Enhancing the security of Wireless Sensor Networks(WSNs)improves the usability of their ***,finding solutions to various attacks,such as the blackhole attack,is crucial for the success of WSN *** paper proposes an enh...
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Enhancing the security of Wireless Sensor Networks(WSNs)improves the usability of their ***,finding solutions to various attacks,such as the blackhole attack,is crucial for the success of WSN *** paper proposes an enhanced version of the AODV(Ad Hoc On-Demand Distance Vector)protocol capable of detecting blackholes and malfunctioning benign nodes in WSNs,thereby avoiding them when delivering *** proposed version employs a network-based reputation system to select the best and most secure path to a *** achieve this goal,the proposed version utilizes the Watchdogs/Pathrater mechanisms in AODV to gather and broadcast reputations to all network nodes to build the network-based reputation *** minimize the network overhead of the proposed approach,the paper uses reputation aggregator nodes only for forwarding reputation ***,to reduce the overhead of updating reputation tables,the paper proposes three mechanisms,which are the prompt broadcast,the regular broadcast,and the light broadcast *** proposed enhanced version has been designed to perform effectively in dynamic environments such as mobile WSNs where nodes,including blackholes,move continuously,which is considered a challenge for other *** the proposed enhanced protocol,a node evaluates the security of different routes to a destination and can select the most secure routing *** paper provides an algorithm that explains the proposed protocol in detail and demonstrates a case study that shows the operations of calculating and updating reputation values when nodes move across different ***,the paper discusses the proposed approach’s overhead analysis to prove the proposed enhancement’s correctness and applicability.
The phenomenal rise in network traffic across various sectors, driven by advancements in network communication, has led to an explosion of connected devices. While internet-based service providers have enhanced smart ...
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A significant obstacle in the world of information IT, especially in terms of energy efficiency, is the increasing demand for energy from data centers. These massive plants currently consume nearly 1% of the world'...
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Over 20 years after introducing and popularizing agile software development methods, those methods have proven effective in delivering projects that meet agile assumptions. Those assumptions require that projects be s...
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Recent advancements in computer science and engineering have significantly boosted interest in and success rate of speech recognition systems. Sophisticated speech recognition systems are being developed for a variety...
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Sentiment Analysis(SA)is one of the Machine Learning(ML)techniques that has been investigated by several researchers in recent years,especially due to the evolution of novel data collection methods focused on social *...
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Sentiment Analysis(SA)is one of the Machine Learning(ML)techniques that has been investigated by several researchers in recent years,especially due to the evolution of novel data collection methods focused on social *** literature,it has been reported that SA data is created for English language in excess of any other *** is challenging to perform SA for Arabic Twitter data owing to informal nature and rich morphology of Arabic *** earlier study conducted upon SA for Arabic Twitter focused mostly on automatic extraction of the features from the *** word embedding has been employed in literature,since it is less labor-intensive than automatic feature *** ignoring the context of sentiment,most of the word-embedding models follow syntactic data of *** current study presents a new Dragonfly Optimization with Deep Learning Enabled Sentiment Analysis for Arabic Tweets(DFODLSAAT)*** aim of the presented DFODL-SAAT model is to distinguish the sentiments from opinions that are tweeted in Arabic *** first,data cleaning and pre-processing steps are performed to convert the input tweets into a useful *** addition,TF-IDF model is exploited as a feature extractor to generate the feature ***,Attention-based Bidirectional Long Short Term Memory(ABLSTM)technique is applied for identification and classification of *** last,the hyperparameters of ABLSTM model are optimized using DFO *** performance of the proposed DFODL-SAAT model was validated using the benchmark dataset and the outcomes were investigated under different *** experimental outcomes highlight the superiority of DFODL-SAAT model over recent approaches.
Alzheimer’s Disease is a progressive neuro-degenerative disorder and a leading cause of dementia, marked by cognitive decline, memory loss, and behavioral changes. Despite advancements in medical imaging and Artifici...
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The increasing volume of data in digital forensic investigations has outpaced the capabilities of existing forensic systems. Traditional systems such as The Sleuth Kit Hadoop, OCFA, and Hansken, though capable of hand...
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Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and ...
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Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for RaaS attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.
This research explores the efficacy of various machine learning models in detecting network threats, focusing on their performance across known, similar, and new attack datasets. I evaluated models including Random Fo...
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