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8th International Congress on Information and Communication Technology, ICICT 2023

作者： Dakić, Pavle Todorović, Vladimir Vranić, Valentino Faculty of Informatics and Computing Singidunum University Belgrade Serbia Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Bratislava Slovakia Faculty of Business Studies and Law MB University Belgrade Serbia

ISBN: (纸本)9789819930906

Achieving a high level of quality in the AV industry involves understanding the complexity of the production cycle with the constant challenges of applying appropriate standards. The need for compliance based on relevant certificates implies the creation of an environment of trust between manufacturers, component suppliers, and end customers. Research should sublimate the most current standards from various fields related to data protection, security, system sustainability, environmental management, financial sustainability, and business transparency. The success of a complex parts supply system is impossible without a stable approach to IT security. The control of production processes sometimes involves using non-standardized techniques, and one of the applicable ones is work-in-progress (WIP), which describes the use of partially finished raw materials in the stages of obtaining final products. Key points and the contribution of the current study are in getting a better overview of the situation within this area related to standards and the financial problems that can arise due to a lack of understanding of standards compliance. The main limitations within the study itself refer to the consideration of the theoretical foundations that should be used during future research related to the practical part during implementation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Automotive industry

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E-mail Spam Classification Using Grasshopper Optimization Algorithm and Neural Networks

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Computers, Materials & Continua 2022年第6期71卷 4749-4766页

作者： Sanaa A.A.Ghaleb Mumtazimah Mohamad Syed Abdullah Fadzli Waheed A.H.M.Ghanem Faculty of Informatics and Computing Universiti Sultan Zainal AbidinKuala Terengganu22200Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia TerengganuKuala Terengganu21030Malaysia Faculty of Engineering University of AdenAdenYemen Faculty of Education(Aden-Saber) University of AdenAdenYemen

Spam has turned into a big predicament these days,due to the increase in the number of spam emails,as the recipient regularly receives piles of *** only is spam wasting users’time and *** addition,it limits the storage space of the email box as well as the disk ***,spam detection is a challenge for individuals and organizations *** advance spam email detection,this work proposes a new spam detection approach,using the grasshopper optimization algorithm(GOA)in training a multilayer perceptron(MLP)classifier for categorizing emails as ham and ***,MLP and GOA produce an artificial neural network(ANN)model,referred to(GOAMLP).Two corpora are applied Spam Base and UK-2011Web spam for this ***,the finding represents evidence that the proposed spam detection approach has achieved a better level in spam detection than the status of the art.

关键词： Grasshopper optimization algorithm multilayer perceptron artificial neural network spam detection approach

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A Scalable and Lightweight Authentication Architecture for the Internet of Things (IoT) in Smart Home Applications 2

A Scalable and Lightweight Authentication Architecture for t...

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2nd Zimbabwe Conference on Information Communication and Technology, ZCICT 2023

作者： Gamundani, Attlee M. Phillips, Amelia Muyingi, Hippolyte N. Namibia University of Science and Technology Faculty of Computing & Informatics Cyber Security Department Windhoek Namibia University of the Cumberlands School of Computer and Information Sciences WilliamsburgKY United States Namibia University of Science and Technology Faculty of Computing & Informatics Windhoek Namibia

ISBN: (纸本)9798350318128

In the evolving landscape of smart home applications, ensuring robust and efficient authentication within the Internet of Things (IoT) environments is paramount. This paper presents a scalable, lightweight authentication architecture for IoT-driven smart homes. The proposed architecture, drawing inspiration from cloud computing mechanisms, introduces a trusted, smart home agent, integrating the Data-Information-Knowledge-Wisdom (DIKW) model to facilitate efficient and secure data exchange within smart homes. Our solution addresses the challenges of minimal computation and processing overheads, essential in resource-constrained IoT devices, and focuses on device-level authentication to reduce computational costs. A comparative analysis with existing models demonstrates the superiority of our architecture in terms of computational efficiency, making it an ideal candidate for scalable deployments. The architecture successfully navigates the complexities of ensuring secure communication among autonomous IoT devices, balancing the dual needs of computational efficiency and robust security, thereby promising resilience against common security threats in the smart home ecosystem. © 2023 IEEE.

关键词： Authentication

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Comparison of Dark Channel Prior and Contrast Limited Histogram Equalization for the Enhancement of Underwater Fish Image 4

Comparison of Dark Channel Prior and Contrast Limited Histog...

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4th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2022

作者： Ahmad Hijazi, Mohd Hanafi Mei, Leong Jing Universiti Malaysia Sabah Faculty of Computing and Informatics Sabah Malaysia

ISBN: (数字)9781665468374

ISBN: (纸本)9781665468374

The application of artificial intelligence (AI) in aquaculture may improve the efficiency of fish farming management. Computer vision is one of the fields in AI beneficial for aquaculture. However, the underwater image quality is usually low due to light scattering through the water. Therefore, image enhancement is necessary before any further processing can be done. There are numerous image enhancement techniques for underwater images reported in the literature. In this paper, the comparison of the two most common image enhancement techniques for underwater images, the Dark Channel Prior (DCP) and Histogram Equalization (HE), is presented. The strength and weaknesses of each technique pertaining to the underwater images are also described. © 2022 IEEE.

关键词： Image enhancement

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Treat Assessment Framework in Analysing Network Threat Occurrence 8

Treat Assessment Framework in Analysing Network Threat Occur...

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8th IEEE International Conference on Recent Advances and Innovations in Engineering, ICRAIE 2023

作者： Awang, Norkhushaini Samy, Ganthan A-L Narayana Hassan, Noor Hafizah Binti Universiti Teknologi MARA College of Computing Informatics and Mathematics Selangor Malaysia Universiti Teknologi Malaysia Razak Faculty of Technology and Informatics Kuala Lumpur Malaysia

ISBN: (纸本)9798350315516

Threat assessment of network security assists in identifying potential risks and vulnerabilities. By understanding the threats, their potential impact, and the probability of their occurrence, organizations can proactively implement the necessary security controls and countermeasures to mitigate the risks. Using a mixed method methodology, this research implemented the semi-structured interview and experimental data collection to assess network threats, emphasizing the significance of a tailored framework for university networks. Semi-structured interviews were conducted with network security administrators, risk management experts, and network security experts. The process of experimental data collection involves gathering data from the university firewall during a specific time period in order to identify occurrences of potential threats. In addition, the developed threat assessment utilized machine learning methods to determine the occurrence of threats using a time series analysis algorithm. The findings contribute to developing a comprehensive threat assessment framework that supports decision-making processes for university network security. © 2023 IEEE.

关键词： Network security

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Super-Resolution Based on Curvelet Transform and Sparse Representation

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Computer Systems Science & Engineering 2023年第4期45卷 167-181页

作者： Israa Ismail Mohamed Meselhy Eltoukhy Ghada Eltaweel Department of Computer Science Faculty of Computers and InformaticsSuez Canal UniversityIsmailia51422Egypt Department of Information Technology University of JeddahCollege of Computing and Information Technology at KhulaisJeddahSaudi Arabia

Super-resolution techniques are used to reconstruct an image with a high resolution from one or more low-resolution image(s).In this paper,we proposed a single image super-resolution *** uses the nonlocal mean filter as a prior step to produce a denoised *** proposed algorithm is based on curvelet *** converts the denoised image into low and high frequencies(sub-bands).Then we applied a multi-dimensional interpolation called Lancozos interpolation over both *** parallel,we applied sparse representation with over complete dictionary for the denoised *** proposed algorithm then combines the dictionary learning in the sparse representation and the interpolated sub-bands using inverse curvelet transform to have an image with a higher *** experimental results of the proposed super-resolution algorithm show superior performance and obviously better-recovering images with enhanced *** comparison study shows that the proposed super-resolution algorithm outperforms the *** mean absolute error is 0.021±0.008 and the structural similarity index measure is 0.89±0.08.

关键词： Super-resolution Curvelet transform non-local means filter lancozos interpolation sparse representation

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An Evolutionary Algorithm-Based Optimization Ensemble Learning Model for Predicting Academic Performance 2022

An Evolutionary Algorithm-Based Optimization Ensemble Learni...

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11th International Conference on Software and Computer Applications, ICSCA 2022

作者： Teoh, Chin-Wei Ho, Sin-Ban Dollmat, Khairi Shazwan Chai, Ian Faculty of Computing and Informatics Multimedia University Cyberjaya63100 Malaysia

ISBN: (纸本)9781450385770

The significant growth of the Massive Open Online Course (MOCC) over last decade has promoted the rise of the educational data mining era in online education domain. This situation has created an opportunity for an educator to utilize the available data from MOOCs to facilitate student learning and performance. Therefore, this research study aims to introduce three types of ensemble learning methods, which are stacking, boosting, and bagging, to predict student performance on the online learning data that contain 480 students with 17 features. These techniques have to include the evolutionary algorithm to select the optimal number of input parameter to build the ensemble learning model. As a result, the proposed stacking type ensemble classifier has shown the highest prediction accuracy of approximately 88% and Area Under the Curve (AUC) of approximately 0.85. Results by stacking ensemble classifier have outperformed other ensemble classifiers, bagging and boosting as well as base classifiers. © 2022 ACM.

关键词： educational data mining classification Ensemble learning genetic algorithm

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Implementation of a Mixed Triple Logistic Map and the BB84 Quantum Key Distribution for Secure Image Communication

Implementation of a Mixed Triple Logistic Map and the BB84 Q...

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2024 International of Seminar on Application for Technology of Information and Communication, iSemantic 2024

作者： Morissa, Virnika Shefira Gina Setiadi, De Rosal Ignatius Moses Universitas Dian Nuswantoro Informatics Engineering Department Semarang50131 Indonesia Universitas Dian Nuswantoro Research Center for Quantum Computing and Materials Informatics Faculty of Computer Science Semarang50131 Indonesia

ISBN: (纸本)9798350366648

In the digital era, data communication security is one of the main challenges. This research proposes a new method for secure image communication, which is a mixed triple logistic map and BB84 quantum key distribution. This approach combines the strengths of classical and quantum cryptographic systems to improve security. BB84 quantum key distribution protocol for securely distributing encryption keys. The resulting key is then processed into a hash value using the SHA-256 algorithm. These hash values are converted into ASCII values, which are used to generate three key sequences using the modified logistic map. The three key sequences are combined to form a keystream used in image encryption. Several security metrics are used to evaluate encryption security, including entropy, the Chi-Square test, and pixel correlation. The analysis results show that the encrypted image has an entropy close to eight. In addition, all chi-square values smaller than 293 indicate a uniform distribution. The correlation of nearby pixels in the encrypted image is also very low, where all values are less than 0.01, which indicates the loss of local patterns in the encrypted image. These results demonstrate that the proposed method effectively secures image communications, providing high security and resistance to conventional and quantum cryptographic attacks. © 2024 IEEE.

关键词： Quantum cryptography

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A Preliminary Lightweight Random Forest Approach-Based Image Classification for Plant Disease Detection

A Preliminary Lightweight Random Forest Approach-Based Image...

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2022 IEEE International Conference on computing, ICOCO 2022

作者： Ibrahim, Mashitah Hamzah, Muzaffar Asli, Mohammad Fadhli Universiti Malaysia Sabah Faculty of Computing and Informatics Sabah Malaysia

ISBN: (纸本)9781665489966

In recent years, the rapid development of environmental sensors and artificial intelligence is changing the traditional mode of agricultural production and moving towards intelligent and efficient precision agriculture. According to the demand of developing precision agriculture, this study plans to carry out comprehensive improvise research on the intelligent unmanned plant disease detection technology for agricultural ecosystems. The production can be adversely affected if plant disease problems cannot be detected in the early stage. Therefore, the biggest challenge in disease detection is the accurate early diagnosis for loss prevention. However, achieving high accuracy requires a computationally intensive approach to the system, which can cause overhead and high technical costs. Random Forest is a special kind of ensemble learning technique and it turns out to perform very well compared to other classification algorithms such as Support Vector Machines (SVM) and Artificial Neural Networks (ANN). In this study, we modified the structure of, RF model to improve the overall accuracy and accessibility, to transform it into a lightweight detection system. This lightweight framework is for cost-effective distribution with high performance without requiring extensive computational resources or complex algorithms. With that, this system can be more practical and easier to use. © 2022 IEEE.

关键词： Image classification

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Energy And Congestion Awareness Traffic Scheduling In Hybrid Software-Defined Network

Energy And Congestion Awareness Traffic Scheduling In Hybrid...

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2022 IEEE International Conference on computing, ICOCO 2022

作者： Lim, C.S. Tan, S.C. Baderulhisham, N.Q. Multimedia University Faculty of Computing and Informatics Cyberjaya63100 Malaysia

ISBN: (纸本)9781665489966

The term 'Hybrid Software-Defined Network' (HSDN) refers to a network that includes both traditional networking devices and Software Defined Networking (SDN) devices. The segregation of the control and data planes in SDN tools that enables centralized control of SDN traffic. Traffic scheduling in H-SDN can be handled through the centralized controller to alleviate traffic congestion. Traffic scheduling that includes flow splitting provides flexibility for traffic flow in order to reduce overload on the network. The network's energy efficiency is critical for cost and energy savings. As a result, the energy consumption of a traffic flow should be considered during traffic scheduling. As a result, the goals of this paper are twofold: First, identify the research challenges in hybrid SDN energy and congestion traffic scheduling. Second, we will discuss future research directions for energy and congested-aware traffic scheduling in Hybrid SDN. © 2022 IEEE.

关键词： Software defined networking

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