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Towards a lightweight security framework using blockchain and machine learning

Blockchain(Research and Applications) 2024年第1期5卷 107-118页

作者： Shereen Ismail Muhammad Nouman Diana W.Dawoud hassan reza School of Electrical Engineering and Computer Science University of North DakotaND 58202USA Department of Computer Science COMSATS University IslamabadIslamabad 44000Pakistan College of Engineering and Information Technology University of DubaiDubaiUnited Arab Emirates

Cyber-attacks pose a significant challenge to the security of Internet of Things(IoT)sensor networks,necessitating the development of robust countermeasures tailored to their unique characteristics and *** prevention and detection techniques have been proposed to mitigate these *** this paper,we propose an integrated security framework using blockchain and Machine Learning(ML)to protect IoT sensor *** framework consists of two modules:a blockchain prevention module and an ML detection *** blockchain prevention module has two lightweight mechanisms:identity management and trust *** management employs a lightweight Smart Contract(SC)to manage node registration and authentication,ensuring that unauthorized entities are prohibited from engaging in any tasks,while trust management uses a lightweight SC that is responsible for maintaining trust and credibility between sensor nodes throughout the network’s lifetime and tracking historical node *** and transaction validation are achieved through a Verifiable Byzantine Fault Tolerance(VBFT)mechanism to ensure network reliability and *** ML detection module utilizes the Light Gradient Boosting Machine(LightGBM)algorithm to classify malicious nodes and notify the blockchain network if it must make decisions to mitigate their *** investigate the performance of several off-the-shelf ML algorithms,including Logistic Regression,Complement Naive Bayes,Nearest Centroid,and Stacking,using the WSN-DS *** is selected following a detailed comparative analysis conducted using accuracy,precision,recall,F1-score,processing time,training time,prediction time,computational complexity,and Matthews Correlation Coefficient(MCC)evaluation metrics.

关键词： Blockchain Machine learning IoT Security Integration Smart contracts

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A Systematic Review Towards Big Data Analytics in Social Media

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Big Data Mining and Analytics 2022年第3期5卷 228-244页

作者： Md.Saifur Rahman hassan reza School of Electrical Engineering and Computer Science University of North DakotaGrand ForksND 58202USA

The recent advancement in internet 2.0 creates a scope to connect people worldwide using society 2.0 and web 2.0 *** new era allows the consumer to directly connect with other individuals,business corporations,and the *** are open to sharing opinions,views,and ideas on any topic in different formats out *** creates the opportunity to make the"Big Social Data"handy by implementing machine learning approaches and social data *** study offers an overview of recent works in social media,data science,and machine learning to gain a wide perspective on social media big data *** explain why social media data are significant elements of the improved data-driven decision-making *** propose and build the"Sunflower Model of Big Data"to define big data and bring it up to date with technology by combining 5 V’s and 10 *** discover the top ten social data analytics to work in the domain of social media platforms.A comprehensive list of relevant statistical/machine learning methods to implement each of these big data analytics is discussed in this work."Text Analytics"is the most used analytics in social data analysis to *** create a taxonomy on social media analytics to meet the need and provide a clear ***,techniques,and supporting data type are also discussed in this research *** a result,researchers will have an easier time deciding which social data analytics would best suit their needs.

关键词： big data social media big data analytics social media analytics text analytics image analytics audio analytics video analytics predictive analytics descriptive analytics prescriptive analytics diagnostic analytics

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Numerical Prediction of Induced Pressure and Lift of the Planing Surfaces

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China Ocean Engineering 2009年第2期23卷 221-232页

作者： hassan GHASSEMI Ahmad reza KOHANSAL Mahmoud GHIASSI Department of Marine Technology Amirkabir Urdversity of Technology 15875-4413 Tehran Iran

This paper discusses the numerical prediction of the induced pressure and lift of the planing surfaces in a steady motion based on the potential flow solver as well as the spray drag by use of the practical method. The numerical method for computation of the induced pressure and lift is potential-based boundary element method. Special technique is identified to present upwash geometry and to determine the spray drag. Numerical results of a planing flat plate and planing craft model 4666 are presented. It is shown that the method is robust and efficient and the results agree well with the experimental measurements with various Froude numbers.

关键词： planing surface pressure distribution induced pressure drag and lift spray

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Nondestructive methods for determining the firmness of apple fruit flesh

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Information Processing in Agriculture 2021年第4期8卷 515-527页

作者： Zahed Fathizadeh Mohammad Aboonajmi Seyed reza hassan-Beygi Department of Agrotechnology College of AbouraihanUniversity of TehranTehranIran

Nowadays,many researches have been accomplished on the attributed quality assessment of agricultural *** have significantly contributed to these researches because of their high production and consumption,*** this paper,the nondestructive instrumental researches in the field of firmness assessment for apple fruit *** researches are important for all production and distribution chain activists such as farmers,insurance companies,packaging and transportation companies,wholesalers and *** studies can be used for examining texture quality,predicting the right time to harvest fruits and classifying them according to the level of ripeness and detecting the apparent and internal defects of the *** apple flesh firmness measurement methods consist of acoustic and mechanical vibration methods,optical methods such as hyperspectral scattering imaging,near infrared,ultrasound and other *** destructive puncture test method commonly used as a reference *** methods are accurate and quick that is suitable for online ***,the use of artificial intelligence methods and data fusion techniques to increase the accuracy of quality measuring of the products has been considered that in the future we will see further development of these methods in measuring the firmness of the apples.

关键词： Apple Firmness Internal quality Nondestructive

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Enhancing Mobile Cloud Computing Security Using Steganography

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Journal of Information Security 2016年第4期7卷 245-259页

作者： hassan reza Madhuri Sonawane School of Aerospace Sciences Department of Computer Science University of North Dakota Grand Forks ND USA

Cloud computing is an emerging and popular method of accessing shared and dynamically configurable resources via the computer network on demand. Cloud computing is excessively used by mobile applications to offload data over the network to the cloud. There are some security and privacy concerns using both mobile devices to offload data to the facilities provided by the cloud providers. One of the critical threats facing cloud users is the unauthorized access by the insiders (cloud administrators) or the justification of location where the cloud providers operating. Although, there exist variety of security mechanisms to prevent unauthorized access by unauthorized user by the cloud administration, but there is no security provision to prevent unauthorized access by the cloud administrators to the client data on the cloud computing. In this paper, we demonstrate how steganography, which is a secrecy method to hide information, can be used to enhance the security and privacy of data (images) maintained on the cloud by mobile applications. Our proposed model works with a key, which is embedded in the image along with the data, to provide an additional layer of security, namely, confidentiality of data. The practicality of the proposed method is represented via a simple case study.

关键词： Cloud Computing Mobile Computing Software Security Software Privacy Data Hiding Steganography Encryption

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Applied Machine Learning Methods for Detecting Fractured Zones by Using Petrophysical Logs

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Intelligent Control and Automation 2021年第2期12卷 44-64页

作者： Haleh Azizi hassan reza School of Electrical Engineering and Computer Sciences University of North Dakota Grand Forks ND USA

In the last decade, a few valuable types of research have been conducted to discriminate fractured zones from non-fractured ones. In this paper, petrophysical and image logs of eight wells were utilized to detect fractured zones. Decision tree, random forest, support vector machine, and deep learning were four classifiers applied over petrophysical logs and image logs for both training and testing. The output of classifiers was fused by ordered weighted averaging data fusion to achieve more reliable, accurate, and general results. Accuracy of close to 99% has been achieved. This study reports a significant improvement compared to the existing work that has an accuracy of close to 80%.

关键词： Decision Tree Deep Learning Ordered Weighted Averaging Random For-est Support Vector Machine

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Toward the Design and Implementation of Traceability Engineering Tool Support

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Journal of Software Engineering and Applications 2019年第6期12卷 249-265页

作者： Subik Pokharel hassan reza Department of Computer Science University of North Dakota Grand Forks North Dakota USA

Requirements of a system keep on changing based on the need of stakeholders or the system developers, making requirement engineering an important aspect in software development. This develops a need for appropriate requirement change management. The importance of requirements traceability is defining relationships between the requirements and artefacts extracted by the stakeholder during the software development life-cycle and gives vital information to encourage software understanding. In this paper, we have concentrated on developing a tool for requirement traceability that can be used to extend the requirement elicitation and identification of system-wide qualities using the notion of quality attribute scenarios to capture the non-functional requirements. It allows us to link the functional and non-functional requirements of the system based on the quality attribute scenarios template proposed by the Carnegie Mellon Software Engineering Institute (SEI). Apart from this, the paper focuses on tracing the functional and non-functional requirements of the system using the concept of requirement traceability matrix.

关键词： Requirement Engineering Requirement Engineering Tool Tool Support Quality Attributes Requirement Traceability Software Engineering

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Toward Quality Attribute Driven Approach to Software Architectural Design

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Journal of Software Engineering and Applications 2017年第6期10卷 483-499页

作者： Payel Bajpayee hassan reza Department of Computer Science University of North Dakota Grand Forks USA

It has been well-documented that the software architecture of any system plays a critical role in success or failure of software intensive systems. In this paper, a method has been proposed to evaluate the software architecture’s fitness with respect to key quality attributes for a web-based system. To the end, a comparative analysis based on quality attributes scenarios and tactics is carried out to select an optimal software architecture that meets the system level requirements of a web-based system, namely, Student and Course Evaluation System (SCES). The comparative study was driven by study of quality attributes and tactics with the selected architectures to select the optimal one.

关键词： Architectural Tactics Quality Attributes Software Architecture Architectural Styles

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Mapping AADL to Petri Net Tool-Sets Using PNML Framework

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Journal of Software Engineering and Applications 2014年第11期7卷 920-933页

作者： hassan reza Amrita Chatterjee Department of Computer Science School of Aerospace Sciences University of North Dakota Grand Forks USA

Architecture Analysis and Design Language (AADL) has been utilized to specify and verify nonfunctional properties of Real-Time Embedded Systems (RTES) used in critical application systems. Examples of such critical application systems include medical devices, nuclear power plants, aerospace, financial, etc. Using AADL, an engineer is enable to analyze the quality of a system. For example, a developer can perform performance analysis such as end-to-end flow analysis to guarantee that system components have the required resources to meet the timing requirements relevant to their communications. The critical issue related to developing and deploying safety critical systems is how to validate the expected level of quality (e.g., safety, performance, security) and functionalities (capabilities) at design level. Currently, the core AADL is extensively applied to analyze and verify quality of RTES embed in the safety critical applications. The notation lacks the formal semantics needed to reason about the logical properties (e.g., deadlock, livelock, etc.) and capabilities of safety critical systems. The objective of this research is to augment AADL with exiting formal semantics and supporting tools in a manner that these properties can be automatically verified. Toward this goal, we exploit Petri Net Markup Language (PNML), which is a standard acting as the intermediate language between different classes of Petri Nets. Using PNML, we interface AADL with different classes of Petri nets, which support different types of tools and reasoning. The justification for using PNML is that the framework provides a context in which interoperability and exchangeability among different models of a system specified by different types of Petri nets is possible. The contributions of our work include a set of mappings and mapping rules between AADL and PNML. To show the feasibility of our approach, a fragment of RT-Embedded system, namely, Cruise Control System has been used.

关键词： Model-Based Engineering Petri Nets AADL PNML Software Architecture Formal Methods

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A Survey on Software Cost Estimation Techniques

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Journal of Software Engineering and Applications 2019年第6期12卷 226-248页

作者： Sai Mohan Reddy Chirra hassan reza School of Electrical Engineering & Computer Science University of North Dakota Grand Forks USA

The ability to accurately estimate the cost needed to complete a specific project has been a challenge over the past decades. For a successful software project, accurate prediction of the cost, time and effort is a very much essential task. This paper presents a systematic review of different models used for software cost estimation which includes algorithmic methods, non-algorithmic methods and learning-oriented methods. The models considered in this review include both the traditional and the recent approaches for software cost estimation. The main objective of this paper is to provide an overview of software cost estimation models and summarize their strengths, weakness, accuracy, amount of data needed, and validation techniques used. Our findings show, in general, neural network based models outperforms other cost estimation techniques. However, no one technique fits every problem and we recommend practitioners to search for the model that best fit their needs.

关键词： Software Cost Estimation Classical SCE Models Algorithmic Models Non-Algorithmic Models Learning-Oriented Cost Estimation Techniques

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