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DaC-GANSAEBF:Divide and Conquer-Generative Adversarial Network-Squeeze and Excitation-Based Framework for Spam Email Identification

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computer Modeling in engineering & sciences 2025年第3期142卷 3181-3212页

作者： Tawfeeq Shawly Ahmed A.Alsheikhy Yahia Said Shaaban M.Shaaban Husam Lahza Aws I.Abu Eid Abdulrahman Alzahrani Department of Electrical Engineering Faculty of Engineering at RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityArar91431Saudi Arabia Center for Scientific Research and Entrepreneurship Northern Border UniversityArar73213Saudi Arabia Department of Information Technology College of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information and Communication Technology College of Computing StudiesArab Open UniversityKuwait BranchKuwait City13033Al-SafatState of Kuwait Department of Information Systems and Technology College of Computer Science and EngineeringUniversity of JeddahJeddah23218Saudi Arabia

Email communication plays a crucial role in both personal and professional contexts;however,it is frequently compromised by the ongoing challenge of spam,which detracts from productivity and introduces considerable security *** spam detection techniques often struggle to keep pace with the evolving tactics employed by spammers,resulting in user dissatisfaction and potential data *** address this issue,we introduce the Divide and Conquer-Generative Adversarial Network Squeeze and Excitation-Based Framework(DaC-GANSAEBF),an innovative deep-learning model designed to identify spam *** framework incorporates cutting-edge technologies,such as Generative Adversarial Networks(GAN),Squeeze and Excitation(SAE)modules,and a newly formulated Light Dual Attention(LDA)mechanism,which effectively utilizes both global and local attention to discern intricate patterns within textual *** approach significantly improves efficiency and accuracy by segmenting scanned email content into smaller,independently evaluated *** model underwent training and validation using four publicly available benchmark datasets,achieving an impressive average accuracy of 98.87%,outperforming leading methods in the *** findings underscore the resilience and scalability of DaC-GANSAEBF,positioning it as a viable solution for contemporary spam detection *** framework can be easily integrated into existing technologies to enhance user security and reduce the risks associated with spam.

关键词： Email spam fraud light dual attention squeeze and excitation divide and conquer-generative adversarial network-squeeze and excitation-based framework security

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Novel intelligent predictive networks for analysis of chaos in stochastic differential SIS epidemic model with vaccination impact

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Mathematics and computers in Simulation 2024年 219卷 251-283页

作者： Anwar, Nabeela Ahmad, Iftikhar Kiani, Adiqa Kausar Shoaib, Muhammad Raja, Muhammad Asif Zahoor Department of Mathematics University of Narowal 51600 Pakistan Department of Mathematics University of Gujrat 50700 Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Yuan Ze University AI Center Taoyuan320 Taiwan Department of Electrical and Computer Engineering COMSATS University Islamabad Attock Campus Attock43600 Pakistan

In this paper, stochastic predictive computing networks are exploited to investigate the dynamics of the SIS with vaccination impact based epidemic model (SISV-EM) represented by nonlinear systems of stochastic differential equations (SDEs) by exploitation of artificial neural networks (ANNs) with the backpropagated Levenberg-Marquardt technique (BLMT) i.e., (ANNs-BLMT) to approximate the solution behavior. The stochastic nonlinear SISV-EM is governed with three classes: susceptible, infectious, and vaccinated populations. The referenced or target datasets for ANNs-BLMT are constructed by employing Euler-Maruyama (EM) scheme for solving stochastic differential systems in case of sufficiently various nonlinear SISV-EM scenarios by varying the percentage of vaccination for newly born, the coefficient of transmission, the natural mortality rates, the infectious rates of recovery, the rate at which vaccinated people lose their immunity, the rate of death caused by disease, the proportion of vaccinated against susceptible and the white noise in the environment. Based on arbitrary training, testing, and validation samples from the referenced dataset, the ANNs-BLMT provides an approximate solution for the stochastic nonlinear SISV-EM, with significant correlations to the referenced results. Exhaustive simulation-based results using error histograms, mean square errors, and regression analyses further demonstrate that the proposed ANNs-BLMT is efficient, consistent, and accurate for solving SISV-EM. © 2023 International Association for Mathematics and computers in Simulation (IMACS)

关键词： Mean square error

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Advanced Persistent Threats (APT): evolution, anatomy, attribution and countermeasures

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Journal of Ambient Intelligence and Humanized Computing 2023年第7期14卷 9355-9381页

作者： Sharma, Amit Gupta, Brij B. Singh, Awadhesh Kumar Saraswat, V.K. Department of Computer Engineering National Institute of Technology Kurukshetra Kurukshetra136119 India International Center for AI and Cyber Security Research and Innovations Department of Computer Science and Information Engineering Asia University Taichung Taiwan NITI Aayog New Delhi110001 India Lebanese American University Beirut Lebanon School of Computing Skyline University College Sharjah United Arab Emirates Department of Computer Engineering National Institute of Technology Kurukshetra Kurukshetra India Birkbeck University of London London United Kingdom

In today’s cyber warfare realm, every stakeholder in cyberspace is becoming more potent by developing advanced cyber weapons. They have equipped with the most advanced malware and maintain a hidden attribution. The precocious cyber weapons, targeted and motivated with some specific intention are called as Advanced Persistent Threats (APT). Developing defense mechanisms and performing attribution analysis of such advanced attacks are extremely difficult due to the intricate design of attack vector and sophisticated malware employed with high stealth and evasive techniques. These attacks also include advanced zero-day and negative-day exploits and payloads. This paper provides a comprehensive survey on the evolution of advanced malware design paradigms, APT attack vector and its anatomy, APT attack Tactics, Techniques, and Procedures (TTP) and specific case studies on open-ended APT attacks. The survey covers a detailed discussion on APT attack phases and comparative study on threat life-cycle specification by various organizations. This work also addresses the APT attack attribution and countermeasures against these attacks from classical signature and heuristic based detection to modern machine learning and genetics based detection mechanisms along with sophisticated zero-day and negative day malware countermeasure by various techniques like monitoring of network traffic and DNS logs, moving target based defense, and attack graph based defenses. Furthermore, the survey addresses various research scopes in the domain of APT cyber-attacks. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Life cycle

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A Zero-Watermark Scheme Based on Quaternion Generalized Fourier Descriptor for Multiple Images

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computers, Materials & Continua 2022年第5期71卷 2633-2652页

作者： Baowei Wang Weishen Wang Peng Zhao Naixue Xiong School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing210044China Engineering Research Center of Digital Forensics Ministry of EducationNanjing210044China Department of Mathematics and Computer Science Northeastern State UniversityTahlequahOK74464USA

Most of the existing zero-watermark schemes for medical images are only appropriate for a single grayscale *** they protect a large number of medical images,repeating operations will cause a significant amount of time and storage ***,this paper proposes an efficient zero-watermark scheme for multiple color medical images based on quaternion generalized Fourier descriptor(QGFD).Firstly,QGFD is utilized to compute the feature invariants of each color image,then the representative features of each image are selected,stacked,and reshaped to generate a feature matrix,which is then binarized to get a binary feature *** information can be converted into the copyright image by using QR code technology,which contains more ***,the zero-watermark image is constructed by executing the XOR operation on the copyright image and the feature image scrambled by the Cat *** the experiment,different parameters are selected to determine the maximum number of images that the proposed scheme can protect simultaneously while achieving good *** experimental results demonstrate that the proposed scheme can effectively resist common attacks,geometric attacks and joint attacks,and effectively improve the operation efficiency of the algorithm,thus effectively decreasing the time and storage cost of copyright protection for lots of medical images.

关键词： Copyright protection color medical image zero-watermark QGFD

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A leap by the rise of solid-state electrolytes for Li-air batteries

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Green Energy & Environment 2023年第4期8卷 939-944页

作者： Kecheng Pan Minghui Li Weicheng Wang Shuochao Xing Yaying Dou Shasha Gao Zhang Zhang Zhen Zhou Interdisciplinary Research Center for Sustainable Energy Science and Engineering(IRC4SE2) School of Chemical EngineeringZhengzhou UniversityZhengzhou450001China Key Laboratory of Microelectronics and Energy of Henan Province Department of Physics and Electronic EngineeringXinyang Normal UniversityXinyang464000China Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education) College of ChemistryNankai UniversityTianjin300071China

Li-air batteries have attracted extensive attention because of their ultrahigh theoretical energy density. However, the potential safety hazard of flammable organic liquid electrolytes hinders their practical applications. Replacing liquid electrolytes with solidstate electrolytes(SSEs) is expected to fundamentally overcome the safety issues. In this work, we focus on the development and challenge of solid-state Li-air batteries(SSLABs). The rise of different types of SSEs, interfacial compatibility and verifiability in SSLABs are presented. The corresponding strategies and prospects of SSLABs are also proposed. In particular, combining machine learning method with experiment and in situ(or operando)techniques is imperative to accelerate the development of SSLABs.

关键词： Solid-state Li-air batteries Solid-state electrolytes Interfacial compatibility and verifiability

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Human Blood Cell (Haematologicalimages) Recognition by Applying Deep Convolution Methods 9

Human Blood Cell (Haematologicalimages) Recognition by Apply...

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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Krishna Kumar, N. Sarada, Ch. Mallika, S. Suguna Subhashini, P. Sai Kumar, K. Zearah, Sajad Ali Gnitc Department of Cse Hyderabad India Cvr College of Engineering Department of Cse Telangana Hyderabad India Mlr Institute of Technology Department of Computer Science And Information Technology Telangana Hyderabad India Malla Reddy University School of Engineering Computer Science Dulapally Maisammaguda Telangana Hyderabad500100 India Al-Ayen University Scientific Research Center Thi-Qar Iraq

ISBN: (纸本)9798350394474

Utilizing Deep Convolution Strategies to Perceive Human Platelets (Hematological Pictures): Deep Learning is rapidly becoming seen as a preferable method for learning over conventional ML models. This is on the grounds that it has previously been demonstrated to have the option to manage continuous issues in numerous application regions. Convolutional neural networks (CNNs), a sort of deep learning calculation, have a few advantages in the field of well-being, where a ton of pictures should be handled and inspected. The objective of the review is to make a deep learning model to take care of the issue of placing platelets into gatherings. It is one of the hardest things to sort out while checking blood out. A CNN-based framework has been made that consequently sorts pictures of platelets into various kinds of cells, like MONOCYTE, LYMPHOCYTE, NEUTROPHIL, and EOSINOPHIL. To further develop CNN innovation, specialists have investigated thoughts like the utilization of numerous initiation and misfortune capabilities, regularization, boundary advancement, and plan development. Be that as it may, changes to CNN's design have made it feasible for it to show much more. A block of layers can likewise be utilized as a structure block. This concentrates first glances at the inward scientific classifications of recently declared deep CNN frameworks. This is done so that new CNN configuration patterns can be placed into classes. The seven regions are channel gain, utilization of room, utilization of element maps, multipath, profundity, width, and consideration. Overall information on CNN's parts, its ongoing issues, and how it tends to be utilized is likewise given. © 2024 IEEE.

关键词： Platelets

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Climate-Based AI-Powered Precision Irrigation: Sustainably Smart Agriculture Frameworks for Maximum Crop Yields

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Remote Sensing in Earth Systems sciences 2024年第1期8卷 161-172页

作者： Dhanke, Jyoti A. Srivastava, Diksha Menaga, D. Raj, Roop Kumar, Kambala Vijaya Jangir, Pradeep Mani, P. Department of Engineering Science (Mathematics) Bharati Vidyapeeth’s College of Engineering Lavale Pune India Department of Biotechnology and Chemical Engineering Manipal University Jaipur Jaipur India Department of Computer Science and Engineering St. Joseph’s Institute of Technology Chennai India Department of Economics HNBG Central University Uttarakhand Srinagar India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation AP Vaddeswaram India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan K.Ramakrishnan College of Technology Trichy India

A digital transformation is necessary for agriculture to achieve sustainability and increase productivity. With the use of IoT, high-tech detectors and helicopters can monitor crop health and environmental factors in real time, transmitting crucial data to cloud-based systems. Due to their robust computational and storage capabilities, these systems are capable of handling large datasets and carrying out intricate data analytics. Even before the COVID-19 pandemic, the world’s food supply was precariously balanced and insufficient. The present agricultural system prioritizes short-term gains above the preservation of the earth and its ecosystems. To construct agricultural systems that can meet the needs of ten billion individuals in the next 30 years, significant structural and automated changes are required. However, with the support of intelligent technology and the progress of artificial intelligence in agriculture, these obstacles might be overcome. Integration of data, processing images, and neural networks are examples of artificial intelligence technologies that have allowed producers to make better choices using up-to-date information and prediction models. The study emphasizes the need to address the ethical and practical concerns associated with climate-based AI in agriculture to promote its equitable deployment. The results of this research contribute to the ongoing debate about artificial intelligence’s possible applications in farming. New agricultural technologies provide optimism for a future that is environmentally friendly and will be able to feed the growing global population. The integration of renewable energy sources is one of the areas where artificial intelligence is seen to be able to assist in reaching global sustainability goals. Artificial intelligence (AI) has the potential to revitalize both newly developed and existing agricultural land by modifying, deploying, and implementing automated systems and tools. We take stock of where AI is at

关键词： Artificial intelligence Climatic conditions Cloud computing Deep learning Energy Sustainable precision irrigation

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Network Intrusion Detection Based on Hybrid Network Model and Federated Learning 7th

Network Intrusion Detection Based on Hybrid Network Model an...

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7th International Conference on Information science, Communication and Computing, ISCC 2023

作者： Kou, Yuqing Cheng, Jieren Yang, Yue Wu, Hao Li, Yajing Sheng, Victor S. Hainan Blockchain Engineering Research Center Hainan China School of Computer Science and Technology Hainan University Haikou570228 China School of Cyberspace Security Hainan University Haikou570228 China Department of Computer Science Texas Tech University LubbockTX79409 United States

ISBN: (纸本)9789819971602

Data is a valuable strategic resource for the development of modern society. However, with the increasingly complex network environment, privacy leaks and malicious attacks emerge in endlessly. For example, blockchain has also begun to become a new outlet for network black production, which poses a huge security threat to cryptocurrency. In this paper, we propose a hybrid network model (Cb Net), which uses Convolutional Neural Networks (CNN) and Bidirectional recurrent neural networks (BiGRU) to fully extract the space-time characteristics of network data traffic. Then, we propose an intrusion detection method (FLD), which introduces federated learning to collect traffic data from different network institutions, analyze network traffic and identify network attacks. We have fully evaluated the performance of the proposed model and method on the public dataset NSL-KDD. Experiments show that the proposed hybrid network model can achieve high detection accuracy, and the FLD method can effectively identify network attacks on the premise of ensuring the privacy of the local data of the users involved, and its performance is better than other methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Complex networks

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Optimizing Quality of Service Parameters for Optical Networks 15

Optimizing Quality of Service Parameters for Optical Network...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Khurana, Jatin Jayasree, S. Gupta, Shivangi Gowrishankar, J. Birare, Komal M. Balaji, N.V. Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research for Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Quantum University Research Center Quantum University India Jain [Deemed to be University School of Engineering and Technology Computer Science Engineering Karnataka Bangalore India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India

ISBN: (纸本)9798350370249

Optical networks are generally designed to offer best of provider (QoS) guarantees to users, which will deliver provider of the appropriate satisfactory. However, because of availability, capacity, and infrastructure constraints, those QoS parameters might not be without problems optimized. This paper explores exclusive strategies for optimizing the QoS parameters in optical networks. It examines numerous techniques inclusive of community slicing and clever manipulate for improving carrier availability, quit-to-end latency, and quit-to-end throughput. It also investigates a couple of routing strategies, together with redundant packet routing, multipath routing, and dynamic routing, to improve hyperlink and node reliabilities, and common hop-matter. Sooner or later, it discusses the potential of the use of disbursed manipulate algorithms for adjusting various QoS parameters in real-time. The paper draws on a spread of simulation situations to demonstrate the effectiveness of these optimization strategies and algorithms. Common, this paper gives an in-depth examination of the various optimization strategies to be had for boosting satisfactory of provider in optical networks. © 2024 IEEE.

关键词： Examination Manipulate Parameters Provider Reliabilities Throughput

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Conversational Product Recommendation using LLM 4

Conversational Product Recommendation using LLM

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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Chang, Ting-Jui Lin, Lydia Hsiao-Mei Tsai, Richard Tzong-Han National Central University Department of Computer Science and Information Engineering Taoyuan Taiwan National Taipei University of Technology Department of Interaction Design Taipei Taiwan Research Center for Humanities and Social Sciences Academia Sinica Taipei Taiwan

ISBN: (纸本)9798350360721

It is expected to deploy chatbots as sales assistants on e-commerce platforms soon. In recent years, the capabilities demonstrated by large language models (LLMs) indicate their suitability for this role. However, a dialogue process is not fully established. Most existing works concentrate on searching for ideal products, such as Retrieval-Augmented Generation (RAG) and product search. Many proposed methods rely on product reviews. However, in the case of some e-commerce platform products, valuable reviews are often lacking, rendering these approaches impractical. Thus, we studied how to assist users and select a set of candidate products. Accordingly, we simulated sales conversations based on the product features provided by the seller, using LLM and reliable content while addressing the cold-start problem. Specifically, we used product features to generate customer persona for user simulation. LLM was used to play the role of sales assistant in giving recommendations. The experimental results showed that practical conversation was created between customers and chatbots in Traditional Chinese. The code and results are available at: https://***/terryobe-ncu/CPR_LLM © 2024 IEEE.

关键词： Sales

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