Samer Atawneh - Academia.edu (original) (raw)

Papers by Samer Atawneh

Research paper thumbnail of Phishing Email Detection Model Using Deep Learning

Electronics

Email phishing is a widespread cyber threat that can result in the theft of sensitive information... more Email phishing is a widespread cyber threat that can result in the theft of sensitive information and financial loss. It uses malicious emails to trick recipients into providing sensitive information or transferring money, often by disguising themselves as legitimate organizations or individuals. As technology advances and attackers become more sophisticated, the problem of email phishing becomes increasingly challenging to detect and prevent. In this research paper, the use of deep learning techniques, including convolutional neural networks (CNNs), long short-term memory (LSTM) networks, recurrent neural networks (RNNs), and bidirectional encoder representations from transformers (BERT), are explored for detecting email phishing attacks. A dataset of phishing and benign emails was utilized, and a set of relevant features was extracted using natural language processing (NLP) techniques. The proposed deep learning model was trained and tested using the dataset, and it was found that...

Research paper thumbnail of Blockchain-Based Decentralized Authentication Modeling Scheme in Edge and IoT Environment

IEEE Internet of Things Journal, 2021

Authentication is the first entrance to kinds of information systems; however, traditional center... more Authentication is the first entrance to kinds of information systems; however, traditional centered single-side authentication is weak and fragile, which has security risk of single-side failure or breakdown caused by outside attacks or internal cheating. In the edge and Internet-of-Things (IoT) environment, blockchain can apply edge devices to better serve the IoT and provide decentralized high security service solutions. In this article, we proposed a blockchain-based decentralized authentication modeling scheme (named BlockAuth) in edge and IoT environment to provide a more secure, reliable, and strong fault tolerance novel solution, in which each edge device is regarded as a node to form a blockchain network. We designed secure registration and authentication strategy, blockchain-based decentralized authentication protocol, and developed the blockchain consensus, smart contract, and implemented a whole blockchain-based authentication platform for the feasibility, security, and performance evaluation. The analysis and evaluation show that the proposed BlockAuth scheme provides a more secure, reliable, and strong fault tolerance decentralized novel authentication with high-level security driven configuration management. The proposed BlockAuth scheme is suitable for password-based, certificate-based, biotechnology-based, and token-based authentication for high-level security requirement system in edge and IoT environment.

Research paper thumbnail of Dynamic Multimedia Encryption Using a Parallel File System Based on Multi-Core Processors

Cryptography

Securing multimedia data on disk drives is a major concern because of their rapidly increasing vo... more Securing multimedia data on disk drives is a major concern because of their rapidly increasing volumes over time, as well as the prevalence of security and privacy problems. Existing cryptographic schemes have high computational costs and slow response speeds. They also suffer from limited flexibility and usability from the user side, owing to continuous routine interactions. Dynamic encryption file systems can mitigate the negative effects of conventional encryption applications by automatically handling all encryption operations with minimal user input and a higher security level. However, most state-of-the-art cryptographic file systems do not provide the desired performance because their architectural design does not consider the unique features of multimedia data or the vulnerabilities related to key management and multi-user file sharing. The recent move towards multi-core processor architecture has created an effective solution for reducing the computational cost and maximizi...

Research paper thumbnail of Using Artificial Intelligence to Predict Students’ Academic Performance in Blended Learning

Sustainability

University electronic learning (e-learning) has witnessed phenomenal growth, especially in 2020, ... more University electronic learning (e-learning) has witnessed phenomenal growth, especially in 2020, due to the COVID-19 pandemic. This type of education is significant because it ensures that all students receive the required learning. The statistical evaluations are limited in providing good predictions of the university’s e-learning quality. That is forcing many universities to go to online and blended learning environments. This paper presents an approach of statistical analysis to identify the most common factors that affect the students’ performance and then use artificial neural networks (ANNs) to predict students’ performance within the blended learning environment of Saudi Electronic University (SEU). Accordingly, this dissertation generated a dataset from SEU’s Blackboard learning management system. The student’s performance can be tested using a set of factors: the studying (face-to-face or virtual), percentage of attending live lectures, midterm exam scores, and percentage o...

Research paper thumbnail of Using Artificial Intelligence to Predict Customer Satisfaction with E-Payment Systems during the COVID-19 Pandemic

Journal of Mathematics

This study explores the impact of electronic payment systems on Saudi Arabia’s customer satisfact... more This study explores the impact of electronic payment systems on Saudi Arabia’s customer satisfaction during the COVID-19 pandemic. Descriptive analytical approach of a sample of 1,025 people living in Saudi Arabia was used to answer the study questions and test its hypotheses. Then, a new hybrid fuzzy inference system (HyFIS) is proposed to predict customer satisfaction during COVID-19 pandemic. The proposed system contemplates customer resistance (CR), access to technology (AT), privacy (PV), costs (CT), and speed of efficiency (SE) as the input variables and customer satisfaction (CS) as the output variable. Various statistical tests are utilized to determine the efficiency of input variables in the obtained data. The statistical tests are multicollinearity tests, reliability and validity, ordinal least square (OLS), fixed effect, and random development. As a result, we can determine each input variable’s direct and indirect impact on the CS. Under OLS, fixed effect, and unexpecte...

Research paper thumbnail of Improving Association Rules Accuracy in Noisy Domains Using Instance Reduction Techniques

Computers, materials & continua, 2022

Research paper thumbnail of Using Machine Learning to Build a Classification Model for IoT Networks to Detect Attack Signatures

International journal of Computer Networks & Communications, 2020

Internet of things (IoT) has led to several security threats and challenges within society. Regar... more Internet of things (IoT) has led to several security threats and challenges within society. Regardless of the benefits that it has brought with it to the society, IoT could compromise the security and privacy of individuals and companies at various levels. Denial of Service (DoS) and Distributed DoS (DDoS) attacks, among others, are the most common attack types that face the IoT networks. To counter such attacks, companies should implement an efficient classification/detection model, which is not an easy task. This paper proposes a classification model to examine the effectiveness of several machine-learning algorithms, namely, Random Forest (RF), k-Nearest Neighbors (KNN), and Naïve Bayes. The machine learning algorithms are used to detect attacks on the UNSW-NB15 benchmark dataset. The UNSW-NB15 contains normal network traffic and malicious traffic instants. The experimental results reveal that RF and KNN classifiers give the best performance with an accuracy of 100% (without nois...

Research paper thumbnail of A Survey of Phishing Email Filtering Techniques

IEEE Communications Surveys & Tutorials, 2013

Research paper thumbnail of Hybrid and Blind Steganographic Method for Digital Images Based on DWT and Chaotic Map

Journal of Communications, 2013

Research paper thumbnail of The Analysis of Current State of Agile Software Development

The agile software development methods are studied in this paper. Agile software development meth... more The agile software development methods are studied in this paper. Agile software development methodology was formally represented to the community of software engineering through twelve principles and four core values. Agility is considered the cornerstone of the agile software development. This contrasts with the plandriven technique that is explained in different conventional models (e.g. Waterfall). Currently, the agile development is an important development approach, which is derived from practical uses to encourage the cooperation between users and developers so that fast development processes could be supported, and to adapt with the modifications that are affecting the dynamic environment. Many agile methods are currently available in the literature with Scrum and Extreme Programming (XP) methods forming two most commonly used methods. This study demonstrates the value of applying the agile methods in developing software projects by analysing the current agile methods. The s...

Research paper thumbnail of Zero-Delay Broadcasting Protocol for Video on Demand over Mobile Ad Hoc Networks

Global Journal on Technology, 2013

Video on Demand (VOD) system is an electronic video rental system where the clients have the abil... more Video on Demand (VOD) system is an electronic video rental system where the clients have the ability to request and view the video at any time, which make the VOD system become an important technology for many applications. User waiting time, wireless coverage and bandwidth allocation are major challenges of VOD services over Mobile Ad Hoc Networks (MANET’s). The importance of this paper is to find a solution to reduce the delay. Numerous periodic VOD broadcasting protocols have been proposed to support a large number of receivers. Broadcasting is an efficient transmission scheme to provide on-demand service for very popular movies. This paper proposes an enhanced method for the Staggered Broadcast (SB) protocol, known as Zero-Delay Staggered Broadcast (ZDSB) method, where the logical channel of the Local Media Forward (LMF) is partitioned into sub-channels and video segments into sub-segments as well. The results showed that the proposed system is more efficient and better than oth...

Research paper thumbnail of Application of Metaheuristic Algorithms for Optimizing Longitudinal Square Porous Fins

Computers, Materials & Continua

Research paper thumbnail of Artificial Neural Networks for Prediction of Covid-19 in Saudi Arabia

Computers, Materials & Continua

Research paper thumbnail of Framework for Cybersecurity Centers to Mass Scan Networks

Intelligent Automation & Soft Computing

Research paper thumbnail of A Successful Framework for the ABET Accreditation of an Information System Program

Intelligent Automation & Soft Computing

Research paper thumbnail of Using Machine Learning to Build a Classification Model for IoT Networks to Detect Attack Signatures

Internet of things (IoT) has led to several security threats and challenges within society. Regar... more Internet of things (IoT) has led to several security threats and challenges within society. Regardless of the benefits that it has brought with it to the society, IoT could compromise the security and privacy of individuals and companies at various levels. Denial of Service (DoS) and Distributed DoS (DDoS) attacks, among others, are the most common attack types that face the IoT networks. To counter such attacks, companies should implement an efficient classification/detection model, which is not an easy task. This paper proposes a classification model to examine the effectiveness of several machine-learning algorithms, namely, Random Forest (RF), k-Nearest Neighbors (KNN), and Naïve Bayes. The machine learning algorithms are used to detect attacks on the UNSW-NB15 benchmark dataset. The UNSW-NB15 contains normal network traffic and malicious traffic instants. The experimental results reveal that RF and KNN classifiers give the best performance with an accuracy of 100% (without nois...

Research paper thumbnail of Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids

Energies

The penetration of distributed generators (DGs) in the existing power system has brought some rea... more The penetration of distributed generators (DGs) in the existing power system has brought some real challenges regarding the power quality and dynamic response of the power systems. To overcome the above-mentioned issues, the researchers around the world have tried and tested different control methods among which the computational intelligence (CI) based methods have been found as most effective in mitigating the power quality and transient response problems intuitively. The significance of the mentioned optimization approaches in contemporary ac Microgrid (MG) controls can be observed from the increasing number of published articles and book chapters in the recent past. However, literature related to this important subject is scattered with no comprehensive review that provides detailed insight information on this substantial development. As such, this research work provides a detailed overview of four of the most extensively used CI-based optimization techniques, namely, artificial...

Research paper thumbnail of A Survey of Fast Flux Botnet Detection With Fast Flux Cloud Computing

International Journal of Cloud Applications and Computing

A botnet refers to a set of compromised machines controlled distantly by an attacker. Botnets are... more A botnet refers to a set of compromised machines controlled distantly by an attacker. Botnets are considered the basis of numerous security threats around the world. Command and control (C&C) servers are the backbone of botnet communications, in which bots send a report to the botmaster, and the latter sends attack orders to those bots. Botnets are also categorized according to their C&C protocols, such as internet relay chat (IRC) and peer-to-peer (P2P) botnets. A domain name system (DNS) method known as fast-flux is used by bot herders to cover malicious botnet activities and increase the lifetime of malicious servers by quickly changing the IP addresses of the domain names over time. Several methods have been suggested to detect fast-flux domains. However, these methods achieve low detection accuracy, especially for zero-day domains. They also entail a significantly long detection time and consume high memory storage. In this survey, we present an overview of the various techniqu...

Research paper thumbnail of Collaborative Mobile-Learning Architecture Based on Mobile Agents

Electronics

The connection between collaborative learning and the new mobile technology has become tighter. M... more The connection between collaborative learning and the new mobile technology has become tighter. Mobile learning enhances collaborative learning as learners can access information and learning materials from anywhere and at any time. However, supporting efficient mobile learning in education is a critical challenge. In addition, incorporating technological and educational components becomes a new, complex dimension. In this paper, an efficient collaborative mobile-learning architecture based on mobile agents is proposed to enhance learning activity and to allow teachers and students to collaborate in knowledge and information transfer. A mobile agent can control its own actions, is able to communicate with other agents, and adapts in accordance with previous experience. The proposed model consists of four components: the learner agent, the teacher agent, the device agent and the social agent. The social agent plays the main role in the collaborative tasks since it is responsible for ...

Research paper thumbnail of A DCT domain smart vicinity reliant fragile watermarking technique for DIBR 3D-TV

Research paper thumbnail of Phishing Email Detection Model Using Deep Learning

Electronics

Email phishing is a widespread cyber threat that can result in the theft of sensitive information... more Email phishing is a widespread cyber threat that can result in the theft of sensitive information and financial loss. It uses malicious emails to trick recipients into providing sensitive information or transferring money, often by disguising themselves as legitimate organizations or individuals. As technology advances and attackers become more sophisticated, the problem of email phishing becomes increasingly challenging to detect and prevent. In this research paper, the use of deep learning techniques, including convolutional neural networks (CNNs), long short-term memory (LSTM) networks, recurrent neural networks (RNNs), and bidirectional encoder representations from transformers (BERT), are explored for detecting email phishing attacks. A dataset of phishing and benign emails was utilized, and a set of relevant features was extracted using natural language processing (NLP) techniques. The proposed deep learning model was trained and tested using the dataset, and it was found that...

Research paper thumbnail of Blockchain-Based Decentralized Authentication Modeling Scheme in Edge and IoT Environment

IEEE Internet of Things Journal, 2021

Authentication is the first entrance to kinds of information systems; however, traditional center... more Authentication is the first entrance to kinds of information systems; however, traditional centered single-side authentication is weak and fragile, which has security risk of single-side failure or breakdown caused by outside attacks or internal cheating. In the edge and Internet-of-Things (IoT) environment, blockchain can apply edge devices to better serve the IoT and provide decentralized high security service solutions. In this article, we proposed a blockchain-based decentralized authentication modeling scheme (named BlockAuth) in edge and IoT environment to provide a more secure, reliable, and strong fault tolerance novel solution, in which each edge device is regarded as a node to form a blockchain network. We designed secure registration and authentication strategy, blockchain-based decentralized authentication protocol, and developed the blockchain consensus, smart contract, and implemented a whole blockchain-based authentication platform for the feasibility, security, and performance evaluation. The analysis and evaluation show that the proposed BlockAuth scheme provides a more secure, reliable, and strong fault tolerance decentralized novel authentication with high-level security driven configuration management. The proposed BlockAuth scheme is suitable for password-based, certificate-based, biotechnology-based, and token-based authentication for high-level security requirement system in edge and IoT environment.

Research paper thumbnail of Dynamic Multimedia Encryption Using a Parallel File System Based on Multi-Core Processors

Cryptography

Securing multimedia data on disk drives is a major concern because of their rapidly increasing vo... more Securing multimedia data on disk drives is a major concern because of their rapidly increasing volumes over time, as well as the prevalence of security and privacy problems. Existing cryptographic schemes have high computational costs and slow response speeds. They also suffer from limited flexibility and usability from the user side, owing to continuous routine interactions. Dynamic encryption file systems can mitigate the negative effects of conventional encryption applications by automatically handling all encryption operations with minimal user input and a higher security level. However, most state-of-the-art cryptographic file systems do not provide the desired performance because their architectural design does not consider the unique features of multimedia data or the vulnerabilities related to key management and multi-user file sharing. The recent move towards multi-core processor architecture has created an effective solution for reducing the computational cost and maximizi...

Research paper thumbnail of Using Artificial Intelligence to Predict Students’ Academic Performance in Blended Learning

Sustainability

University electronic learning (e-learning) has witnessed phenomenal growth, especially in 2020, ... more University electronic learning (e-learning) has witnessed phenomenal growth, especially in 2020, due to the COVID-19 pandemic. This type of education is significant because it ensures that all students receive the required learning. The statistical evaluations are limited in providing good predictions of the university’s e-learning quality. That is forcing many universities to go to online and blended learning environments. This paper presents an approach of statistical analysis to identify the most common factors that affect the students’ performance and then use artificial neural networks (ANNs) to predict students’ performance within the blended learning environment of Saudi Electronic University (SEU). Accordingly, this dissertation generated a dataset from SEU’s Blackboard learning management system. The student’s performance can be tested using a set of factors: the studying (face-to-face or virtual), percentage of attending live lectures, midterm exam scores, and percentage o...

Research paper thumbnail of Using Artificial Intelligence to Predict Customer Satisfaction with E-Payment Systems during the COVID-19 Pandemic

Journal of Mathematics

This study explores the impact of electronic payment systems on Saudi Arabia’s customer satisfact... more This study explores the impact of electronic payment systems on Saudi Arabia’s customer satisfaction during the COVID-19 pandemic. Descriptive analytical approach of a sample of 1,025 people living in Saudi Arabia was used to answer the study questions and test its hypotheses. Then, a new hybrid fuzzy inference system (HyFIS) is proposed to predict customer satisfaction during COVID-19 pandemic. The proposed system contemplates customer resistance (CR), access to technology (AT), privacy (PV), costs (CT), and speed of efficiency (SE) as the input variables and customer satisfaction (CS) as the output variable. Various statistical tests are utilized to determine the efficiency of input variables in the obtained data. The statistical tests are multicollinearity tests, reliability and validity, ordinal least square (OLS), fixed effect, and random development. As a result, we can determine each input variable’s direct and indirect impact on the CS. Under OLS, fixed effect, and unexpecte...

Research paper thumbnail of Improving Association Rules Accuracy in Noisy Domains Using Instance Reduction Techniques

Computers, materials & continua, 2022

Research paper thumbnail of Using Machine Learning to Build a Classification Model for IoT Networks to Detect Attack Signatures

International journal of Computer Networks & Communications, 2020

Internet of things (IoT) has led to several security threats and challenges within society. Regar... more Internet of things (IoT) has led to several security threats and challenges within society. Regardless of the benefits that it has brought with it to the society, IoT could compromise the security and privacy of individuals and companies at various levels. Denial of Service (DoS) and Distributed DoS (DDoS) attacks, among others, are the most common attack types that face the IoT networks. To counter such attacks, companies should implement an efficient classification/detection model, which is not an easy task. This paper proposes a classification model to examine the effectiveness of several machine-learning algorithms, namely, Random Forest (RF), k-Nearest Neighbors (KNN), and Naïve Bayes. The machine learning algorithms are used to detect attacks on the UNSW-NB15 benchmark dataset. The UNSW-NB15 contains normal network traffic and malicious traffic instants. The experimental results reveal that RF and KNN classifiers give the best performance with an accuracy of 100% (without nois...

Research paper thumbnail of A Survey of Phishing Email Filtering Techniques

IEEE Communications Surveys & Tutorials, 2013

Research paper thumbnail of Hybrid and Blind Steganographic Method for Digital Images Based on DWT and Chaotic Map

Journal of Communications, 2013

Research paper thumbnail of The Analysis of Current State of Agile Software Development

The agile software development methods are studied in this paper. Agile software development meth... more The agile software development methods are studied in this paper. Agile software development methodology was formally represented to the community of software engineering through twelve principles and four core values. Agility is considered the cornerstone of the agile software development. This contrasts with the plandriven technique that is explained in different conventional models (e.g. Waterfall). Currently, the agile development is an important development approach, which is derived from practical uses to encourage the cooperation between users and developers so that fast development processes could be supported, and to adapt with the modifications that are affecting the dynamic environment. Many agile methods are currently available in the literature with Scrum and Extreme Programming (XP) methods forming two most commonly used methods. This study demonstrates the value of applying the agile methods in developing software projects by analysing the current agile methods. The s...

Research paper thumbnail of Zero-Delay Broadcasting Protocol for Video on Demand over Mobile Ad Hoc Networks

Global Journal on Technology, 2013

Video on Demand (VOD) system is an electronic video rental system where the clients have the abil... more Video on Demand (VOD) system is an electronic video rental system where the clients have the ability to request and view the video at any time, which make the VOD system become an important technology for many applications. User waiting time, wireless coverage and bandwidth allocation are major challenges of VOD services over Mobile Ad Hoc Networks (MANET’s). The importance of this paper is to find a solution to reduce the delay. Numerous periodic VOD broadcasting protocols have been proposed to support a large number of receivers. Broadcasting is an efficient transmission scheme to provide on-demand service for very popular movies. This paper proposes an enhanced method for the Staggered Broadcast (SB) protocol, known as Zero-Delay Staggered Broadcast (ZDSB) method, where the logical channel of the Local Media Forward (LMF) is partitioned into sub-channels and video segments into sub-segments as well. The results showed that the proposed system is more efficient and better than oth...

Research paper thumbnail of Application of Metaheuristic Algorithms for Optimizing Longitudinal Square Porous Fins

Computers, Materials & Continua

Research paper thumbnail of Artificial Neural Networks for Prediction of Covid-19 in Saudi Arabia

Computers, Materials & Continua

Research paper thumbnail of Framework for Cybersecurity Centers to Mass Scan Networks

Intelligent Automation & Soft Computing

Research paper thumbnail of A Successful Framework for the ABET Accreditation of an Information System Program

Intelligent Automation & Soft Computing

Research paper thumbnail of Using Machine Learning to Build a Classification Model for IoT Networks to Detect Attack Signatures

Internet of things (IoT) has led to several security threats and challenges within society. Regar... more Internet of things (IoT) has led to several security threats and challenges within society. Regardless of the benefits that it has brought with it to the society, IoT could compromise the security and privacy of individuals and companies at various levels. Denial of Service (DoS) and Distributed DoS (DDoS) attacks, among others, are the most common attack types that face the IoT networks. To counter such attacks, companies should implement an efficient classification/detection model, which is not an easy task. This paper proposes a classification model to examine the effectiveness of several machine-learning algorithms, namely, Random Forest (RF), k-Nearest Neighbors (KNN), and Naïve Bayes. The machine learning algorithms are used to detect attacks on the UNSW-NB15 benchmark dataset. The UNSW-NB15 contains normal network traffic and malicious traffic instants. The experimental results reveal that RF and KNN classifiers give the best performance with an accuracy of 100% (without nois...

Research paper thumbnail of Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids

Energies

The penetration of distributed generators (DGs) in the existing power system has brought some rea... more The penetration of distributed generators (DGs) in the existing power system has brought some real challenges regarding the power quality and dynamic response of the power systems. To overcome the above-mentioned issues, the researchers around the world have tried and tested different control methods among which the computational intelligence (CI) based methods have been found as most effective in mitigating the power quality and transient response problems intuitively. The significance of the mentioned optimization approaches in contemporary ac Microgrid (MG) controls can be observed from the increasing number of published articles and book chapters in the recent past. However, literature related to this important subject is scattered with no comprehensive review that provides detailed insight information on this substantial development. As such, this research work provides a detailed overview of four of the most extensively used CI-based optimization techniques, namely, artificial...

Research paper thumbnail of A Survey of Fast Flux Botnet Detection With Fast Flux Cloud Computing

International Journal of Cloud Applications and Computing

A botnet refers to a set of compromised machines controlled distantly by an attacker. Botnets are... more A botnet refers to a set of compromised machines controlled distantly by an attacker. Botnets are considered the basis of numerous security threats around the world. Command and control (C&C) servers are the backbone of botnet communications, in which bots send a report to the botmaster, and the latter sends attack orders to those bots. Botnets are also categorized according to their C&C protocols, such as internet relay chat (IRC) and peer-to-peer (P2P) botnets. A domain name system (DNS) method known as fast-flux is used by bot herders to cover malicious botnet activities and increase the lifetime of malicious servers by quickly changing the IP addresses of the domain names over time. Several methods have been suggested to detect fast-flux domains. However, these methods achieve low detection accuracy, especially for zero-day domains. They also entail a significantly long detection time and consume high memory storage. In this survey, we present an overview of the various techniqu...

Research paper thumbnail of Collaborative Mobile-Learning Architecture Based on Mobile Agents

Electronics

The connection between collaborative learning and the new mobile technology has become tighter. M... more The connection between collaborative learning and the new mobile technology has become tighter. Mobile learning enhances collaborative learning as learners can access information and learning materials from anywhere and at any time. However, supporting efficient mobile learning in education is a critical challenge. In addition, incorporating technological and educational components becomes a new, complex dimension. In this paper, an efficient collaborative mobile-learning architecture based on mobile agents is proposed to enhance learning activity and to allow teachers and students to collaborate in knowledge and information transfer. A mobile agent can control its own actions, is able to communicate with other agents, and adapts in accordance with previous experience. The proposed model consists of four components: the learner agent, the teacher agent, the device agent and the social agent. The social agent plays the main role in the collaborative tasks since it is responsible for ...

Research paper thumbnail of A DCT domain smart vicinity reliant fragile watermarking technique for DIBR 3D-TV