Kazy Noor-e-Alam Siddiquee | University of science and technology chittagong (original) (raw)

Papers by Kazy Noor-e-Alam Siddiquee

Computational Intelligence and Neuroscience

In this paper, an autonomous brain tumor segmentation and detection model is developed utilizing ... more In this paper, an autonomous brain tumor segmentation and detection model is developed utilizing a convolutional neural network technique that included a local binary pattern and a multilayered support vector machine. The detection and classification of brain tumors are a key feature in order to aid physicians; an intelligent system must be designed with less manual work and more automated operations in mind. The collected images are then processed using image filtering techniques, followed by image intensity normalization, before proceeding to the patch extraction stage, which results in patch extracted images. During feature extraction, the RGB image is converted to a binary image by grayscale conversion via the colormap process, and this process is then completed by the local binary pattern (LBP). To extract feature information, a convolutional network can be utilized, while to detect objects, a multilayered support vector machine (ML-SVM) can be employed. CNN is a popular deep l...

Wireless Communications and Mobile Computing, Apr 4, 2022

Sensor-based agriculture monitoring systems have limited outcomes on the detection or counting of... more Sensor-based agriculture monitoring systems have limited outcomes on the detection or counting of vegetables from agriculture fields due to the utilization of either conventional color transformations or machine learning-based methods. To overcome these limitations, this research is aimed at proposing an IoT-based smart agriculture monitoring system with multiple algorithms such as detection, quantification, ripeness checking, and detection of infected vegetables. This paper presents smart agriculture monitoring systems for Internet of Things (IoT) applications. The CHT has been applied to detect and quantify vegetables from the agriculture field. Using color thresholding and color segmentation techniques, defected vegetables have also been detected. A machine learning method-convolutional neural network (CNN) has been used for the development and implementation of all algorithms. A comparison between traditional methods and CNN has been simulated in MATLAB to find out the optimal method for its implementation in this agricultural monitoring system. Compared to the traditional methods, the CNN is the optimal method in this research work which performed better over the previously developed algorithms with an accuracy of more than 90%. As an example (case study), a tomato field in Chittagong, Bangladesh, was chosen where a camera-mounted mobile robot captured images from the agriculture field for which the proposed IoT-based smart monitoring system was developed. This system will benefit farmers through the digitally monitored output at an agriculture field in Bangladesh as well as in Malaysia. Since this proposed smart IoT-based system is still driven by bulky, costly, and limited powered sensors, in a future work, for the required power of sensors, this research work is aimed at the design and development of an energy harvester (hybrid) (HEH) based on ultralow power electronics circuits to generate the required power of sensors. Implementation of multiple algorithms using CNN, circular Hough transformation (CHT), color thresholding, and color segmentation methods for the detection, quantification, ripeness checking, and detection of infected crops.

Journal of Mathematics

The burst dropping ratio is witnessed in the contemporary literature as a considerable constraint... more The burst dropping ratio is witnessed in the contemporary literature as a considerable constraint of optical burst switching (OBS) networks that attained many researchers’ efforts in the recent past. Among the multiple practices endeavoring to reduce the burst drop ratio, the optimal burst scheduling is one dimension in this regard. The transmission channel scheduling and appropriate wavelength allocation are critical objectives to achieve optimal burst scheduling in regard to minimal burst drop ratio. Many of the scheduling models depicted in the contemporary literature aimed to achieve the optimum scheduling by electing the channels, which depend on optimum utilization of idle time. Some of the studies tried to select channels by any metrics of quality, and significantly minimal amount of studies focused on wavelength allocation for lowering BDR. Moreover, in regard to this, this study tried to achieve optimum wavelength allocation beneath manifold objective QoS metrics, which is ...

Wireless Communications and Mobile Computing, Apr 29, 2022

The technology grows quickly in the area of the VLSI physical design; it is crucial to integrate ... more The technology grows quickly in the area of the VLSI physical design; it is crucial to integrate the greater number of transistors and parts into a very small range. Before the placement is completed, the physical and technical positioning of the blocks in the chip area is planned, which is nothing but floor planning. In order to lessen the placement region in the physical layout, floor planning must be carried out effectively. This paper proposes a blended harmony search and particle swarm optimization (BHSPS) algorithm which is the deliberate blend of the harmony search (HS) algorithm, and the particle swarm optimization (PSO) algorithm is proposed to acquire the central goal of the VLSI placement strategy. The objective here is to lessen the field of plan. The MATLAB code for the blended harmony search and particle swarm optimization (BHSPS) algorithm is compiled, and investigations were carried out for better examination through the standard MCNC, i.e., North Carolina Microelectronics Center benchmark circuits.

2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), 2017

Recent developments in the area of Wireless sensor networks and Mobile ad hoc networks provide fl... more Recent developments in the area of Wireless sensor networks and Mobile ad hoc networks provide flexible and easyto-deploy communication means for a wide range of applications without any need for an infrastructure being pre-configured. Our paper studies performance of proactive and reactive routing protocols in a scenario with agro-sensors. Our results, achieved by simulating a network both in OPNET Modeler and NS2, show that the AODV routing protocol performs better for a large-scale network (where node density is higher) while the DSR routing protocol performs better in a small-scale network given the particular scenario we studied.

Computational Intelligence and Neuroscience

The use of speech as a biomedical signal for diagnosing COVID-19 is investigated using statistica... more The use of speech as a biomedical signal for diagnosing COVID-19 is investigated using statistical analysis of speech spectral features and classification algorithms based on machine learning. It is established that spectral features of speech, obtained by computing the short-time Fourier Transform (STFT), get altered in a statistical sense as a result of physiological changes. These spectral features are then used as input features to machine learning-based classification algorithms to classify them as coming from a COVID-19 positive individual or not. Speech samples from healthy as well as “asymptomatic” COVID-19 positive individuals have been used in this study. It is shown that the RMS error of statistical distribution fitting is higher in the case of speech samples of COVID-19 positive speech samples as compared to the speech samples of healthy individuals. Five state-of-the-art machine learning classification algorithms have also been analyzed, and the performance evaluation m...

Mobile Information Systems

The paper investigates a naturally motivated meaning of wise shrewd self-ruling specialists of hu... more The paper investigates a naturally motivated meaning of wise shrewd self-ruling specialists of humans. Knowledge is identified with whether the conduct of a framework adds to its self-upkeep. Conduct turns out to be clearer (or adapts to more biological issue factors) when it is able to make and utilize portrayals. The thought of portrayal ought not to be confined to formal articulations with neuro hypothetical semantics. The element at different degrees of canny frameworks assumes a fundamental part in shaping portrayals. The paper investigates an organically roused meaning of shrewd self-ruling specialists of humans. Insight is identified with whether the conduct of a framework adds to its self-upkeep. Conduct turns out to be keener when it is proficient to make and utilize portrayals. The idea of portrayal also focused on formal articulations with sentimental hypothetical semantics.

F1000Research, 2021

Problem solving and modelling in traditional substitution methods at large scale for systems usin... more Problem solving and modelling in traditional substitution methods at large scale for systems using sets of simultaneous equations is time consuming. For such large scale global-optimization problem, Simulated Annealing (SA) algorithm and Genetic Algorithm (GA) as meta-heuristics for random search technique perform faster. Therefore, this study applies the SA to solve the problem of linear equations and evaluates its performances against Genetic Algorithms (GAs), a population-based search meta-heuristic, which are widely used in Travelling Salesman problems (TSP), Noise reduction and many more. This paper presents comparison between performances of the SA and GA for solving real time scientific problems. The significance of this paper is to solve the certain real time systems with a set of simultaneous linear equations containing different unknown variable samples those were simulated in Matlab using two algorithms-SA and GA. In all of the experiments, the generated random initial so...

J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 2018

For estimation of signal coverage and localization, path loss is the major component for link bud... more For estimation of signal coverage and localization, path loss is the major component for link budget of any communication system. Instead of traditional Doppler shift or Doppler spread techniques, ...

Internet Voting (i-Voting) is an online electronic voting process where a voter can vote staying ... more Internet Voting (i-Voting) is an online electronic voting process where a voter can vote staying online from anywhere or connected to a wireless network of a target place. In this paper, a wireless ...

Computational Science and Engineering

Voting is an important part for any democratic country. Citizen elects their leader through the v... more Voting is an important part for any democratic country. Citizen elects their leader through the voting process to lead the country. This vote capturing process can be manually or electronically. Manually means traditional ballot paper voting to go in the voting center to cast the vote. Electronically means voting using electronic devices such as computers. We have introduced here such a voting system that is called I-voting. I-voting that stands for Internet Voting therefore it means participate in voting through Internet from home and abroad by the citizen of any country. This paper identifies the challenges for the growth of an I-voting concept and prefaces starting place and describes the requirements behind the challenges presented and finally a proposed solution and implementation techniques of I-voting system.

International Journal of Computer Applications, 2015

Information Systems Security is one of the most critical challenges presently facing nearly every... more Information Systems Security is one of the most critical challenges presently facing nearly every one of the organizations. However, making certain security and quality in both information and the systems which control information is a difficult goal necessitating the mixture of two wide research disciplines which are typically separate: security engineering and secure software engineering. Security engineering has an extensive history, and has focused generally on providing advances in security models, techniques and protocols, but it remains in a steady state of the development. Secure software engineering, however, has emerged relatively recently, but is growing quickly and is paying attention on the integration of security into software engineering techniques; models and processes, in order to build up more secure information systems.The main aim of this paper is to show the requirements analysis using Secure Tropos to Umlsec. Secure tropos is a security oriented extension of tropos methodology and UMLsec is a security oriented extension of standard UML model. To do this we identify different transformation rules and we apply these rules by identifying different steps. We use kent Modeling Transformation Language as a Transformation Language to transform the secure tropos model to UMLsec model and then finally we use a case study to exemplify these rules.

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), Jun 1, 2017

2017 IEEE 42nd Conference on Local Computer Networks Workshops (LCN Workshops), Oct 1, 2017

2018 IEEE 43rd Conference on Local Computer Networks Workshops (LCN Workshops), Oct 1, 2018

Because of the increased popularity and fast expansion of the Internet as well as Internet of thi... more Because of the increased popularity and fast expansion of the Internet as well as Internet of things, networks are growing rapidly in every corner of the society. As a result, huge amount of data is travelling across the computer networks that lead to the vulnerability of data integrity, confidentiality and reliability. So, network security is a burning issue to keep the integrity of systems and data. The traditional security guards such as firewalls with access control lists are not anymore enough to secure systems. To address the drawbacks of traditional Intrusion Detection Systems (IDSs), artificial intelligence and machine learning based models open up new opportunity to classify abnormal traffic as anomaly with a self-learning capability. Many supervised learning models have been adopted to detect anomaly from networks traffic. In quest to select a good learning model in terms of precision, recall, area under receiver operating curve, accuracy, F-score and model built time, this paper illustrates the performance comparison between Naïve Bayes, Multilayer Perceptron, J48, Naïve Bayes Tree, and Random Forest classification models. These models are trained and tested on three subsets of features derived from the original benchmark network intrusion detection dataset, NSL-KDD. The three subsets are derived by applying different attributes evaluator's algorithms. The simulation is carried out by using the WEKA data mining tool.

2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), 2017

Recent developments in the area of Wireless sensor networks and Mobile ad hoc networks provide fl... more Recent developments in the area of Wireless sensor networks and Mobile ad hoc networks provide flexible and easyto-deploy communication means for a wide range of applications without any need for an infrastructure being pre-configured. Our paper studies performance of proactive and reactive routing protocols in a scenario with agro-sensors. Our results, achieved by simulating a network both in OPNET Modeler and NS2, show that the AODV routing protocol performs better for a large-scale network (where node density is higher) while the DSR routing protocol performs better in a small-scale network given the particular scenario we studied.

IET Image Processing

In this study, specifically for the detection of ripe/unripe tomatoes with/without defects in the... more In this study, specifically for the detection of ripe/unripe tomatoes with/without defects in the crop field, two distinct methods are described and compared from captured images by a camera mounted on a mobile robot. One is a machine learning approach, known as 'Cascaded Object Detector' (COD) and the other is a composition of traditional customised methods, individually known as 'Colour Transformation': 'Colour Segmentation' and 'Circular Hough Transformation'. The (Viola-Jones) COD generates 'histogram of oriented gradient' (HOG) features to detect tomatoes. For ripeness checking, the RGB mean is calculated with a set of rules. However, for traditional methods, colour thresholding is applied to detect tomatoes either from natural or solid background and RGB colour is adjusted to identify ripened tomatoes. This algorithm is shown to be optimally feasible for any micro-controller based miniature electronic devices in terms of its run time complexity of O(n 3) for a traditional method in best and average cases. Comparisons show that the accuracy of the machine learning method is 95%, better than that of the Colour Segmentation Method using MATLAB.

International Journal of Computer Applications, 2015

Information Systems Security is one of the most critical challenges presently facing nearly every... more Information Systems Security is one of the most critical challenges presently facing nearly every one of the organizations. However, making certain security and quality in both information and the systems which control information is a difficult goal necessitating the mixture of two wide research disciplines which are typically separate: security engineering and secure software engineering. Security engineering has an extensive history, and has focused generally on providing advances in security models, techniques and protocols, but it remains in a steady state of the development. Secure software engineering, however, has emerged relatively recently, but is growing quickly and is paying attention on the integration of security into software engineering techniques; models and processes, in order to build up more secure information systems.The main aim of this paper is to show the requirements analysis using Secure Tropos to Umlsec. Secure tropos is a security oriented extension of tropos methodology and UMLsec is a security oriented extension of standard UML model. To do this we identify different transformation rules and we apply these rules by identifying different steps. We use kent Modeling Transformation Language as a Transformation Language to transform the secure tropos model to UMLsec model and then finally we use a case study to exemplify these rules.

2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI), 2016

— A Mobile Ad Hoc Network (MANET) is a group of wireless mobile nodes which dynamically form a ne... more — A Mobile Ad Hoc Network (MANET) is a group of wireless mobile nodes which dynamically form a network without any established infrastructure. The application is considered in an agro-based project and therefore, Routing protocols are mandatory to send and receive packets. In this paper, we have evaluated the most commonly used routing protocols in MANET and compared the performance of reactive routing protocols such as Dynamic Source Routing (DSR), Ad-hoc On-demand Distance Vector (AODV) and proactive routing protocols such as Geographic Routing Protocol (GRP), and Destination-Sequenced Distance Vector (DSDV) routing protocol by using OPNET simulator 17.5. The OPNET simulator is optimal for core level network design and parameters of sensor nodes are detailed enough to design a sensor network as the MANET in this paper. Analysis of the performance of protocols are certainly depending on End to End delay (average), Network Load and the throughput. These parameters are the common primary issues behind routing and sensor nodes in the MANET will coordinate themselves following these issues staying in an environment of proactive or reactive routing. The result shows that AODV performs better than the other two.

Computational Intelligence and Neuroscience

In this paper, an autonomous brain tumor segmentation and detection model is developed utilizing ... more In this paper, an autonomous brain tumor segmentation and detection model is developed utilizing a convolutional neural network technique that included a local binary pattern and a multilayered support vector machine. The detection and classification of brain tumors are a key feature in order to aid physicians; an intelligent system must be designed with less manual work and more automated operations in mind. The collected images are then processed using image filtering techniques, followed by image intensity normalization, before proceeding to the patch extraction stage, which results in patch extracted images. During feature extraction, the RGB image is converted to a binary image by grayscale conversion via the colormap process, and this process is then completed by the local binary pattern (LBP). To extract feature information, a convolutional network can be utilized, while to detect objects, a multilayered support vector machine (ML-SVM) can be employed. CNN is a popular deep l...

Wireless Communications and Mobile Computing, Apr 4, 2022

Sensor-based agriculture monitoring systems have limited outcomes on the detection or counting of... more Sensor-based agriculture monitoring systems have limited outcomes on the detection or counting of vegetables from agriculture fields due to the utilization of either conventional color transformations or machine learning-based methods. To overcome these limitations, this research is aimed at proposing an IoT-based smart agriculture monitoring system with multiple algorithms such as detection, quantification, ripeness checking, and detection of infected vegetables. This paper presents smart agriculture monitoring systems for Internet of Things (IoT) applications. The CHT has been applied to detect and quantify vegetables from the agriculture field. Using color thresholding and color segmentation techniques, defected vegetables have also been detected. A machine learning method-convolutional neural network (CNN) has been used for the development and implementation of all algorithms. A comparison between traditional methods and CNN has been simulated in MATLAB to find out the optimal method for its implementation in this agricultural monitoring system. Compared to the traditional methods, the CNN is the optimal method in this research work which performed better over the previously developed algorithms with an accuracy of more than 90%. As an example (case study), a tomato field in Chittagong, Bangladesh, was chosen where a camera-mounted mobile robot captured images from the agriculture field for which the proposed IoT-based smart monitoring system was developed. This system will benefit farmers through the digitally monitored output at an agriculture field in Bangladesh as well as in Malaysia. Since this proposed smart IoT-based system is still driven by bulky, costly, and limited powered sensors, in a future work, for the required power of sensors, this research work is aimed at the design and development of an energy harvester (hybrid) (HEH) based on ultralow power electronics circuits to generate the required power of sensors. Implementation of multiple algorithms using CNN, circular Hough transformation (CHT), color thresholding, and color segmentation methods for the detection, quantification, ripeness checking, and detection of infected crops.

Journal of Mathematics

The burst dropping ratio is witnessed in the contemporary literature as a considerable constraint... more The burst dropping ratio is witnessed in the contemporary literature as a considerable constraint of optical burst switching (OBS) networks that attained many researchers’ efforts in the recent past. Among the multiple practices endeavoring to reduce the burst drop ratio, the optimal burst scheduling is one dimension in this regard. The transmission channel scheduling and appropriate wavelength allocation are critical objectives to achieve optimal burst scheduling in regard to minimal burst drop ratio. Many of the scheduling models depicted in the contemporary literature aimed to achieve the optimum scheduling by electing the channels, which depend on optimum utilization of idle time. Some of the studies tried to select channels by any metrics of quality, and significantly minimal amount of studies focused on wavelength allocation for lowering BDR. Moreover, in regard to this, this study tried to achieve optimum wavelength allocation beneath manifold objective QoS metrics, which is ...

Wireless Communications and Mobile Computing, Apr 29, 2022

The technology grows quickly in the area of the VLSI physical design; it is crucial to integrate ... more The technology grows quickly in the area of the VLSI physical design; it is crucial to integrate the greater number of transistors and parts into a very small range. Before the placement is completed, the physical and technical positioning of the blocks in the chip area is planned, which is nothing but floor planning. In order to lessen the placement region in the physical layout, floor planning must be carried out effectively. This paper proposes a blended harmony search and particle swarm optimization (BHSPS) algorithm which is the deliberate blend of the harmony search (HS) algorithm, and the particle swarm optimization (PSO) algorithm is proposed to acquire the central goal of the VLSI placement strategy. The objective here is to lessen the field of plan. The MATLAB code for the blended harmony search and particle swarm optimization (BHSPS) algorithm is compiled, and investigations were carried out for better examination through the standard MCNC, i.e., North Carolina Microelectronics Center benchmark circuits.

2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), 2017

Recent developments in the area of Wireless sensor networks and Mobile ad hoc networks provide fl... more Recent developments in the area of Wireless sensor networks and Mobile ad hoc networks provide flexible and easyto-deploy communication means for a wide range of applications without any need for an infrastructure being pre-configured. Our paper studies performance of proactive and reactive routing protocols in a scenario with agro-sensors. Our results, achieved by simulating a network both in OPNET Modeler and NS2, show that the AODV routing protocol performs better for a large-scale network (where node density is higher) while the DSR routing protocol performs better in a small-scale network given the particular scenario we studied.

Computational Intelligence and Neuroscience

The use of speech as a biomedical signal for diagnosing COVID-19 is investigated using statistica... more The use of speech as a biomedical signal for diagnosing COVID-19 is investigated using statistical analysis of speech spectral features and classification algorithms based on machine learning. It is established that spectral features of speech, obtained by computing the short-time Fourier Transform (STFT), get altered in a statistical sense as a result of physiological changes. These spectral features are then used as input features to machine learning-based classification algorithms to classify them as coming from a COVID-19 positive individual or not. Speech samples from healthy as well as “asymptomatic” COVID-19 positive individuals have been used in this study. It is shown that the RMS error of statistical distribution fitting is higher in the case of speech samples of COVID-19 positive speech samples as compared to the speech samples of healthy individuals. Five state-of-the-art machine learning classification algorithms have also been analyzed, and the performance evaluation m...

Mobile Information Systems

The paper investigates a naturally motivated meaning of wise shrewd self-ruling specialists of hu... more The paper investigates a naturally motivated meaning of wise shrewd self-ruling specialists of humans. Knowledge is identified with whether the conduct of a framework adds to its self-upkeep. Conduct turns out to be clearer (or adapts to more biological issue factors) when it is able to make and utilize portrayals. The thought of portrayal ought not to be confined to formal articulations with neuro hypothetical semantics. The element at different degrees of canny frameworks assumes a fundamental part in shaping portrayals. The paper investigates an organically roused meaning of shrewd self-ruling specialists of humans. Insight is identified with whether the conduct of a framework adds to its self-upkeep. Conduct turns out to be keener when it is proficient to make and utilize portrayals. The idea of portrayal also focused on formal articulations with sentimental hypothetical semantics.

F1000Research, 2021

Problem solving and modelling in traditional substitution methods at large scale for systems usin... more Problem solving and modelling in traditional substitution methods at large scale for systems using sets of simultaneous equations is time consuming. For such large scale global-optimization problem, Simulated Annealing (SA) algorithm and Genetic Algorithm (GA) as meta-heuristics for random search technique perform faster. Therefore, this study applies the SA to solve the problem of linear equations and evaluates its performances against Genetic Algorithms (GAs), a population-based search meta-heuristic, which are widely used in Travelling Salesman problems (TSP), Noise reduction and many more. This paper presents comparison between performances of the SA and GA for solving real time scientific problems. The significance of this paper is to solve the certain real time systems with a set of simultaneous linear equations containing different unknown variable samples those were simulated in Matlab using two algorithms-SA and GA. In all of the experiments, the generated random initial so...

J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 2018

For estimation of signal coverage and localization, path loss is the major component for link bud... more For estimation of signal coverage and localization, path loss is the major component for link budget of any communication system. Instead of traditional Doppler shift or Doppler spread techniques, ...

Internet Voting (i-Voting) is an online electronic voting process where a voter can vote staying ... more Internet Voting (i-Voting) is an online electronic voting process where a voter can vote staying online from anywhere or connected to a wireless network of a target place. In this paper, a wireless ...

Computational Science and Engineering

Voting is an important part for any democratic country. Citizen elects their leader through the v... more Voting is an important part for any democratic country. Citizen elects their leader through the voting process to lead the country. This vote capturing process can be manually or electronically. Manually means traditional ballot paper voting to go in the voting center to cast the vote. Electronically means voting using electronic devices such as computers. We have introduced here such a voting system that is called I-voting. I-voting that stands for Internet Voting therefore it means participate in voting through Internet from home and abroad by the citizen of any country. This paper identifies the challenges for the growth of an I-voting concept and prefaces starting place and describes the requirements behind the challenges presented and finally a proposed solution and implementation techniques of I-voting system.

International Journal of Computer Applications, 2015

Information Systems Security is one of the most critical challenges presently facing nearly every... more Information Systems Security is one of the most critical challenges presently facing nearly every one of the organizations. However, making certain security and quality in both information and the systems which control information is a difficult goal necessitating the mixture of two wide research disciplines which are typically separate: security engineering and secure software engineering. Security engineering has an extensive history, and has focused generally on providing advances in security models, techniques and protocols, but it remains in a steady state of the development. Secure software engineering, however, has emerged relatively recently, but is growing quickly and is paying attention on the integration of security into software engineering techniques; models and processes, in order to build up more secure information systems.The main aim of this paper is to show the requirements analysis using Secure Tropos to Umlsec. Secure tropos is a security oriented extension of tropos methodology and UMLsec is a security oriented extension of standard UML model. To do this we identify different transformation rules and we apply these rules by identifying different steps. We use kent Modeling Transformation Language as a Transformation Language to transform the secure tropos model to UMLsec model and then finally we use a case study to exemplify these rules.

2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), Jun 1, 2017

2017 IEEE 42nd Conference on Local Computer Networks Workshops (LCN Workshops), Oct 1, 2017

2018 IEEE 43rd Conference on Local Computer Networks Workshops (LCN Workshops), Oct 1, 2018

Because of the increased popularity and fast expansion of the Internet as well as Internet of thi... more Because of the increased popularity and fast expansion of the Internet as well as Internet of things, networks are growing rapidly in every corner of the society. As a result, huge amount of data is travelling across the computer networks that lead to the vulnerability of data integrity, confidentiality and reliability. So, network security is a burning issue to keep the integrity of systems and data. The traditional security guards such as firewalls with access control lists are not anymore enough to secure systems. To address the drawbacks of traditional Intrusion Detection Systems (IDSs), artificial intelligence and machine learning based models open up new opportunity to classify abnormal traffic as anomaly with a self-learning capability. Many supervised learning models have been adopted to detect anomaly from networks traffic. In quest to select a good learning model in terms of precision, recall, area under receiver operating curve, accuracy, F-score and model built time, this paper illustrates the performance comparison between Naïve Bayes, Multilayer Perceptron, J48, Naïve Bayes Tree, and Random Forest classification models. These models are trained and tested on three subsets of features derived from the original benchmark network intrusion detection dataset, NSL-KDD. The three subsets are derived by applying different attributes evaluator's algorithms. The simulation is carried out by using the WEKA data mining tool.

2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), 2017

Recent developments in the area of Wireless sensor networks and Mobile ad hoc networks provide fl... more Recent developments in the area of Wireless sensor networks and Mobile ad hoc networks provide flexible and easyto-deploy communication means for a wide range of applications without any need for an infrastructure being pre-configured. Our paper studies performance of proactive and reactive routing protocols in a scenario with agro-sensors. Our results, achieved by simulating a network both in OPNET Modeler and NS2, show that the AODV routing protocol performs better for a large-scale network (where node density is higher) while the DSR routing protocol performs better in a small-scale network given the particular scenario we studied.

IET Image Processing

In this study, specifically for the detection of ripe/unripe tomatoes with/without defects in the... more In this study, specifically for the detection of ripe/unripe tomatoes with/without defects in the crop field, two distinct methods are described and compared from captured images by a camera mounted on a mobile robot. One is a machine learning approach, known as 'Cascaded Object Detector' (COD) and the other is a composition of traditional customised methods, individually known as 'Colour Transformation': 'Colour Segmentation' and 'Circular Hough Transformation'. The (Viola-Jones) COD generates 'histogram of oriented gradient' (HOG) features to detect tomatoes. For ripeness checking, the RGB mean is calculated with a set of rules. However, for traditional methods, colour thresholding is applied to detect tomatoes either from natural or solid background and RGB colour is adjusted to identify ripened tomatoes. This algorithm is shown to be optimally feasible for any micro-controller based miniature electronic devices in terms of its run time complexity of O(n 3) for a traditional method in best and average cases. Comparisons show that the accuracy of the machine learning method is 95%, better than that of the Colour Segmentation Method using MATLAB.

International Journal of Computer Applications, 2015

Information Systems Security is one of the most critical challenges presently facing nearly every... more Information Systems Security is one of the most critical challenges presently facing nearly every one of the organizations. However, making certain security and quality in both information and the systems which control information is a difficult goal necessitating the mixture of two wide research disciplines which are typically separate: security engineering and secure software engineering. Security engineering has an extensive history, and has focused generally on providing advances in security models, techniques and protocols, but it remains in a steady state of the development. Secure software engineering, however, has emerged relatively recently, but is growing quickly and is paying attention on the integration of security into software engineering techniques; models and processes, in order to build up more secure information systems.The main aim of this paper is to show the requirements analysis using Secure Tropos to Umlsec. Secure tropos is a security oriented extension of tropos methodology and UMLsec is a security oriented extension of standard UML model. To do this we identify different transformation rules and we apply these rules by identifying different steps. We use kent Modeling Transformation Language as a Transformation Language to transform the secure tropos model to UMLsec model and then finally we use a case study to exemplify these rules.

2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI), 2016

— A Mobile Ad Hoc Network (MANET) is a group of wireless mobile nodes which dynamically form a ne... more — A Mobile Ad Hoc Network (MANET) is a group of wireless mobile nodes which dynamically form a network without any established infrastructure. The application is considered in an agro-based project and therefore, Routing protocols are mandatory to send and receive packets. In this paper, we have evaluated the most commonly used routing protocols in MANET and compared the performance of reactive routing protocols such as Dynamic Source Routing (DSR), Ad-hoc On-demand Distance Vector (AODV) and proactive routing protocols such as Geographic Routing Protocol (GRP), and Destination-Sequenced Distance Vector (DSDV) routing protocol by using OPNET simulator 17.5. The OPNET simulator is optimal for core level network design and parameters of sensor nodes are detailed enough to design a sensor network as the MANET in this paper. Analysis of the performance of protocols are certainly depending on End to End delay (average), Network Load and the throughput. These parameters are the common primary issues behind routing and sensor nodes in the MANET will coordinate themselves following these issues staying in an environment of proactive or reactive routing. The result shows that AODV performs better than the other two.