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Modified Aquila Optimizer Feature Selection Approach and Support Vector Machine Classifier for Intrusion Detection System

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Multimedia Tools and Applications 2024年第21期83卷 59887-59913页

作者： Abualigah, Laith Ahmed, Saba Hussein Almomani, Mohammad H. Zitar, Raed Abu Alsoud, Anas Ratib Abuhaija, Belal Hanandeh, Essam Said Jia, Heming Elminaam, Diaa Salama Abd Elaziz, Mohamed Abd Computer Science Department Al Al-Bayt University Mafraq25113 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia Department of Mathematics Facility of Science The Hashemite University P.O box 330127 Zarqa13133 Jordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi Abu Dhabi United Arab Emirates Department of Computer Science Wenzhou-Kean University Wenzhou China Department of Computer Information System Zarqa University P.O. Box 13132 Zarqa Jordan School of Information Engineering Sanming University Sanming365004 China Information Systems Department Faculty of Computers and Artificial Intelligence Benha University Benha12311 Egypt Computer Science Department Faculty of Computer Science Misr International University Cairo12585 Egypt Faculty of Computer Science & Engineering Galala University Suze435611 Egypt Ajman University Ajman346 United Arab Emirates Department of Mathematics Faculty of Science Zagazig University Zagazig44519 Egypt

With the ever-expanding ubiquity of the Internet, wireless networks have permeated every facet of modern life, escalating concerns surrounding network security for users. Consequently, the demand for a robust Intrusion Detection System (IDS) has surged. The IDS serves as a critical bastion within the security framework, a significance further magnified in wireless networks where intrusions may stem from the deluge of sensor data. This influx of data, however, inevitably taxes the efficiency and computational speed of IDS. To address these limitations, numerous strategies for enhancing IDS performance have been posited by researchers. This paper introduces a novel feature selection method grounded in Support Vector Machine (SVM) and harnessing the innovative modified Aquila Optimizer (mAO) for Intrusion Detection Systems in Wireless Sensor Networks. To evaluate the efficacy of our approach, we employed the KDD'99 dataset for testing and benchmarking against established methods. Multiple performance metrics, including accuracy, detection rate, false alarm rate, feature count, and execution time, were utilized for assessment. Our comparative analysis reveals the superiority of the proposed method, with standout results in terms of feature reduction, detection accuracy, and false alarm mitigation, yielding significant improvements of 11%, 98.76%, and 0.02%, respectively. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2023.

关键词： Network security

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The Quest for : Embedded Visualization for Augmenting Basketball Game Viewing Experiences

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IEEE Transactions on Visualization and computer Graphics 2023年第1期29卷 962-971页

作者： Lin, Tica Chen, Zhutian Yang, Yalong Chiappalupi, Daniele Beyer, Johanna Pfister, Hanspeter John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States Department of Computer Science Virginia Tech BlacksburgVA United States Department of Computer Science ETH Zürich Switzerland Harvard University United States

Sports game data is becoming increasingly complex, often consisting of multivariate data such as player performance stats, historical team records, and athletes' positional tracking information. While numerous visual analytics systems have been developed for sports analysts to derive insights, few tools target fans to improve their understanding and engagement of sports data during live games. By presenting extra data in the actual game views, embedded visualization has the potential to enhance fans' game-viewing experience. However, little is known about how to design such kinds of visualizations embedded into live games. In this work, we present a user-centered design study of developing interactive embedded visualizations for basketball fans to improve their live game-watching experiences. We first conducted a formative study to characterize basketball fans' in-game analysis behaviors and tasks. Based on our findings, we propose a design framework to inform the design of embedded visualizations based on specific data-seeking contexts. Following the design framework, we present five novel embedded visualization designs targeting five representative contexts identified by the fans, including shooting, offense, defense, player evaluation, and team comparison. We then developed Omnioculars, an interactive basketball game-viewing prototype that features the proposed embedded visualizations for fans' in-game data analysis. We evaluated Omnioculars in a simulated basketball game with basketball fans. The study results suggest that our design supports personalized in-game data analysis and enhances game understanding and engagement. © 2022 IEEE.

关键词： Data visualization

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Structured Illumination Digital Holographic Microscopy via two integrated Mach-Zehnder interferometers

Structured Illumination Digital Holographic Microscopy via t...

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3D Image Acquisition and Display: Technology, Perception and Applications, 3D 2024 - Part of Optica Imaging Congress

作者： Obando-Vásquez, Sofía Restrepo, René Trujillo, Carlos Doblas, Ana Applied optics group School of Applied Science and Engineering Universidad EAFIT Medellín Colombia Department of Electrical and Computer Engineering University of Massachusetts DartmouthMA United States

We propose two Match-Zehnder interferometers coupled to create a structured illumination digital holographic microscope with tunable modulation frequency capability, expanding the system's numerical aperture regar... 详细信息

关键词： Mach-Zehnder interferometers

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A Novel Hybrid Architecture for Superior IoT Threat Detection through Real IoT Environments

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computers, Materials & Continua 2024年第11期81卷 2299-2316页

作者： Bassam Mohammad Elzaghmouri Yosef Hasan Fayez Jbara Said Elaiwat Nisreen Innab Ahmed Abdelgader Fadol Osman Mohammed Awad Mohammed Ataelfadiel Farah H.Zawaideh Mouiad Fadeil Alawneh Asef Al-Khateeb Marwan Abu-Zanona Department of Computer Science Faculty of Computer Science and Information TechnologyJerash UniversityJerash26150Jordan Computer Engineering Department College of Engineering&Information Technology Buraydah CollegesBuraydah51418Saudi Arabia Faculty of Architecture and Design Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityDiriyahRiyadh13713Saudi Arabia Applied College King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Business Intelligence and Data Analysis Faculty of Financial Sciences and BusinessIrbid National UniversityIrbid21110Jordan Faculty of Information Technology Ajloun National UniversityAjlun26810Jordan Department of Management Information Systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia

As the Internet of Things(IoT)continues to expand,incorporating a vast array of devices into a digital ecosystem also increases the risk of cyber threats,necessitating robust defense *** paper presents an innovative hybrid deep learning architecture that excels at detecting IoT threats in real-world *** proposed model combines Convolutional Neural Networks(CNN),Bidirectional Long Short-Term Memory(BLSTM),Gated Recurrent Units(GRU),and Attention mechanisms into a cohesive *** integrated structure aims to enhance the detection and classification of complex cyber threats while accommodating the operational constraints of diverse IoT *** evaluated our model using the RT-IoT2022 dataset,which includes various devices,standard operations,and simulated *** research’s significance lies in the comprehensive evaluation metrics,including Cohen Kappa and Matthews Correlation Coefficient(MCC),which underscore the model’s reliability and predictive *** model surpassed traditional machine learning algorithms and the state-of-the-art,achieving over 99.6%precision,recall,F1-score,False Positive Rate(FPR),Detection Time,and accuracy,effectively identifying specific threats such as Message Queuing Telemetry Transport(MQTT)Publish,Denial of Service Synchronize network packet crafting tool(DOS SYN Hping),and Network Mapper Operating System Detection(NMAP OS DETECTION).The experimental analysis reveals a significant improvement over existing detection systems,significantly enhancing IoT security *** our experimental analysis,we have demonstrated a remarkable enhancement in comparison to existing detection systems,which significantly strength-ens the security standards of *** model effectively addresses the need for advanced,dependable,and adaptable security solutions,serving as a symbol of the power of deep learning in strengthening IoT ecosystems amidst the constantly evolving cyber threat *** achievemen

关键词： A hybrid deep learning model IoT threat detection real IoT environments cybersecurity attention mechanism

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Ultra-Low Power Designs and Strategies for Next-Generation Sensor Networks 7

Ultra-Low Power Designs and Strategies for Next-Generation S...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Gupta, Priyanka Revathi, V. Hameed, Ali Abduhussien Gupta, Manish Yadav, Suman Avdhesh Rao, Bolleddu Devananda Institute of Aeronautical Engineering Department of Computer Science and Engineering Telangana Hyderabad India New Horizon College of Engineering Department of Applied Sciences Bangalore India The Islamic University College of Medical Technology Radiology Techniques Department Najaf Iraq Lovely Professional University Phagwara India Iilm University Department of Computer Science & Engineering Uttar Pradesh Greater Noida India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798350350067

Energy-efficient design and operation are essential for next-generation sensor networks to persist and require less maintenance. This paper describes a novel energy-efficient sensor network. It uses superior data routing and aggregation. Three novel algorithms-EARA, DFAA, and Adaptive Data Sampling-make this strategy practicable. EARA sends data with little energy, DFAA collects all data to eliminate duplicates, and ADSA adjusts sample rates based on relevance and variability. Each piece of software sends, manages, and changes sample rates with minimal energy. This innovative energy-saving strategy is tested against static-duty cycling, non-adaptive data aggregation, fixed-rate data sampling, high-energy data transmission, centralized data routing, and unoptimized sensor node location. The recommended solution outperforms network lifetime, energy usage, data accuracy, latency, scalability, and dependability. Energy savings, ease of use, affordability, adaptability, long-lastingness, and network lifespan are usually better with the proposed response. Scatter plots illustrate how much better the proposed method saves energy and works properly. The EARA, DFAA, and ADSA algorithm-based techniques offer great potential for energy-efficient sensor networks. This strategy stabilizes and prolongs sensor network configurations by optimizing data pathways, aggregating data, and adaptively sampling data. The results show that it works, making it a novel strategy for the future generation of sensor networks that demand higher performance and less energy. © 2024 IEEE.

关键词： Adaptive Data Sampling Data Aggregation Data Management Energy Consumption Energy Efficiency Energy-Aware Routing Network Lifetime Performance Evaluation Sensor Networks Sustainability

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Performance Impact of Wind Speed on MAC Protocols for Underwater Wireless Sensor Networks 16

Performance Impact of Wind Speed on MAC Protocols for Underw...

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16th International Conference on Ambient Systems, Networks and Technologies Networks, ANT 2025 / 8th International Conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Shayokh, Md Al Kampen, Anne-Lena Frøysa, Kjell Eivind Kristensen, Lars Michael Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Bergen Norway

Acoustic communication in underwater environments is challenging due to high propagation delay and severely limited bandwidth. Furthermore, the quality of the channel is dynamically changing due to wind, rain, temperature and other environmental factors. Efficient medium access control (MAC) protocols are therefore particularly important for acoustic sensor networks (UWSNs) to prevent a significant portion of the scarce bandwidth to be wasted on packet collision. Increased wind speed add surface roughness for underwater communication, which in turn can affect the overall performance of MAC protocols in UWSNs. The contribution of this paper is to investigate the performance of five MAC protocols for UWSNs in terms of packet delivery rate, energy consumption and delay under different wind speeds. The protocols investigated are: Aloha, Aloha with carrier sense (Aloha-CS), Carrier Sense Multiple Access (CSMA), T-Lohi, and Distance Aware Collision Avoidance Protocol (DACAP). Our simulation studies show that at low wind speeds of 10 m/s, CSMA performs better than other protocols in terms of Packet Delivery Ratio (PDR) while Aloha without acknowledgement has the lowest End-to-End (E2E) delay with a trade-off in packet delivery ratio (PDR). At higher wind speed of 20 m/s to 30 m/s, T-Lohi outperforms the other protocols both in terms of PDR, E2E delay, and energy consumption. © 2025 Elsevier B.V.. All rights reserved.

关键词： Carrier sense multiple access

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Flutter Based Mobile Application for Electric Vehicle Charging Reservation 8

Flutter Based Mobile Application for Electric Vehicle Chargi...

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8th IEEE International Conference for Convergence in Technology, I2CT 2023

作者： Hari Krishna, S.M. Geethanjali, R. Naik, Dhanya Maruti Hemashree, N. Bhabya, Bhabya M S Ramaiah University of Applied Sciences Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350334012

The growing number of Electric Vehicles (EV) in the transportation sector has brought with it challenges associated with charging of the vehicle at the charging stations, like clustering of vehicles at a particular station, leading to longer waiting hours due to low number of charging outlets available. This has led to loss in time and energy of the EV owners and a frustrating experience in locating a nearby charging station. The paper entrails a solution to tackle these issues, by proposing a mobile application to pre book or reserve a charging port ahead of time at any available charging station for charging the EV, thus ensuring effective service to the users, reducing the clustering of vehicles at the charging stations and thereby less waiting time. The proposed system provides the user with details such as the location of a charging station, number and type of chargers present at a charging station and availability of slots during a specific period. It also allows users to book an available slot with a secured payment gateway and maintains user feedback. © 2023 IEEE.

关键词： Mobile computing

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MINIMUM-RANK POSITIVE SEMIDEFINITE MATRIX COMPLETION WITH CHORDAL PATTERNS AND APPLICATIONS TO SEMIDEFINITE RELAXATIONS

Applied Set-Valued Analysis and Optimization

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applied Set-Valued Analysis and Optimization 2023年第2期5卷 265-283页

作者： Jiang, Xin Sun, Yifan Andersen, Martin S. Vandenberghe, Lieven Department of Industrial and Systems Engineering Lehigh University BethlehemPA18015-1582 United States Department of Computer Science Stony Brook University Stony BrookNY11794-2424 United States Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Denmark Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA90095 United States

We present an algorithm for computing the minimum-rank positive semidefinite completion of a sparse matrix with a chordal sparsity pattern. This problem is tractable, in contrast to the minimumrank positive semidefinite completion problem for general sparsity patterns. We also present a similar algorithm for the Euclidean distance matrix completion with minimum embedding dimension. The two algorithms use efficient recursions over a clique tree associated with the chordal sparsity pattern. As an application, we use the minimum-rank completion method as a rounding technique to convert the solution of a sparse semidefinite optimization problem with non-unique solutions to an optimal solution of lower rank. In experiments with semidefinite relaxations of optimal power flow problems, the minimum-rank completion often results in solutions of lower rank than the solutions computed by interior-point solvers. ©2023 applied Set-Valued Analysis and Optimization.

关键词： Electric load flow

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Examining Various Search Algorithms in AI with Appropriate Literature and Their Performances Against a Human Agent in the Snake Game 14

Examining Various Search Algorithms in AI with Appropriate L...

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14th IEEE Global engineering Education Conference, EDUCON 2023

作者： Mim, Sheikh Sharfuddin Islam, Md Nahin Logofatu, Doina Frankfurt University of Applied Sciences Department of Computer Science and Engineering Frankfurt am Main Germany

ISBN: (纸本)9798350399431

Artificial intelligence (AI) is one of computer science's most crucial subfields. AI applications are growing rapidly. Games are the main place where artificial intelligence is actually used. AI is used to create the game's non-player characters, also referred to as NPCs. Although there are a lot of alternative ways to implement AI in a game, the search strategy is by far the most common. A variety of different search algorithms can be used to construct AI in video games. This paper's main objective is to use the snake game as a comparative tool to examine the differences between search algorithms employed by human agents and those used in AI. This paper presents detailed assessments of informed and uninformed search strategies as well as experiments on Hamiltonian search. This paper also addresses a few widely used techniques, like finite state machines, behavior trees, tree search, etc., frequently used while creating AI. We get to the conclusion that some algorithms are better candidates for use as search algorithms based on the results of thorough expla-nations and trials. We found that the Human Agent performs poorly when compared to the Depth-First Search, Breadth-First Search, Hamiltonian Search, and Best-First Search algorithms, while the A ∗ Search algorithm surpasses them all significantly. © 2023 IEEE.

关键词： Artificial intelligence

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Closest Celestial Body Search Using KD Trees

Closest Celestial Body Search Using KD Trees

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Priya Ponnusamy, P. Shabariram, C.P. Umayal, V.R. Susmeta, A. PSG Institute of Technology and Applied Research Neelambur Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350348217

A Binary Search Tree is expanded into a KD Tree to handle the multi-dimensional key searches. A discriminator makes the KD tree different from the BST. This discriminator will take branching decisions at every level based on the key search. It can handle multi-dimensional coordinate object searching. K-d trees enable O(klogn) lookup times for the k nearest points to some point x. This is extremely useful, especially in cases where an O(n) lookup time is intractable already. In this work, a kd tree has been created based on how a celestial body is positioned in relation to the sun. It aims at finding the minimum in a particular dimension, searching for a celestial body and its nearest neighbor. © 2023 IEEE.

关键词： Nearest neighbor search

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