Search Results - (( java segmentation learning algorithm ) OR ( using machine protocol algorithm ))

Packet header support using hybrid security approach for securing trivial file transfer protocol in machine to machine applications / Nur Nabila Mohamed by Mohamed, Nur Nabila

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Machine Learning For HTTP Botnet Detection Using Classifier Algorithms by Mohd Dollah, Rudy Fadhlee, Abd Majid, Mohd Faizal, Arif, Fahmi, Mas'ud, Mohd Zaki, Lee, Kher Xin

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Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review by Goh, Choon-Hian, Ferdowsi, Mahbuba, Gan, Ming Hong, Kwan, Ban-How, Lim, Wei Yin, Tee, Yee Kai, Rosli, Roshaslina, Tan, Maw Pin *

“…The aims of the study were to systematically evaluate available machine learning (ML) algorithm for supporting syncope diagnosis to determine their performance compared to existing point scoring protocols. …”
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Secure Hybrid Scheme For Securing Mqtt Protocol Based On Enhanced Symmetric Algorithm by Hintaw, Ahmed Jameel

“…Internet of Things (IoT) enables device and machine communication using TCP/IP protocol. Message Queuing Telemetry Transport (MQTT) is the most preferred protocol and is expected to be the de facto messaging IoT standard. …”
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Mitigating Slow Hypertext Transfer Protocol Distributed Denial of Service Attacks in Software Defined Networks by Akanji, Oluwatobi Shadrach, Abisoye, Opeyemi Aderiike, Iliyasu, Mohammed Awwal

“…This study contributes to the ongoing research in detecting and mitigating slow HTTP DDoS attacks with emphasis on the use of machine learning classification and meta-heuristic algorithms.…”
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The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

“…Due to network complexity, conventional QoS-improving routing algorithms (RAs) may be impractical. Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”

Brain Machine Interface Controlled Robot Chair by Hema Chengalvarayan, Radhakrishnamurthy

“…The BMI controls the joystick of the robot chair using a shared control algorithm. Real-time experiments are also presented using 10 trained and 5 untrained subjects to validate the applicability of the brain machine interface. …”
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Intrusion detection on the in-vehicle network using machine learning by Sharmin, Shaila, Mansor, Hafizah

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Adaptive medium access control protocol of Wifi-Halow for home machine-to-machine network by Liew, Jiun Terng

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Botnet Detection in IoT Devices Using Random Forest Classifier with Independent Component Analysis by Akash, Nazmus Sakib, Rouf, Shakir, Jahan, Sigma, Chowdhury, Amlan, Uddin, Jia

“…This paper represents a model that accounts for the detection of botnets through the use of machine learning algorithms. The model examined anomalies, commonly referred to as botnets, in a cluster of IoT devices attempting to connect to a network. …”
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Intelligent DNA signature detection for internet worms by Ghazali, Osman

“…Active worms spread in an automated fashion flooding the Internet in a very short time.Slammer worm infected more than 90% of vulnerable machines within 10 minutes on January 25th, 2003.Hence it is necessary to monitor and detect the worms as soon as they are introduced to minimize the damage caused by them.This project concentrates on developing an anti-scanning worm detection system that can automatically detect and control the spread of internet scanning worms without any manual intervention.The Intelligent Failure Connection Algorithm (IFCA) developed in this project can detect both stealth and normal worms within a short time.Experiments conducted as part of the evaluation shows that IFCA detects a worm within two scanning cycles of the worm.This is faster than any of the currently available algorithms or mechanisms reported in the literature.The IFCA uses Artificial Immune System (AIS) for the purpose of monitoring and detecting the worms.The Traffic Signature Algorithm (TSA) developed in the project captures the traffic signature of the worm from the infector when it sends the traffic to the victim.The Intelligent DNA Signature Detection Algorithm (IDNASDA) algorithm works by breaking an infection session into different infection phases, each phase containing a number of different traffic such as Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), or User Datagram Protocol (UDP).Finally it converts the traffic signature to DNA signature.The tests carried out show that the IDNASD could detect DNA signature for MSBlaster worm.…”
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A protocol for developing a classification system of mosquitoes using transfer learning by Pradeep Isawasan, Zetty Ilham Abdullah, Ong, Song Quan, Khairulliza Ahmad Salleh

“…This protocol aims to develop step-by-step procedure in developing a classification system with transfer learning algorithm for mosquito, we demonstrate the protocol to classify two species of Aedes mosquito - Aedes aegypti L. and Aedes albopitus L, but user can adopt the protocol for higher number of species classification. …”
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Missing tags detection algorithm for radio frequency identification (RFID) data stream by Zainudin, Nur 'Aifaa

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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

“…To validate the research, the researcher presents case study using GLOMOSIM simulation platform with AODV ad hoc routing protocols. …”
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Identifying and predicting Muslim’s community funeral funding protocols by Ibrahim, Izzul Ismail, M Ashhuri, Muhammad Hassan, Hassan, Raini

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Moving vehicle identification using artificial neural network by Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr., Abdul Hamid, Adom, Assoc. Prof. Dr., Siti Marhainis, Othman, Sundararaj, Sathish Kumar

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Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

“…Next, the ML-based routing algorithm is compared to the conventional routing algorithm, Routing Information Protocol version 2 (RIPv2). …”

A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features by Keshkeh, Kinan

“…This study also investigates TLSMalDetect detection performance using seven ML classification algorithms and identifies the one with the highest accuracy.…”
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A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications by Uddin I., Awan H.H., Khalid M., Khan S., Akbar S., Sarker M.R., Abdolrasol M.G.M., Alghamdi T.A.H.

“…To address this challenge, the paper proposed XGB5hmC, a machine learning algorithm based on a robust gradient boosting algorithm (XGBoost), with different residue based formulation methods to identify 5hmC samples. …”