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CNN-LSTM Model for Mitigation of DDoS Attacks in Software-Defined Networks

CNN-LSTM Model for Mitigation of DDoS Attacks in Software-De...

2024 International Conference on science, Engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Jimoh, Ebunayo Rachael Oladele, Tinuke Omolewa Oladele, Oluwabunmi Titilope Akinlolu, Azeez Olawale Akanbi, Mulikat Bola Olabanke, Olasehinde-Williams University of Ilorin Faculty of Communication and Information Sciences Department of Computer Science Ilorin Nigeria University of Ilorin Faculty of Communication and Information Sciences Department of Information Technology Ilorin Nigeria Fountain University Department of Mathematical and Computer Sciences Osogbo Nigeria Kwara State Polytechnic Computer Science Department Kwara State Ilorin Nigeria University of Ilorin Centre for Open and Distance Learning Department of Computer Science Ilorin Nigeria

ISBN: (纸本)9798350358155

The Internet, as the world's largest computer network, has evolved beyond a mere repository of information to become an indispensable tool driving modern society. Its dynamic nature enables communication, interaction, and access to diverse information sources, shaping how we navigate the digital landscape. However, this ubiquity also makes it vulnerable to Distributed Denial of Service (DDoS) attacks, where malicious actors deliberately disrupt system resources. As network operators transition to Software Defined Networks (SDN) for improved visibility and control, the centralized architecture of SDN becomes susceptible to DDoS attacks, compromising network integrity. In this study, we developed a novel approach for mitigating DDoS attacks by integrating a CNN-LSTM model, achieving promising results with a loss of 0.0131, Accuracy of 0.9952, Precision score of 0.9918, recall score of 0.9961, and F1_score of 0.9939. This fusion of CNN-LSTM models into SDN-based DDoS mitigation systems holds significant potential for enhancing network security and resilience. © 2024 IEEE.

关键词： Convolutional neural networks

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Comprehensive analysis of relativistic embedded class-I exponential compact spheres in f(R,φ)gravity via Karmarkar condition

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Communications in Theoretical Physics 2023年第10期75卷 100-110页

作者： Zoya Asghar Adnan Malik M Farasat Shamir Fatemah Mofarreh National University of Computer and Emerging Sciences Lahore CampusPakistan School of Mathematical Sciences Zhejiang Normal UniversityJinhuaZhejiangChina Department of Mathematics University of Management and TechnologySialkot CampusPakistan Mathematical Science Department Faculty of Science Princess Nourah bint Abdulrahman University Riyadh 11546Saudi Arabia

In this article,we use the prominent Karmarkar condition to investigate some novel features of astronomical objects in the f(R,φ)gravity;R andφrepresent the Ricci curvature and the scalar field,*** is worth noting that we classify the exclusive set of modified field equations using the exponential type model of the f(R,φ)theory of gravity f(R,φ)=φ(R+α(eβR-1)).We show the embedded class-I approach via a static,spherically symmetric spacetime with an anisotropic *** accomplish our objective,we use a particular interpretation of metric potential(grr)that has already been given in the literature and then presume the Karmarkar condition to derive the second metric *** employ distinct compact stars to determine the values of unknown parameters emerging in metric *** ensure the viability and consistency of our exponential model,we execute distinct physical evolutions,*** graphical structure of energy density and pressure evolution,mass function,adiabatic index,stability,equilibrium,and energy *** investigation reveals that the observed anisotropic findings are physically appropriate and have the highest level of precision.

关键词： stellar structures metric potentials f(R,φ)theory of gravity Karmarkar condition

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A Privacy-Preserving Corpus for Occupational Health in Spanish: Evaluation for NER and Classification Tasks 6

A Privacy-Preserving Corpus for Occupational Health in Spani...

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6th Workshop on Clinical Natural Language Processing, ClinicalNLP 2024, held at NAACL 2024

作者： Aracena, Claudio Miranda, Luis Vakili, Thomas Villena, Fabián Quiroga, Tamara Núñez-Torres, Fredy Rocco, Victor Dunstan, Jocelyn Faculty of Physical and Mathematical Sciences University of Chile Chile Department of Computer Science Pontifical Catholic University of Chile Chile Department of Computer and Systems Sciences Stockholm University Sweden Department of Computer Science University of Chile Chile Chile Department of Language Science Pontifical Catholic University of Chile Chile Chile

ISBN: (纸本)9798891761094

Annotated corpora are essential to reliable natural language processing. While they are expensive to create, they are essential for building and evaluating systems. This study introduces a new corpus of 2,869 medical and admission reports collected by an occupational insurance and health provider. The corpus has been carefully annotated for personally identifiable information (PII) and is shared, masking this information. Two annotators adhered to annotation guidelines during the annotation process, and a referee later resolved annotation conflicts in a consolidation process to build a gold standard subcorpus. The inter-annotator agreement values, measured in F1, range between 0.86 and 0.93 depending on the selected subcorpus. The value of the corpus is demonstrated by evaluating its use for NER of PII and a classification task. The evaluations find that fine-tuned models and GPT-3.5 reach F1 of 0.911 and 0.720 in NER of PII, respectively. In the case of the insurance coverage classification task, using the original or de-identified corpus results in similar performance. The annotated data are released in de-identified form. © 2024 Association for Computational Linguistics.

关键词： Natural language processing systems

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Numerical scheme to solve a class of variable–order Hilfer–Prabhakar fractional differential equations with Jacobi wavelets polynomials

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Applied Mathematics(A Journal of Chinese Universities) 2022年第1期37卷 35-51页

作者： B.Bagherzadeh Tavasani A.H.Refahi Sheikhani H.Aminikhah Department of Applied Mathematics Faculty of Mathematical SciencesLahijan BranchIslamic Azad UniversityLahijanIran Department of Applied Mathematics and Computer Science Faculty of Mathematical SciencesUniversity of GuilanRashtIran

In this paper,we introduced a numerical approach for solving the fractional differential equations with a type of variable-order Hilfer-Prabhakar derivative of orderμ(t)andν(t).The proposed method is based on the Jacobi wavelet collocation *** to this method,an operational matrix is *** use this operational matrix of the fractional derivative of variable-order to reduce the solution of the linear fractional equations to the system of algebraic *** considerations are ***,some numerical examples are presented to demonstrate the accuracy of the proposed method.

关键词： Hilfer-Prabhakar derivative Jacobi wavelets operational matrices variable order

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Recognition of Colon Neoplasm using Contrast-Aware Capsule Network 9

Recognition of Colon Neoplasm using Contrast-Aware Capsule N...

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9th IEEE International Conference on Adaptive science and Technology, ICAST 2024

作者： Yeboah, Mavis Serwaa Kwabena Mensah, Patrick Adekoya, Adebayo Felix Abra Ayidzoe, Mighty University of Energy and Natural Resources Department of Computer Science and Informatics Sunyani Ghana Sunyani Technical University Department of Computer Science Sunyani Ghana Catholic University of Ghana Faculty of Computing Engineering and Mathematical Sciences Sunyani Ghana

ISBN: (纸本)9798350385403

Colon neoplasms are the second leading cause of mortality worldwide, and despite advances in endoscopy, even experienced endoscopists miss 22-28% of cases. Intelligent systems can bridge this gap, but current approaches face significant challenges. For instance, Convolutional Neural Networks (CNNs) excel in image recognition but require large datasets, which are often scarce in healthcare. On the other hand, Capsule Networks, suitable for smaller datasets, struggle with complex images. To address these limitations, we propose a novel contrast-aware Capsule Network for colon neoplasm recognition. By incorporating a novel contrast-aware feature transformation algorithm, our proposed model enhances extracted features and focuses on processing relevant features, achieving remarkable recognition accuracies of 96.70%, 93.68%, and 99.99% on PolyGen, ETIS-Larib, and CVC-ClinicDB datasets, respectively. Our approach outperforms state-of-the-art Capsule Network algorithms and offers a promising solution to support endoscopists in accurate colon neoplasm detection, reducing the burden of image analysis and improving patient outcomes. © 2024 IEEE.

关键词： Convolutional neural networks

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A Provably Secure and Efficient Remote Password Authentication Scheme Using Smart Cards

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computers, Materials & Continua 2022年第6期71卷 6125-6145页

作者： Fairuz Shohaimay Eddie Shahril Ismail Department of Mathematical Sciences Faculty of Science and TechnologyUniversiti Kebangsaan MalaysiaUKM Bangi43600SelangorMalaysia Department of Mathematics Faculty of Computer and Mathematical SciencesUniversiti Teknologi MARA PahangRaub CampusRaub27600PahangMalaysia

Communication technology has advanced dramatically amid the 21st century,increasing the security risk in safeguarding sensitive *** remote password authentication(RPA)scheme is the simplest cryptosystem that serves as the first line of defence against unauthorised entity *** the literature contains numerous RPA schemes,to the best of the authors’knowledge,only few schemes based on the integer factorisation problem(IFP)and the discrete logarithm problem(DLP)that provided a provision for session key agreement to ensure proper mutual ***,none of the previous schemes provided formal security proof using the random oracle ***,this study proposed an improved RPA scheme with session key establishment between user and *** design of the proposed RPA scheme is based on the widely established Dolev-Yao adversary ***,as the main contribution,a novel formal security analysis based on formal definitions of IFP and DLP under the random oracle model was *** proposed scheme’s performance was compared to that of other similar competitive schemes in terms of the transmission/computational cost and time *** findings revealed that the proposed scheme required higher memory storage costs in smart ***,the proposed scheme is more efficient regarding the transmission cost of login and response messages and the total time complexity compared to other scheme of similar security ***,the proposed scheme outperformed the other RPA schemes based on IFP and ***,the potential application of converting the RPA scheme to a user identification(UI)scheme is considered for future *** RPA and UI schemes are similar,the proposed approach can be expanded to develop a provably secure and efficientUI scheme based on IFP and DLP.

关键词： Authentication scheme discrete logarithm factorisation password provable security

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Classifying Body Type based on Eating Habits and Physical Condition using Decision Tree Technique 1

Classifying Body Type based on Eating Habits and Physical Co...

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1st International Visualization, Informatics and Technology Conference, IVIT 2022

作者： Bahrin, Ummu Fatihah Jantan, Hamidah Sani Mohd Sofian, Muhammad Adam Syahirah Ismail, Izzatul Aishah Samsudin, Siti Hajar Cawangan Terengganu Faculty of Computer and Mathematical Sciences Department of Computer Science Kuala Terengganu21080 Malaysia

ISBN: (纸本)9781665486484

Nowadays, due to busy schedules, many people are unaware of what they are eating and their physical condition. This scenario will lead to various health issues such as obesity, diabetes, blood pressure, etc. Hence, it has become very essential for people to have a good balanced nutritional healthy diet to deal with those issues. Therefore, it is important to determine what factors may be conducive to healthy eating behaviors among people with different Body Mass Index (BMI). A predictive analysis approach in data mining can be used to identify the food consumption pattern in people's eating habits and how it is related to their body type. This study aims to classify body types based on eating habits and physical conditions using a decision tree induction algorithm. Several phases have been conducted in this study such as data understanding, data preparation, modeling, and evaluation. In the experimental phase, the datasets that are known as full dataset and reduced dataset have been used to identify which dataset will produce high accuracy. As a result, it is shown that a full dataset produces higher accuracy compared to a reduced dataset. Perhaps there is room for improvement in the reduced dataset by applying other attribute selection methods to produce better accuracy of the classifier. This study brings a high significance for effectiveness and efficiency in eating habits and physical condition analysis based on body type, and it can also be explored for other classification methods for future work enhancement. © 2022 IEEE.

关键词： Classification (of information)

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Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network

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computers, Materials & Continua 2024年第3期78卷 3909-3927页

作者： Yilei Wang Xin Sun Guiping Zheng Ahmar Rashid Sami Ullah Hisham Alasmary Muhammad Waqas Zhejiang Electric-Power Corporation Research Institute Zhejiang310014China Faculty of Information Technology Beijing University of TechnologyBeijing100124China Beijing Trusty Cloud Technology Co. Ltd.Beijing100022China Department of Computer Science and Engineering Ghulam Ishaq Khan Institute of Engineering Sciences and EngineeringTopi23640Pakistan Department of Computer Science Shaheed Benazir Bhutto UniversitySheringalUpper Dir18050Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia School of Computing and Mathematical Science Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUK School of Engineering Edith Cowan UniversityPerth6027Australia

The application of Intelligent Internet of Things(IIoT)in constructing distribution station areas strongly supports platform transformation,upgrade,and intelligent *** sensing layer of IIoT comprises the edge convergence layer and the end sensing layer,with the former using intelligent fusion terminals for real-time data collection and ***,the influx of multiple low-voltage in the smart grid raises higher demands for the performance,energy efficiency,and response speed of the substation fusion ***,it brings significant security risks to the entire distribution substation,posing a major challenge to the smart *** response to these challenges,a proposed dynamic and energy-efficient trust measurement scheme for smart grids aims to address these *** scheme begins by establishing a hierarchical trust measurement model,elucidating the trust relationships among smart IoT *** then incorporates multidimensional measurement factors,encompassing static environmental factors,dynamic behaviors,and energy *** comprehensive approach reduces the impact of subjective factors on trust ***,the scheme incorporates a detection process designed for identifying malicious low-voltage end sensing units,ensuring the prompt identification and elimination of any malicious ***,in turn,enhances the security and reliability of the smart grid *** effectiveness of the proposed scheme in pinpointing malicious nodes has been demonstrated through simulation ***,the scheme outperforms established trust metric models in terms of energy efficiency,showcasing its significant contribution to the field.

关键词： IIoT trusted measure energy efficient

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Pager Explosion:Cybersecurity Insights and Afterthoughts

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2359-2362页

作者： Chuan Sheng Wanlun Ma Qing-Long Han Wei Zhou Xiaogang Zhu Sheng Wen Yang Xiang Fei-Yue Wang Swinburne University of Technology Hawthorn VIC 3122Australia IEEE the School of Computer and Mathematical Sciences the University of AdelaideAdelaideSouth Australia 5005Australia the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 the Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

PAGER EXPLOSION:THE *** 2024 Lebanon pager explosions represent one of the most unexpected and devastating technological incidents in recent *** September 17 and 18,2024,thousands of pagers and walkie-talkies exploded simultaneously across Lebanon and parts of Syria,resulting in 42 deaths and more than 3500 *** handheld communication devices,previously regarded as secure and low-profile,were rigged with concealed explosives and remotely triggered by attackers.

关键词： injuries thoughts explosion

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Deep learning on medical image analysis

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CAAI Transactions on Intelligence Technology 2025年第1期10卷 1-35页

作者： Jiaji Wang Shuihua Wang Yudong Zhang School of Computing and Mathematical Sciences University of LeicesterLeicesterUK Department of Biological Sciences Xi'an Jiaotong-Liverpool UniversitySuzhouJiangsuChina Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia School of Computer Science and Engineering Southeast UniversityNanjingJiangsuChina

Medical image analysis plays an irreplaceable role in diagnosing,treating,and monitoring various *** neural networks(CNNs)have become popular as they can extract intricate features and patterns from extensive *** paper covers the structure of CNN and its advances and explores the different types of transfer learning strategies as well as classic pre-trained *** paper also discusses how transfer learning has been applied to different areas within medical image *** comprehensive overview aims to assist researchers,clinicians,and policymakers by providing detailed insights,helping them make informed decisions about future research and policy initiatives to improve medical image analysis and patient outcomes.

关键词： CNN deep learning medical image transfer learning

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