels through an unsecured channel. A novel watermarking algorithm has been proposed based on five active positions and on using two marks. In addition to the extraction process, watermarking images will be subjected to a set of attack tests. The evaluation criteria have been the bases of assessing the value of SNR, PNSR, MAE and RMSE for both the watermarking images and the watermarking images after attacks, followed by the invisibility of the watermarking being measured before and after the attacks. Our lab results show high robustness and high quality images obtaining value for both SNR and PNSR.
Novel authentication framework for securing communication in internet-of-things IJECEIAES
Internet-of-Things (IoT) offers a big boon towards a massive network of connected devices and is considered to offer coverage to an exponential number of the smart appliance in the very near future. Owing to the nascent stage of evolution of IoT, it is shrouded by security loopholes because of various reasons. Review of existing research-based solution highlights the usage of conventional cryptographic-based solution over the traditional mechanism of data forwarding process between IoT nodes and gateway. The proposed system presents a novel solution to this problem by a model that is capable of performing a highly secured and cost-effective authentication process. The proposed system introduces Authentication Using Signature (AUS) as well as Security with Complexity Reduction (SCR) for the purpose to resist participation of any form of unknown threats. The outcome of the model shows better security strength with faster response time and energy saving of the IoT nodes.
Interactive Technologies for Improving Quality of Education to Build Collabor...ijsrd.com
Today with advancement in Information Communication Technology (ICT) the way the education is being delivered is seeing a paradigm shift from boring classroom lectures to interactive applications such as 2-D and 3-D learning content, animations, live videos, response systems, interactive panels, education games, virtual laboratories and collaborative research (data gathering and analysis) etc. Engineering is emerging with more innovative solutions in the field of education and bringing out their innovative products to improve education delivery. The academic institutes which were once hesitant to use such technology are now looking forward to such innovations. They are adopting the new ways as they are realizing the vast benefits of using such methods and technology. The benefits are better comprehensibility, improved learning efficiency of students, and access to vast knowledge resources, geographical reach, quick feedback, accountability and quality research. This paper focuses on how engineering can leverage the latest technology and build a collaborative learning environment which can then be integrated with the national e-learning grid.
DESIGN AND IMPLEMENTATION OF THE ADVANCED CLOUD PRIVACY THREAT MODELING IJNSA Journal
Privacy-preservation for sensitive data has become a challenging issue in cloud computing. Threat
modeling as a part of requirements engineering in secure software development provides a structured
approach for identifying attacks and proposing countermeasures against the exploitation of vulnerabilities
in a system. This paper describes an extension of Cloud Privacy Threat Modeling (CPTM) methodology for
privacy threat modeling in relation to processing sensitive data in cloud computing environments. It
describes the modeling methodology that involved applying Method Engineering to specify characteristics
of a cloud privacy threat modeling methodology, different steps in the proposed methodology and
corresponding products. In addition, a case study has been implemented as a proof of concept to
demonstrate the usability of the proposed methodology. We believe that the extended methodology
facilitates the application of a privacy-preserving cloud software development approach from requirements
engineering to design.
Intelligent multimodal identification system based on local feature fusion be...nooriasukmaningtyas
Biometric identification systems, which use physical features to check a person's identity, ensure much higher security than password and number systems. Biometric features such as the face or a fingerprint can be stored on a microchip in a credit card, for example. A single modal biometric identification system fails to extract enough features for identification. Another disadvantage of using only one feature is not always readable. In this article, a smart multimodal biometric verification model for identifying and verifying a person's identity is recommended based on artificial intelligence methods. The proposed model is identified the iris and finger vein unique patterns each individual to overcome many challenges such as identity fraud, poor image quality, noise, and instability of the surrounding environment. Several experiments were performed on a dataset containing 50 people by using many matching methods. The results of the proposed model were provided a higher accuracy of 98%, with FAR and FRR of 0.0015% and 0.025%, respectively.
WEARABLE TECHNOLOGY DEVICES SECURITY AND PRIVACY VULNERABILITY ANALYSISIJNSA Journal
Wearable Technology also called wearable gadget, is acategory of technology devices with low processing
capabilities that can be worn by a user with the aim to provide information and ease of access to the master
devices its pairing with. Such examples are Google Glass and Smart watch. The impact of wearable
technology becomes significant when people start their invention in wearable computing, where their
mobile devices become one of the computation sources. However, wearable technology is not mature yet in
term of device security and privacy acceptance of the public. There exists some security weakness that
prompts such wearable devices vulnerable to attack. One of the critical attack on wearable technology is
authentication issue. The low processing due to less computing power of wearable device causethe
developer's inability to equip some complicated security mechanisms and algorithm on the device.In this
study, an overview of security and privacy vulnerabilities on wearable devices is presented.
Internet of things-based photovoltaics parameter monitoring system using Node...IJECEIAES
The use of the internet of things (IoT) in solar photovoltaic (PV) systems is a critical feature for remote monitoring, supervising, and performance evaluation. Furthermore, it improves the long-term viability, consistency, efficiency, and system maintenance of energy production. However, previous researchers' proposed PV monitoring systems are relatively complex and expensive. Furthermore, the existing systems do not have any backup data, which means that the acquired data could be lost if the network connection fails. This paper presents a simple and low-cost IoT-based PV parameter monitoring system, with additional backup data stored on a microSD card. A NodeMCU ESP8266 development board is chosen as the main controller because it is a system-on-chip (SOC) microcontroller with integrated Wi-Fi and low-power support, all in one chip to reduce the cost of the proposed system. The solar irradiance, ambient temperature, PV output voltage and PV output current, are measured with photo-diodes, DHT22, impedance dividers and ACS712. While, the PV output power is a product of the PV voltage and PV current. ThingSpeak, an opensource software, is used as a cloud database and data monitoring tool in the form of interactive graphics. The results showed that the system was designed to be highly accurate, reliable, simple to use, and low-cost.
Secure Modern Healthcare System Based on Internet of Things and Secret Sharin...Eswar Publications
The Internet of Things (IoT), is a concept that describes how objects that we are used in daily life will interact and negotiate with other objects over the internet. The amount of devices with Wi-Fi capabilities and built-in sensors keeps on increasing. IoT combines smart devices to provide smart services and applications like smart cities, smart healthcare, smart home, and digital farm etc. But it is very crucial to secure connected IoT devices and networks because of the nature of IoT system. In this paper, the existing works are analyzed and an IoT based
healthcare system architecture is proposed. An authentication scheme to enhance the security of the proposed healthcare system is also present.
VOICE BIOMETRIC IDENTITY AUTHENTICATION MODEL FOR IOT DEVICESijsptm
Behavioral biometric authentication is considered as a promising approach to securing the internet of things (IoT) ecosystem. In this paper, we investigated the need and suitability of employing voice recognition systems in the user authentication of the IoT. Tools and techniques used in accomplishing voice recognition systems are reviewed, and their appropriateness to the IoT environment are discussed. In the end, a voice recognition system is proposed for IoT ecosystem user authentication. The proposed system has two phases. The first being the enrollment phase consisting of a pre-processing step where the noise is removed from the voice for the enrollment process, the feature extraction step where feature traits are extracted from user’s voice, and the model training step where the voice model is trained for the IoT user. And the second being the phase verifies whether the identity claimer is the owner of the IoT device. Based on the resources limitedness of the IoT technologies, the suitability of text-dependent voice recognition systems is promoted. Likewise, the use of MFCC features is considered in the proposed system.
A Smart Receptionist Implementing Facial Recognition and Voice InteractionCSCJournals
The purpose of this research is to implement a smart receptionist system with facial recognition and voice interaction using deep learning. The facial recognition component is implemented using real time image processing techniques, and it can be used to learn new faces as well as detect and recognize existing faces. The first time a customer uses this system, it will take the person’s facial data to create a unique user facial model, and this model will be triggered if the person comes the second time. The recognition is done in real time and after which voice interaction will be applied. Voice interaction is used to provide a life-like human communication and improve user experience. Our proposed smart receptionist system could be integrated into the self check-in kiosks deployed in hospitals or smart buildings to streamline the user recognition process and provide customized user interactions. This system could also be used in smart home environment where smart cameras have been deployed and voice assistants are in place.
A Novel Security Approach for Communication using IOTIJEACS
The Internet of Things (IOT) is the arrangement of physical articles or "things" introduced with equipment, programming, sensors, and framework accessibility, which enables these things to accumulate and exchange data. Here outlining security convention for the Internet of Things, and execution of this relating security convention on the inserted gadgets. This convention will cover the honesty of messages and verification of every customer by giving a productive confirmation component. By this venture the protected correspondence is executed on implanted gadgets.
State regulation of the IoT in the Russian Federation: Fundamentals and chall...IJECEIAES
The purpose of this section is to study the problems with implementing technical and legal regulations for the development of public administration functions in the Russian Federation when using the internet of things (IoT). The introduction is based on an analysis of regulatory legal acts and presents the main strategic directions for the development of public administration functions in the Russian federation when using IoT. State reports, scientific literature, a system of technical and legal regulation are analyzed, and the main problems of implementing the IoT that impede the achievement of effective public administration are studied. The Russian practice of using IoT in various economic areas is investigated. Based on an analysis of the mechanisms for ensuring data safety of information technology users in the Russian federation, problems were investigated, such as the collecting data through IoT, including publicly available personal data in order to profile human activities, and creating of a digital twin of a person. The social constraints for introducing distributed registry technologies are users' distrust in the field of data privacy protection and mathematical algorithms that are used to establish trust in a digital environment instead of trusted centralized intermediaries; these problems were also analyzed. The Russian approach was analyzed in comparison to European experience in this field. To ensure information security and the possibility of its distribution, the IoT is revealed.
Smart information desk system with voice assistant for universities IJECEIAES
This article aims to develop a smart information desk system through a smart mirror for universities. It is a mirror with extra capabilities of displaying answers for academic inquiries such as asking about the lecturers’ office numbers and hours, exams dates and times on the mirror surface. In addition, the voice recognition feature was used to answer spoken inquiries in audio responds to serve all types of users including disabled ones. Furthermore, the system showed general information such as date, weather, time and the university map. The smart mirror was connected to an outdoor camera to monitor the traffics at the university entrance gate. The system was implemented on a Raspberry Pi 4 model B connected to a two-way mirror and an infrared (IR) touch frame. The results of this study helped to overcome the problem of the information desk absence in the university. Therefore, it helped users to save their time and effort in making requests for important academic information.
Multi-objective NSGA-II based community detection using dynamical evolution s...IJECEIAES
Community detection is becoming a highly demanded topic in social networking-based applications. It involves finding the maximum intraconnected and minimum inter-connected sub-graphs in given social networks. Many approaches have been developed for community’s detection and less of them have focused on the dynamical aspect of the social network. The decision of the community has to consider the pattern of changes in the social network and to be smooth enough. This is to enable smooth operation for other community detection dependent application. Unlike dynamical community detection Algorithms, this article presents a non-dominated aware searching Algorithm designated as non-dominated sorting based community detection with dynamical awareness (NDS-CD-DA). The Algorithm uses a non-dominated sorting genetic algorithm NSGA-II with two objectives: modularity and normalized mutual information (NMI). Experimental results on synthetic networks and real-world social network datasets have been compared with classical genetic with a single objective and has been shown to provide superiority in terms of the domination as well as the convergence. NDS-CD-DA has accomplished a domination percentage of 100% over dynamic evolutionary community searching DECS for almost all iterations.
The internet of things is an emerging technology that is currently present in most processes and devices, allowing to improve the quality of life of people and facilitating the access to specific information and services. The main purpose of the present article is to offer a general overview of internet of things, based on the analysis of recently published work. The added value of this article lies in the analysis of the main recent publications and the diversity of applications of internet of things technology. As a result of the analysis of the current literature, internet of things technology stands out as a facilitator in business and industrial performance but above all in improving the quality of life. As a conclusion to this document, the internet of things is a technology that can overcome the challenges in terms of security, processing capacity and data mobility, as long as the development related to other technologies follows its expected course.
A Bring Your Own Device Risk Assessment ModelCSCJournals
Bring Your Own Device (BYOD), a technology where individuals or employees use their own devices on the organization’s network to perform tasks assigned to them by the organization has been widely embraced. The reasons for adoption are diverse in every organization. In spite of the security control strategies implemented by these organizations to safeguard their information resources, there has been an upsurge in information security breaches as a result of existing vulnerabilities in these systems and the legacy systems in use. Various approaches have been employed to deal with security challenges in BYOD, but according to literature, risk assessment has proved to be the first key step towards improving security of the BYOD environment in an enterprise. Risk assessment models have been proposed by various researchers, although, most are largely influenced by the degree of technological advancement and utilization as well as the working cultures within institutions. The existing models were largely developed in technologically advanced countries and thus do not fit well in developing countries. This study sought to develop flexible BYOD risk assessment model that can be adopted by varied institutions to secure their information resources. The study was carried out in Five (5) purposively selected state universities in Kenya. The research adopted a mixed research design approach with mixed sampling technique utilized to select the participants. Reliability and validity of data collection tools were evaluated and recommended by IT security and network experts. The qualitative and quantitative data was collected by interviewing experts and administering a questionnaire to sampled participants. The developed model was validated both statistically and by experts. The findings revealed that threats and vulnerabilities contributed to 39.9% and 69.2% respectively to the risk of the BYOD environment while Data Encryption (DE) and Software Updates (SU) came out strongly as intervening variables which have a major impact on the relationship between the dependent and independent variables.
27 5 jun17 28apr 15859 ammar final (edti ari baru))IAESIJEECS
The transition from analog technologies to digital technologies has increased the ever-growing concern for protection and authentication of digital content and data. Owners of digital content of any type are seeking and exploring new technologies for the protection of copyrighted multimedia content. Multimedia protection has become an issue in recent years, and to deal with this issue, researchers are continuously searching for and exploring new effective and efficient technologies. This thesis study has been prepared in order to increase the invisibility and durability of invisible watermarking by using the multilayer Discrete Wavelet Transform (DWT) in the frequency plane and embedding two marks into an image for the purpose of authentication and copyright when digital content travels through an unsecured channel. A novel watermarking algorithm has been proposed based on five active positions and on using two marks. In addition to the extraction process, watermarking images will be subjected to a set of attack tests. The evaluation criteria have been the bases of assessing the value of SNR, PNSR, MAE and RMSE for both the watermarking images and the watermarking images after attacks, followed by the invisibility of the watermarking being measured before and after the attacks. Our lab results show high robustness and high quality images obtaining value for both SNR and PNSR.
Novel authentication framework for securing communication in internet-of-things IJECEIAES
Internet-of-Things (IoT) offers a big boon towards a massive network of connected devices and is considered to offer coverage to an exponential number of the smart appliance in the very near future. Owing to the nascent stage of evolution of IoT, it is shrouded by security loopholes because of various reasons. Review of existing research-based solution highlights the usage of conventional cryptographic-based solution over the traditional mechanism of data forwarding process between IoT nodes and gateway. The proposed system presents a novel solution to this problem by a model that is capable of performing a highly secured and cost-effective authentication process. The proposed system introduces Authentication Using Signature (AUS) as well as Security with Complexity Reduction (SCR) for the purpose to resist participation of any form of unknown threats. The outcome of the model shows better security strength with faster response time and energy saving of the IoT nodes.
Interactive Technologies for Improving Quality of Education to Build Collabor...ijsrd.com
Today with advancement in Information Communication Technology (ICT) the way the education is being delivered is seeing a paradigm shift from boring classroom lectures to interactive applications such as 2-D and 3-D learning content, animations, live videos, response systems, interactive panels, education games, virtual laboratories and collaborative research (data gathering and analysis) etc. Engineering is emerging with more innovative solutions in the field of education and bringing out their innovative products to improve education delivery. The academic institutes which were once hesitant to use such technology are now looking forward to such innovations. They are adopting the new ways as they are realizing the vast benefits of using such methods and technology. The benefits are better comprehensibility, improved learning efficiency of students, and access to vast knowledge resources, geographical reach, quick feedback, accountability and quality research. This paper focuses on how engineering can leverage the latest technology and build a collaborative learning environment which can then be integrated with the national e-learning grid.
DESIGN AND IMPLEMENTATION OF THE ADVANCED CLOUD PRIVACY THREAT MODELING IJNSA Journal
Privacy-preservation for sensitive data has become a challenging issue in cloud computing. Threat
modeling as a part of requirements engineering in secure software development provides a structured
approach for identifying attacks and proposing countermeasures against the exploitation of vulnerabilities
in a system. This paper describes an extension of Cloud Privacy Threat Modeling (CPTM) methodology for
privacy threat modeling in relation to processing sensitive data in cloud computing environments. It
describes the modeling methodology that involved applying Method Engineering to specify characteristics
of a cloud privacy threat modeling methodology, different steps in the proposed methodology and
corresponding products. In addition, a case study has been implemented as a proof of concept to
demonstrate the usability of the proposed methodology. We believe that the extended methodology
facilitates the application of a privacy-preserving cloud software development approach from requirements
engineering to design.
Intelligent multimodal identification system based on local feature fusion be...nooriasukmaningtyas
Biometric identification systems, which use physical features to check a person's identity, ensure much higher security than password and number systems. Biometric features such as the face or a fingerprint can be stored on a microchip in a credit card, for example. A single modal biometric identification system fails to extract enough features for identification. Another disadvantage of using only one feature is not always readable. In this article, a smart multimodal biometric verification model for identifying and verifying a person's identity is recommended based on artificial intelligence methods. The proposed model is identified the iris and finger vein unique patterns each individual to overcome many challenges such as identity fraud, poor image quality, noise, and instability of the surrounding environment. Several experiments were performed on a dataset containing 50 people by using many matching methods. The results of the proposed model were provided a higher accuracy of 98%, with FAR and FRR of 0.0015% and 0.025%, respectively.
Role of fuzzy in multimodal biometrics systemKishor Singh
Person identification is possible through the biometrics using their physiological and behavioral characteristics such
as face, ear, thumb print, voice, signature and key stock. Unimodal biometric systems face a range of problems, including noisy
data, intra-class versions, small liberty, non-university, spoof assaults, and unsustainable error rates. Some of these drawbacks
can be overcome by multimodal biometric technologies, which incorporate data from various information sources. In this paper
we work on multimodal biometric using three modalities face, ear and foot to find the optimal results using fuzzy fusion
mechanism and produces final identification decision via a fuzzy rules that enhance the quality of multimodalities biometric
system.
Health monitoring catalogue based on human activity classification using mac...IJECEIAES
In recent times, fitness trackers and smartphones equipped with different sensors like gyroscopes, accelerometers, global positioning system sensors and programs are used for recognizing human activities. In this paper, the results collected from these devices are used to design a system that can assist an application in monitoring a person’s health. The proposed system takes the raw sensor signals as input, preprocesses it and using machine learning techniques outputs the state of the user with minimum error. The objective of this paper is to compare the performance of different algorithms logistic regression (LR), support vector machine (SVM), k-nearest neighbor (k-NN) and random forest (RF). The algorithms are trained and tested with an original number of features as well as with transformed number of features (using linear discriminant analysis). The data with a smaller number of features is then used to visualize the high dimensional data. In this paper, each data point is mapped in the high dimensional data to two-dimensional data using t-distributed stochastic neighbor embedding technique. Overall, the first high dimensional data is visualized and compared with model’s performance with different algorithms and different number of coordinates.
Robust Analysis of Multibiometric Fusion Versus Ensemble Learning Schemes: A ...CSCJournals
Identification of person using multiple biometric is very common approach used in existing user
validation of systems. Most of multibiometric system depends on fusion schemes, as much of the
fusion techniques have shown promising results in literature, due to the fact of combining multiple
biometric modalities with suitable fusion schemes. However, similar type of practices are found in
ensemble of classifiers, which increases the classification accuracy while combining different
types of classifiers. In this paper, we have evaluated comparative study of traditional fusion
methods like feature level and score level fusion with the well-known ensemble methods such as
bagging and boosting. Precisely, for our frame work experimentations, we have fused face and
palmprint modalities and we have employed probability model - Naive Bayes (NB), neural
network model - Multi Layer Perceptron (MLP), supervised machine learning algorithm - Support
Vector Machine (SVM) classifiers for our experimentation. Nevertheless, machine learning
ensemble approaches namely, Boosting and Bagging are statistically well recognized. From
experimental results, in biometric fusion the traditional method, score level fusion is highly
recommended strategy than ensemble learning techniques.
Wearable sensor-based human activity recognition with ensemble learning: a co...IJECEIAES
The spectacular growth of wearable sensors has provided a key contribution to the field of human activity recognition. Due to its effective and versatile usage and application in various fields such as smart homes and medical areas, human activity recognition has always been an appealing research topic in artificial intelligence. From this perspective, there are a lot of existing works that make use of accelerometer and gyroscope sensor data for recognizing human activities. This paper presents a comparative study of ensemble learning methods for human activity recognition. The methods include random forest, adaptive boosting, gradient boosting, extreme gradient boosting, and light gradient boosting machine (LightGBM). Among the ensemble learning methods in comparison, light gradient boosting machine and random forest demonstrate the best performance. The experimental results revealed that light gradient boosting machine yields the highest accuracy of 94.50% on UCI-HAR dataset and 100% on single accelerometer dataset while random forest records the highest accuracy of 93.41% on motion sense dataset.
K-Medoids Clustering Using Partitioning Around Medoids for Performing Face Re...ijscmcj
Face recognition is one of the most unobtrusive biometric techniques that can be used for access control as well as surveillance purposes. Various methods for implementing face recognition have been proposed with varying degrees of performance in different scenarios. The most common issue with effective facial biometric systems is high susceptibility of variations in the face owing to different factors like changes in pose, varying illumination, different expression, presence of outliers, noise etc. This paper explores a novel technique for face recognition by performing classification of the face images using unsupervised learning approach through K-Medoids clustering. Partitioning Around Medoids algorithm (PAM) has been used for performing K-Medoids clustering of the data. The results are suggestive of increased robustness to noise and outliers in comparison to other clustering methods. Therefore the technique can also be used to increase the overall robustness of a face recognition system and thereby increase its invariance and make it a reliably usable biometric modality.
Gated recurrent unit decision model for device argumentation in ambient assis...IJECEIAES
The increasing elderly population worldwide is facing a variety of social, phys- ical, and cognitive issues, such as walking problems, falls, and difficulties in performing daily activities. To support elderly people, continuous monitoring and supervision are needed. Due to the busy modern lifestyle of caretakers, taking care of elderly people is difficult. As a result, many elderly people pre- fer to live independently at home without any assistance. To help such people, an ambient assisted living (AAL) environment is provided that monitors and evaluates the daily activities of elderly individuals. An AAL environment has heterogeneous devices that interact, and exchange information of the activities performed by the users. The devices can be involve in an argumentation about the occurrence of an activity thus leading to generate conflicts. To address this issue, the paper proposes a gated recurrent unit (GRU) learning techniques to facilitate decision-making for device argumentation during activity occurrences. The proposed model is used to initially classify user activities and each sensor value status. Then a novel method is used to identify argumentation among de- vices for activity occurrences in the classified user activities. Later, the GRU decision making model is used to resolve the argumentation and to identify the target activity that occurred. The result of the proposed model is compared with other existing techniques. The proposed model outperformed the other existing methods with an accuracy of 85.45%, precision of 72.32%, recall of 65.83%, and F1-Score of 60.22%.
A Fast and Accurate Palmprint Identification System based on Consistency Orie...IJTET Journal
Abstract — A palmprint identification system is a relatively most promising physiological biometric approach to identify the person. The numbers of palmprint recognition based biometric system have been successfully applied for real world access to control applications. A typical palmprint identification system identifies a query palmprint and matching it with the template stored in the database and comparing the similarity score with a pre-defined threshold. The Consistency Orientation Pattern (COP) hashing method is implemented in this work to enforce the fast search and to obtain the accurate result. Orientation pattern (OP) is defined as a collection of orientation features at arbitrary positions. The principal palm line is a kind of evident and stable features in palmprint images, and the orientation features in this region are expected to be more consistent than others. Using the orientation and response features extracted by steerable filter and gives an analysis on the consistency of orientation features, and then introduces a method to construct COP using the consistent features. Those features can be used as the indexes to the target template. Because the COP is very stable across the samples of the same subject, the COP hashing method can find the target template quickly. This method can lead to early termination of the searching process.
Biometrics Authentication of Fingerprint with Using Fingerprint Reader and Mi...TELKOMNIKA JOURNAL
The idea of security is as old as humanity itself. Between oldest methods of security were
included simple mechanical locks whose authentication element was the key. At first, a universal–simple
type, later unique for each lock. A long time had mechanical locks been the sole option for protection
against unauthorized access. The boom of biometrics has come in the 20th century, and especially in
recent years, biometrics is much expanded in the various areas of our life. Opposite of traditional security
methods such as passwords, access cards, and hardware keys, it offers many benefits. The main benefits
are the uniqueness and the impossibility of their loss. The main benefits are the uniqueness and the
impossibility of their loss. Therefore we focussed in this paper on the the design of low cost biometric
fingerprint system and subsequent implementation of this system in praxtise. Our main goal was to create
a system that is capable of recognizing fingerprints from a user and then processing them. The main part
of this system is the microcontroller Arduino Yun with an external interface to the scan of the fingerprint
with a name Adafruit R305 (special reader). This microcontroller communicates with the external database,
which ensures the exchange of data between Arduino Yun and user application. This application was
created for (currently) most widespread mobile operating system-Android.
As we know the fingerprint is unique of every living objects. It is quite difficult to find out the prints.
Usually the Forensics use Fine powder and duct tapes to identify the prints of living object. As powder is
exceptionally muddled, so such molecule can cause loss of information after that examination the information is
coordinated with the system. The proposed system consists of an embedded device in which it consists of ultra
light to glow the fingerprints details. After that we can detect the fingerprint, analysis and it will checks on the
database, and it will return the output after matching. For matching and analysis of the Fingerprint, we will be
using the Algorithm for matching.
Using Brain Waves as New Biometric Feature for Authenticating a Computer User...CSCJournals
In this paper we propose an Electroencephalogram based Brain Computer Interface as a new modality for Person Authentication and develop a screen lock application that will lock and unlock the computer screen at the users will. The brain waves of the person, recorded in real time are used as password to unlock the screen. Data fusion from 14 sensors of the Emotiv headset is done to enhance the signal features. The power spectral density of the intermingle signals is computed. The channel spectral power in the frequency band of alpha, beta and gamma is used in the classification task. A two stage checking is done to authenticate the user. A proximity value of 0.78 and above is considered a good match. The percentage of accuracy in classification is found to be good. The essence of this work is that the authentication is done in real time based on the meditation task and no external stimulus is used.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
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Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Vaccine management system project report documentation..pdf
FEATURE EXTRACTION METHODS FOR IRIS RECOGNITION SYSTEM: A SURVEY
1. International Journal of Computer Science & Information Technology (IJCSIT) Vol 14, No 1, February 2022
DOI: 10.5121/ijcsit.2022.14107 99
FEATURE EXTRACTION METHODS FOR IRIS
RECOGNITION SYSTEM: A SURVEY
Tara Othman Qadir1
, Nik Shahidah Afifi Md Taujuddin2
, Sundas Naqeeb Khan3
1, 2
Faculty of Electrical and Electronic Engineering,
Universiti Tun Hussein Onn Malaysia (UTHM), 86400, Parit Raja, Johor, Malaysia
3
Faculty of Computer Science and Information Technology,
Universiti Tun Hussein Onn Malaysia, 86400, Johor, Malaysia
ABSTRACT
Protection has become one of the biggest fields of study for several years, however the demand for this is
growing exponentially mostly with rise in sensitive data. The quality of the research can differ slightly from
any workstation to cloud, and though protection must be incredibly important all over. Throughout the past
two decades, sufficient focus has been given to substantiation along with validation in the technology
model. Identifying a legal person is increasingly become the difficult activity with the progression of time.
Some attempts are introduced in that same respect, in particular by utilizing human movements such as
fingerprints, facial recognition, palm scanning, retinal identification, DNA checking, breathing, speech
checker, and so on. A number of methods for effective iris detection have indeed been suggested and
researched. A general overview of current and state-of-the-art approaches to iris recognition is presented
in this paper. In addition, significant advances in techniques, algorithms, qualified classifiers, datasets and
methodologies for the extraction of features are also discussed.
KEYWORDS
Bio-metric traits, iris patterns, feature extraction, SVM, wavelet transform, iris security.
1. INTRODUCTION
The most significant security issue today is verification; if researchers can enhance this area, it
implies they are reducing security threats. Various secure techniques were used, including
security, but today a biometric technology known as iris recognition provides security in terms of
verification. Humans live in a safe environment owing to the unique iris pattern, but they also
have evil genius brains that can break the protection. As a result, academics are working to
develop more secure iris recognition technologies for a more safe society [1].
There are three focused categories of verification, such as starting from password, but this was a
very weak way to secure any system or object from hackers. The next method was card or token,
but that was also a very low-level security method. Anyone could present a card or token on their
own. The last step for security is biometric, and this method provides real security to
verification. According to the biometric method, no one can emulate or steal natural human
patterns [2 - 3].
Verification of a person based on physiological and behavioral aspects. Face, finger prints, palm
and hand geometry, DNA, retinal and iris trends are some of the most commonly observed
physical aspects in a person, while signatures, tone of voice, walking style, and keystrokes are
2. International Journal of Computer Science & Information Technology (IJCSIT) Vol 14, No 1, February 2022
100
some of the most frequently observed behavioral aspects. From all of these above patterns, the
iris is the only method that is used for security verification [4].
Now a question arises about the word biometric. What is a biometric? It consists of two words.
Bios means life and metrikos means measurement, so when researchers use these two words
together, it becomes biometric. Therefore, a biometric system capable of identifying a person's
traits stands upon a feature vector [7].
Biometric systems consist of four major parts, such as the sensor unit, feature extraction element,
matching pattern, and decision response. Consequently, when a biometric system is applied to a
human trait, there are four basic conditions that a human must have, like entirety, uniqueness,
immovability, and collectability. There is a comparison between some biometric systems
according to their factors in terms of High (H), Medium (M) and Low (L) in table 1 [8].
TABLE 1. Comparison between biometric systems with their factors
In the modern age of secure applications, there are some traditional issues which have a great
impact on biometric systems, as described in Table 2 with their impact factor also in terms of
High, Medium, and Low [8].
TABLE 2. Biometric system traditional factors with their impact
As a result, iris recognition is a fully systematic biometric system in which issues are resolved
using various mathematical methods, and these methods are directly applied to individual eye
Biometric traits Entirety Uniqueness Immovability Collectability
Face recognition H L M H
Walking style M L L H
Keystroke dynamics L L L M
Odor H H H L
Ear M M H M
Hand geometry M M M H
Finger print M H H M
Retina H H M L
Palm print M H H M
Tone of voice M L L M
DNA H H H L
Signature L L L H
Iris H H H M
Biometric traits Performance Acceptability Circumvention
Face recognition L H H
Walking style L H M
Keystroke dynamics L M M
Odor L M L
Ear M H M
Hand geometry M M M
Finger print H M M
Retina H L L
Palm print H M M
Tone of voice L H H
DNA H L L
Signature L H H
Iris H L L
3. International Journal of Computer Science & Information Technology (IJCSIT) Vol 14, No 1, February 2022
101
images that are considered distinctive [9 - 11]. There are many possible approaches which can be
used for iris recognition, but formally, researchers divided these approaches into three known
categories, such as supervised, unsupervised, and semi-supervised approaches. In supervised
approaches, trained data is available for testing by using different classifiers, while according to
unsupervised learning approaches, using unlabelled data, the working style of this approach is
slightly different from the supervised approach. If the data pool has a smaller amount of trained
data and a huge amount of untrained data, then researchers recommend the semi-supervised
approaches.
The first section contains an introduction to the study that is relevant to the research. The second
section is about the related research work, and the third portion describes the methodology of the
research. The results and discussion section is under the umbrella of the fourth portion of the
study, and at the end, the conclusion is included as a final discussion.
2. LITERATURE REVIEW
There are some main contributed articles that are considered related works. Due to certain
resolving issues, iris recognition systems are considered the main stream for security verification
of individuals. Nanik Suciati [12] presents an automatic recognition system for a person's
identification based on eye image. Canny Edge Detection (CED) with Hough Transform
techniques used for iris detection, followed by features selected by Wavelet Transform at the last
Support Vector Machine (SVM) classifier trained for feature representation, provides 93.5% of
the results. In [13], researchers worked on optimizing attribute mining according to the wavelet
task, while for the similarity method, they used multi-class SVM with an ant colony algorithm
and gave better outcomes in terms of performance.
Tejas's [14] research concept is based on energy compression, and three different Self Mutated
Hybrid Wavelet Transforms (SMHWT) methods are used to generate feature vectors.
Characteristics basic purpose of this research is to reduce vector size, with the help of partial
energy and the Genuine Acceptance Rate (GAR) metric. Cosine-Haar provides the best GAR
accuracy rate. Researchers [15] provide scattering and textural feature sets for the reduction of
dimensionality according to the Principle Component Analysis (PCA) method and the minimum
distance classifier algorithm, which are also used for matching and get a 99.2% accuracy
rate. Kiran [16] gives the idea of vigorous segmentation of detectable iris examples while
estimating the radius of the iris with a new deep sparse filtering algorithm for unsupervised
learning. The proposed method shows 85% accuracy in correct results on both the existing
dataset and the newly generated dataset VSSIRIS. Authors [17] give the idea of attribute mining
the name "vigorous keypoints method". In this method, they merge three detectors as regards
SIFT features for corresponding score points. The unions take care of the calculation of weights
with summation regulations and provide competitive performance as compared to baseline
methods.
Lydia Elizabeth [18] presents her work in 2014 on a grid-based algorithm for feature extraction
that combines Singular Value Detection (SVD) and Discrete Wavelet Transform (DWT).
Therefore, this hybrid process offers a powerful, protected, and imperceptible watermarking
method with a minimum fault acceptance rate in good behavior. Imen Tajouri [19] improves on
Rai's algorithm by combining HAAR wavelet, 2D Log Gabor, and a monogenic filter for feature
extraction. This shows the 94.45% empirical results of the proposed method as compared to the
Daubechies wavelet and Histogram of Oriented Gradient (HOG). A deep learning approach
named convolutional neural network is integrated with a fusion method for iris recognition [43].
The feed forward mechanism proposed along a clustering method k-mean for the iris feature
extraction. The approach reduces the calculated time and size of source link as well as improves
4. International Journal of Computer Science & Information Technology (IJCSIT) Vol 14, No 1, February 2022
102
the iris recognition [44]. An intelligent method presented for iris feature extraction and matching
activity in which the two hybrid methods used for this activity. Besides this, machine learning
algorithm is also include in the research as apart of matching approach which gives more efficient
results [45].
To address the low false rejection issue in feature extraction, the proposed Combined Directional
Wavelet Filter Bank (CDWFB) [20] algorithm combines the Directional Wavelet Filter Bank
(DWFB) and the Rotated Directional Wavelet Filter Bank (RDWFB). This approach extracts the
texture of the iris in 12 directions and provides excellent results as compared to more exciting
approaches. Researchers proposed [21] a hybrid technique design based on sparse demonstration,
including three classifiers for classes’ short list and further work on classes after that work
combining these classifiers with genetic algorithms to provide the best results. Table 3 shows the
considered articles as reviewed for related work and explains the main contributions of the
researchers.
TABLE 3. Biography of under consideration articles
Author name Article name
Search
engine
Amol D. Rahulkar and
Raghunath S. Holambe
[14]
Partial iris feature extraction and recognition based on a new
combined directional and rotated directional wavelet filter
banks
Elsevier
Vijay Prakash Sharma,
et al [7]
Improved Iris Recognition System using Wavelet Transform
and Ant Colony Optimization
IEEE
Lydia Elizabeth. B, et
al [12]
A grid based iris biometric watermarking using wavelet
transform
IEEE
Shervin Minaee, et al
[9]
Iris recognition using scattering transform and textural features IEEE
Kiran B. Raja, et al
[10]
Smartphone based visible iris recognition using deep sparse
filtering
Elsevier
Nanik Suciati, et al [6]
Feature Extraction Using Statistical Moments of Wavelet
Transform for Iris Recognition
IEEE
Tejas H. Jadhav and
Jaya H. Dewan [8]
Iris Recognition using Self Mutated Hybrid Wavelet Transform
using Cosine, Haar, Hartley and Slant Transforms with Partial
Energies of Transformed Iris Images
IJCA
Yuniol Alvarez-
Betancourt and Miguel
Garcia-Silvente [11]
A keypoints-based feature extraction method for iris
recognition under variable image quality conditions
Elsevier
Imen Tajouri, et al [13]
An Efficient Iris Texture Analysis Based On HAAR Wavelet
2D Log Gabor and Monogenic Filter
IEEE
Ashok K Bhateja, et al
[15]
Iris recognition based on sparse representation and k-nearest
subspace with genetic algorithm
Elsevier
5. International Journal of Computer Science & Information Technology (IJCSIT) Vol 14, No 1, February 2022
103
3. METHODOLOGY
Iris recognition is performed by the different biometric systems. Due to certain specifications, the
evaluation process of iris recognition systems is divided into four major modules, which are
mentioned in Figure 1.
The very first step of iris recognition is acquiring the iris images from different types of objects
through electronic devices like cameras or sensors etc. Each image has elucidation, location area
among corporeal incarcerate structure, and other factors such as occlusion, illumination, and pixel
extent play an important role in image eminence [22].
The second step is early stage processing, in which we check the iris liveness and edge, pupil,
eyelid, normalization, subtraction of iris etc. Through iris liveness recognition, the security
system can check if the focal object is alive because there is an option in which biometric aspects
are employed illegitimately. Localization of the iris and pupil is another important preprocessing
step that was developed by Zhaofeng [5 - 6].
As a result, the parabolic arcs perform conformant of the eyelids and then plot this extorted iris
area according to the normalization. All forces composition [23] comes from the commencement
of the summation of points which examine the iris and pupil centre within the radius. Some
functions attained iris boundaries through applied form in [24]. The basic law of iris localization
is based on incline strength along consistency divergence [25].
Classification is performed through extracted aspects of iris images in the third step, where some
aspects have important variants such as 90° axis, range and dimensions of pupil, strength,
direction according to ellipsoid shape, and all the features snatched from the iris images which
are useful for security verification are organized in this step. The last step used processed iris
images along with stored images for the matching process [26]. Due to inter-class and intra-class
variables, classification issues can be resolved. Table 4 describes some important methods of iris
recognition according to their influence on results in the form of performance, where Equal Error
Rate (EER), False Rejection Rate (FRR) and False Acceptance Rate (FAR) are used as
performance measures.
Image acquisition
Matching/Recognition
Feature extraction
Preprocessing
Image adequate
through electronic
devices or from
stored database
This early stage
required methods/
techniques for
cleanliness of
noisy data
Unique units of
images fetched
by different
methods
Decision regarding
acceptance or
rejection perform in
this stage
FIGURE 1. Iris recognition system
6. International Journal of Computer Science & Information Technology (IJCSIT) Vol 14, No 1, February 2022
104
TABLE 4. Iris patterns based methods with their performance and average time
4. RESULTS AND DISCUSSION
Table 5 shows the performance of the under consideration articles by SVM, PCA, different
algorithms and classifiers with their accuracy. Normally, SVM used with the combination of
some type of filters and statistical methods such as SVM with wavelet transform and colony
Methods Reference
Stored patterns
in DB
Performance
Average time
taken (seconds)
Phase based
method
Daugman
[27,28]
4258 images EER: 0.08% 0.71, 0.68
Martin Roche
[29]
300 images FRR: 8% 0.89
Masek [30] 624 images
FAR: 0.005% and
FRR: 0.238%
0.92
Xiaomei Liu
[31]
12000 images
(ICE)
Recognition rate:
96.61%
0.78
Karen
Hollingsworth
[32]
(i) 1226 images
from 24 subjects
(ICE)
(ii) 1061 videos
from 296 eyes
(iii) ICE database
(iv) 1263 images
from 18 subjects
(ICE)
(i)HD=7.48
(ii)EER=3.88x10-3,
FRR =7.61x10-6,
FAR=0.001
(iii) HD=0.15
(iv)FRR=0.271, FAR
= 0.001, EER=0.068
for large pupil subset
Null
Texture analysis
based method
Wildes [33, 34,
35]
60 images EER: 1.76% 0.62, 0.69, 0.78
Emine Krichen
[36]
700 images
Improvement in
FAR: 2% and FRR:
11.5%
0.88
Zero crossing
representation
method
Boles [37] Real images EER: 8.13% 0.69
Intensity
variations based
method
Li Ma [26, 38]
2245 images
(CASIA)
Correct Recognition
Rate: 94.33%.
0.77, Null
Jong Gook Ko
[39]
(i) 820 images
from 82
individuals
(ii) 756 images
(CASIA)
Recognition rate:
98.21%
0.66
N. Tajbakhsh
[40]
1877 images
(UBIRIS)
ERR: 0.66%, FRR:
4.10% and FAR:
0.01%
0.71
Independent
Component
Analysis (ICA)
based method
Ya Ping Haung
[41]
Real images
Blurred iris: 81.3%,
Variant illumination:
93.8% and Noise
interference: 62.5%
0.65
Continuous
Dynamic
Programming
based method
Radhika [42]
(i)1205 images
(UBIRIS)
(ii)1200 images
(CASIAv2)
Acceptance Rate:
98%
Rejection Rate 97%
Null
7. International Journal of Computer Science & Information Technology (IJCSIT) Vol 14, No 1, February 2022
105
gives 93.5% and 98% results respectively. On the other hand, PCA was used with distance
classifiers and provided better results, like 99.2% accuracy. The Deep Sparse Algorithm is a
filtering algorithm used for the VSSIRIS dataset and has shown 85% accuracy in empirical
tests. The CED algorithm is based on grid watermarking. This is used for the global iris
recognition dataset and minimizes the fault acceptance and error rate by approximately 77%. The
Genetic Algorithm (GA) is associated with three classifiers and helps to reduce the execution
time. There are many algorithms used for feature extraction, like enhancement in Rai’s algorithm
integrated with filters, while on the basis of keypoints extraction, there are marginal
improvements among three detectors such as Harris, Hessian, and Fast Laplace. For the reduction
of feature vector size, researchers used the self-mutated hybrid wavelet transform method and
adequate 14% improvement in the results.
Figure 2 shows the testing results of articles in diverse domains that contain the time and
frequency developed through the measurements of performance. Consequently, figure 3 describes
the measurement results in terms of performance according to their relevant datasets, and several
feature extraction methods and algorithms were applied to these datasets and improved the angle
of performance and accuracy. In figure 4, we select the articles that have diversity in methods
such as phase-based methods, texture analysis methods, zero crossing representation based
methods, intensity variations based methods, independent component analysis based methods,
and continuous dynamic programming based methods along with their performance according to
the FAR and FRR with recognition and error rate.
TABLE 5. Summary of performance under reviewed articles with different applied methods
Task Approach Dataset Result Primary objectives
Limitations/f
uture work
Iris
recogniti
on
system
[12]
SVM with
Wavelet
transform
CASIA
eye
image
93.5%
Detection of iris area with
suitable selected features and
then representation of these
features are the focus
objectives of this research.
Improvement
in results
regarding
accuracy and
execution time
Selection
of
optimize
d feature
[13]
SVM with ant
colony
CASIA
eye
image
99% for
FAR and
98% for
FFR
Selection and optimization
operations perform with the
help of multi class SVM and
ant colony process.
Reduction of
computational
time
Feature
vector
size
reduction
[14]
Self mutated
hybrid
wavelet
transforms
Palacky
Universit
y Iris DB
14%
improve
ment
The SMHWT reduce the
feature vector size and
Cosine-Haar used partial
energy with best
improvement in GAR
function.
Color spaces
use for better
performance
Dimensio
nality
reduction
of feature
vector
[15]
Principal
component
analysis
(PCA) with
minimum
distance
classifier
Iris DB
collected
by IIT
Delhi
99.2%
Reduce dimensions of two
proposed feature sets
according to PCA and
algorithm used for best
accuracy.
Proposed set
of features test
on other
datasets and
biometric
detection
issues
Robust
segmenta
tion for
iris
recogniti
deep sparse
filtering
algorithm
with
VSSIRIS
BIPLab
DB and
VSSIRIS
newly
created
85%
accuracy
A deep sparse filtering
method used for robust
segmentation of observable
range iris recognition
provides high outcomes on
Supervised
learning
improve the
accuracy
8. International Journal of Computer Science & Information Technology (IJCSIT) Vol 14, No 1, February 2022
106
on [16] dataset DB newly created dataset.
Feature
extractio
n [17]
Keypoints-
based feature
extraction
method
CASIA-
IrisV4-
Interval,
MMU2,
and
UBIRIS
1DB
68%
Keypoints feature extraction
combine three detectors like
Harris, Hessian and Fast
Laplace as a SIFT features for
matching score level and
calculate the weights for
attain better performance.
Implementatio
n of real time
application
Feature
extractio
n [18]
Grid based
approach
used Canny
Edge
Detection
(CED)
algorithm
Global
iris
recognitio
n dataset
77%
Grid based watermarking
algorithm used with a hybrid
SVD and DWT for
minimizing fault acceptance
and error rate.
Watermarking
algorithm
accuracy
Feature
extractio
n [19]
Rai’s
algorithm for
attribute
extraction
CASIA
V1.0 and
CASIA
V3.0
94.45%
Enhance the Rai’s algorithm
with combination of
monogenic filter and 2D Log
Gabor filter
Gabor Ordinal
Measures
GOM) test for
feature
extraction
Feature
extractio
n [20]
Combined
Directional
Wavelet
Filter Bank
(CDWFB)
proposed
approach
UBIRIS
and
MMU1
DBs
99%
accuracy
for
UBIRIS
and 98%
accuracy
for
MMU1
CDWFB a new approach for
feature extraction consists of
two different filter banks and
provide better performance in
terms of accuracy.
Improve the
performance
on real time
applications
Reductio
n of time
[21]
Three
classifiers
with genetic
algorithm
CASIA
and IITD
DBs
99.43%
on
CASIA
and
99.20%
on IITD
DBs
accuracy
Three classifiers used with
genetic algorithm for sparse
representation for reducing
the time.
Improve FRR
and FAR with
accuracy on
real time
applications
9. International Journal of Computer Science & Information Technology (IJCSIT) Vol 14, No 1, February 2022
107
FIGURE 2. Year wise distribution of articles
FIGURE 3. Accuracy performance measured by different datasets
FIGURE 4. Iris recognition methods with their approved performance
2010
2012
2014
2016
2018
[10]
[11]
[14]
[15]
[12]
[13]
[6]
[7]
[9]
[8]
Elsevier IEEE IJCA
Year
wise
distribution
Search engines
Frequency count regarding
references
0
0.2
0.4
0.6
0.8
1
Performance
Datasets
Accuracy
0
0.2
0.4
0.6
0.8
1
Boles
[31]
EER:
Emine
Krichen
…
Jong
Gook
Ko
…
Martin
Roche
…
Masek
[24]
FRR:
N.
Tajbakhsh
…
Radhika
[36]
…
Wildes
…
Ya
Ping
Haung
…
Performance
Iris patterns references
10. International Journal of Computer Science & Information Technology (IJCSIT) Vol 14, No 1, February 2022
108
5. CONCLUSION
This paper presents a comprehensive review of state-of-the-art techniques in iris recognition. It
comprises of methodologies, algorithms and techniques related to this domain like feature
extraction etc. Finally, the techniques have been evaluated in terms of efficiency. Different
evaluation criteria have been employed to find the variations in the methods proposed so far in
the literature and which method is better and in what capacity. The research also provides a wide
range of other articles and average time along their algorithms, methods, procedures and
approaches performance measure. It also includes the comparison of different researches
outcomes and give a brief description about all. The survey can be a good platform for fresh and
intermediate researchers in the field of iris recognition.
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AUTHORS
Tara Othman Qadir is a PhD student in Faculty of Electrical and Electronic Engineering,
Universiti Tun Hussein Onn Malaysia (UTHM), 86400, Parit Raja, Johor, Malaysia. She is
a lecturer at Department of Software and Informatics, College of Engineering, Salahaddin
University, Erbil, Kurduistan, Iraq. She got her MSc in Security and BSc, in Computer
Science in Baghdad and used to be a programmer in Iraqi Commission for Computer
Informatics, Scientific Technology Information Center in Baghdad.
Dr. Nik Shahidah Afifi Md Taujuddin is a senior lecturer at Electronic Engineering
Department, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn
Malaysia. She obtained her PhD in Image Processing from the Universiti Tun Hussein
Onn Malaysia and her MSc and BSc (Hons) in Electrical and Electronic Engineering from
the Universiti Teknologi Malaysia. She also used to be a visiting researcher at Nagaoka
University of Technology, Japan. Her research area is Image Processing, Computer
Security and Computer Networks.
Sundas Naqeeb Khan is a PhD scholar at Faculty of Computer Science and Information
Technology, Universiti Tun Hussein Onn Malaysia. She obtained her MSCS degree with
distinction from The University of Lahore, Pakistan and her MSc from Fatima Jinnah
Women University, Pakistan. She also used to be a visiting lecturer in The University of
Punjab, Pakistan, and Mirpur University of Science and Technology, Pakistan. Her
research area is multi-disciplinary optimization, e-commerce, image processing, database
management, data mining, text mining, and electrical engineering.