Search Results - (( features detection packet algorithm ) OR ( java application interface algorithm ))
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1
Non-invasive pathological voice classifications using linear and non-linear classifiers
Published 2010“…In the case of detection of specific disorders, wavelet packet and entropy features perform well compared to time-domain energy variations based features and MFCCs and SVD based features. …”
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2
CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets
Published 2017“…In addition, it is also aimed to improve the resource consumption of the packet-based detection approach. CHID applied attribute wrapper features evaluation algorithms that marked malicious flows for further analysis by the packet-based detection. …”
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3
Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders
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4
Features selection for IDS in encrypted traffic using genetic algorithm
Published 2013“…Feature selection for IDS is a fundamental step in detection procedure and aims to eliminate some irrelevant and unneeded features from the dataset. …”
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5
Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain
Published 2019“…Second, the MFO algorithm was utilised to select the optimal discriminative features. …”
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Features selection for ids in encrypted traffic using genetic algorithm
Published 2013“…This paper presents a hybrid feature selection using Genetic Algorithm and Bayesian Network to improve Brute Force attack detection in Secure Shell (SSH) traffic. …”
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7
A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features
Published 2022“…The difficulty and impracticality of decrypting TLS network traffic before it reaches the Intrusion Detection System (IDS) has driven numerous research studies to focus on anomaly-based malware detection without decryption employing various features and Machine Learning (ML) algorithms. …”
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8
Secure address resolution protocol proxy in software defined network
Published 2018“…Therefore, the proposed approach contains collecting information algorithm, ARP storm attack detection algorithm, and ARP spoofing attack detection algorithm. …”
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9
A novel selection of optimal statistical features in the DWPT domain for discrimination of ictal and seizure-free electroencephalography signals
Published 2018“…In this present study, a novel feature selection scheme based on the discrete wavelet packet decomposition and cuckoo search algorithm (CSA) was proposed. …”
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10
Effective dimensionality reduction of payload-based anomaly detection in TMAD model for HTTP payload
Published 2016“…The PCA algorithm transforms high-dimensional feature vectors into a low-dimensional feature space, which is used to determine the optimum volume of factors. …”
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11
A novel selection of optimal statistical features in the DWPT domain for discrimination of ictal and seizure‑free electroencephalography signals
Published 2017“…Properly determining the discriminative fea-tures which characterize the inherent behaviors of electro-encephalography (EEG) signals remains a great challenge for epileptic seizure detection. In this present study, a novel feature selection scheme based on the discrete wavelet packet decomposition and cuckoo search algorithm (CSA) was proposed. …”
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12
Malware Classification and Detection using Variations of Machine Learning Algorithm Models
Published 2025“…The results of the study concluded that the best algorithm for detecting malware packages is the Neural Network for the Feature Combination category with an accuracy rate of 96.91%, Recall of 97.35% and Precision of 96.78%. …”
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13
A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS
Published 2019“…The Correlationbased Feature Selection Evaluator (CfsSubset) algorithm is applied in feature selection process in order to improve the classification process. …”
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14
Real‑time chatter detection during turning operation using wavelet scattering network
Published 2024“…Several attempts have been made to detect chatter. Some manual feature extraction methods used to detect the chatter involve wavelet packet transform (WPT), ensemble empirical mode decomposition (EEMD), local mean decomposition (LMD), and variational mode decomposition (VMD). …”
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15
Network tool for preventing DDOS attacks on cloud computing
Published 2015“…The algorithm is implemented in a simulated network environment and results obtained is analyze based on packet delivery ratio.…”
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Final Year Project Report / IMRAD -
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A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features
Published 2022“…Due to the complexity of TLS traffic decryption, several anomaly-based detection studies have been conducted to detect TLS-based malware using different features and machine learning (ML) algorithms. …”
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17
Intelligent fault diagnosis for broken rotor bar using wavelet packet signature analysis
Published 2016“…The fault detection and classification algorithm is carried out under the unknown dataset and the off-line testing results with 98.8% classification accuracy indicate good reliability of the proposed method in identifying broken rotor bars severity.…”
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18
Flow-based approach on bro intrusion detection
Published 2017“…Packet-based or Deep Packet Inspection (DPI) intrusion detection systems (IDSs) face challenges when coping with high volume of traffic. …”
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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20
Anomaly detection in ICS datasets with machine learning algorithms
Published 2021“…The features of flow-based network traffic are extracted for behavior analysis with port-wise profiling based on the data baseline, and anomaly detection classification and prediction using machine learning algorithms are performed.…”
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