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25 articles for “network traffic”
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Application of Game Theory Principles for Opportunistic Routing in MANETS
Abstract: This article explores the application of game theory principles to enhance opportunistic routing in mobile ad hoc networks (MANETs). MANETs are characterized by their dynamic topology, limited resources, and lack of infrastructure, making traditional routing protocols less efficient. Opportunistic routing leverages the mobility of nodes and the broadcast nature of wireless communication to achieve reliable message delivery. However, existing opportunistic routing algorithms may suffer from challenges such as high message …
Published in International Journal of Mobile Computing Technology · Vol. 2, Issue 1, 2024 · pp. 1–8 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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Adaptive Traffic Control Systems: Enhancing Urban Mobility through Real-Time Traffic Management
Abstract: Traffic congestion is a ubiquitous challenge in urban areas, necessitating innovative solutions to improve transportation efficiency and alleviate gridlock. Traditional traffic signal control methods often prove inadequate in dynamically adapting to fluctuating traffic conditions, leading to increased travel times, fuel consumption, and emissions. In response, adaptive traffic control systems have emerged as a promising approach to mitigate congestion and enhance traffic flow in urban environments. These devices dynamically modify signal …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 37–45 Read article
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Enhancing LAN Security Using Machine Learning
Abstract: The modern Local Area Network (LAN) is a critical component of any organization's infrastructure, facilitating communication, resource sharing, and access to the wider internet. However, this connectivity also brings inherent security risks. Traditional security measures, relying on signature-based detection and rule-based systems, are increasingly struggling to keep pace with the evolving sophistication of cyberattacks. This is where Machine Learning (ML) offers a powerful alternative, enabling proactive threat detection and enhanced …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 07–16 Read article
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ML Associated DoS and DDoS Attack Observation in Protection
Abstract: DoS and DDoS assaults are significant risks to the availability and integrity of online services and networks. Attack traffic might come from a variety of geographical regions, making it difficult to filter and neutralize the attack. DDoS attacks are far more sophisticated and powerful than DoS attacks. They use a network of compromised devices, known as a botnet, to launch a coordinated attack on a target. Monitoring and evaluating the …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 1, 2024 · pp. 18–26 Read article
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Revolutionizing Motorcycle Safety: A Deep Learning Approach for Helmet and Triple Riding Detection using Computer Vision Technology and Machine Learning Model
Abstract: Introducing a revolutionary paradigm in road safety, our project unveils the Intelligent Traffic Surveillance System (ITSS), a groundbreaking initiative poised to transform urban traffic management. In an era where road safety is paramount, ITSS emerges as a beacon of innovation, harnessing the prowess of computer vision and machine learning to tackle two of the most pressing concerns plaguing our roads: helmet non-compliance and triple riding among motorcyclists. At its core, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 28–36 Read article
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Real-Time Object Detection and Tracking in Traffic Surveillance: Implementing Algorithms That Can Process Video Streams for Immediate Traffic Monitoring
Abstract: The rapid growth in urban development and traffic congestion calls for adopting high standards of traffic surveillance systems for monitoring. This paper reviews the current advancement and future trends of real-time object detection and tracking technology and its implications for traffic surveillance. Conventional approaches to traffic monitoring can provide more or less accurate data, but they are not easily scalable and cannot cope with rapidly changing conditions typical within urban …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 18–39 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Resource Reservation Approach: Application in Wireless Network
Abstract: This paper presents an enhanced resource reservation and call admission control strategy tailored for cellular networks. The proposed method uses user mobility trends to improve the efficiency of resource usage while avoiding significant network congestion. The call admission control mechanism is activated each time a new or handoff service request occurs, ensuring that resources are allocated efficiently to uphold a steady quality of service (QoS) for multimedia traffic. This mechanism …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 1, 2025 · pp. 9–12 Read article
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Dynamic Skip-Layer Trees: A Novel Data Structure for Efficient Multi-level IoT Data Processing in Smart Cities
Abstract: This paper introduces dynamic skip-layer trees (DSLTs), a novel hierarchical data structure specifically designed for processing and managing multi-layered Internet of Things (IoT) sensor data in smart city environments. DSLTs extend the traditional skip list concept by incorporating dynamic layer adjustment and spatial awareness, enabling efficient querying and updates across various geographical and temporal dimensions. Our experimental results demonstrate that DSLTs achieve up to 40% faster query processing and a …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 11–21 Read article
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Radio Frequency Next-Generation Advances
Abstract: Radio frequency (RF) technology is a key enabler for modern wireless communications, driving the evolution of telecommunications, healthcare, aerospace, defence and the Internet of Things (IoT). Faster, more reliable and energy-efficient communication systems have been developed at a rapid pace due to recent discoveries in RF engineering. This article discusses novel advancements in RF technologies including enhanced antenna design, millimeter-wave communication, software defined radio, smart spectrum management, and RF-based sensor …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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V2V Communication Using LiFi
Abstract: The global status report on road safety launched by the World Health Organization (WHO) highlights that the number of annual road traffic deaths has reached 1.35 million. In the USA over 37,000 people die in road crashes each year and an additional 2.35 are injured or disabled. The direct impact of road accidents is loss of life as well as damage to vehicles and property. Accidents might happen due to …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 1, 2024 · pp. 17–24 Read article
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AI-Based Intelligent Traffic Signal Management System: A Review
Abstract: Traffic congestion is a growing problem in urban areas worldwide, leading to economic losses, increased pollution, and commuter frustration. Traditional traffic management systems rely on fixed timing cycles and lack adaptability to real-time traffic conditions. Intelligent traffic light control systems based on artificial intelligence (AI) have become a viable substitute for traditional techniques. These systems are able to evaluate large volumes of traffic data in real time, identify patterns, and …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article
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Multi-Layered AI-Driven Security in Wireless Ecosystems
Abstract: The proliferation of next-generation wireless technologies, from 5G/6G networks to the pervasive Internet of Things (IoT), has birthed a hyperconnected digital ecosystem of unprecedented scale and dynamism. This interconnectedness, however, introduces a vast and volatile attack surface, rendering conventional, signature-based security paradigms fundamentally obsolete. This paper posits that the only viable defense is an offensive, self-adaptive one, predicated on the integration of artificial intelligence (AI) directly into the wireless security …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 21–28 Read article
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A study in Leveraging Deep Learning and IoT Arrays for Dynamic, Hyper-Local Atmospheric Intelligence
Abstract: The critical demand for high-resolution, actionable atmospheric data is challenged by the high cost and sparse coverage of traditional regulatory monitoring stations. This paper explores the synergistic paradigm shift enabled by integrating low-cost, dense Internet of Things (IoT) sensor arrays with advanced Artificial Intelligence (AI) methodologies, specifically Deep Learning (DL) models. We address the primary limitations of low-cost sensors—inherent bias, sensitivity to environmental drift (temperature/humidity), and calibration inconsistency—by utilizing AI …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 50–62 Read article
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Zoology in Forensic Science: Unraveling Mysteries through Animal Clues
Abstract: Traditionally, forensic wisdom has been grounded on mortal substantiation similar as fingerprints, DNA, and bloodstains to unravel the riddle of crimes. There's important untapped eventuality in the beast area that could unravel mystifications and bring culprits to justice. This composition explores the instigative area of crossroad of zoology and forensic wisdom by demonstrating how suggestions from creatures can be significantly contributed to felonious examinations. From beast poisons in analysis to …
Published in International Journal of Toxins and Toxics · Vol. 2, Issue 1, 2025 · pp. 37–49 Read article
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WSN with IoT Using Raspberry Pi as a Tool for Communication
Abstract: Wireless systems based on IoT have developed exponentially in various aspects. The Internet of Things (IoT) is a network in which physical devices, sensors, and other objects communicate among themselves without the involvement of humans. The WSN (Wireless sensor network) is a central component of IoT that has escalated into various applications in the real world. Many industries are turning towards industrial automation as it provides increased efficiency, reduced costs, …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 1, Issue 1, 2023 · pp. 34–42 Read article
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Advanced Helmet Recognition System with Integrated Number Plate Detection for Enhanced Traffic Monitoring Using Deep Learning
Abstract: This study focuses on the crucial problem of non-adherence to traffic regulations, particularly with the compulsory use of helmets by motorcyclists. Motorcycle accidents have a greater mortality rate compared to other types of accidents, indicating a need for a more effective enforcement strategy. Current procedures depend on traditional techniques where traffic officers manually observe traffic rule infractions through patrols and monitoring CCTVs, requiring substantial labor and time resources. The inherent …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 9–18 Read article