Search Results - flood detection algorithm

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  1. 1

    Cars detection in stitched image using morphological approach by Joselyn, Jok.

    Published 2017
    “…The performance of the proposed cars detection algorithm could detect the cars fairly accurate. …”
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    Final Year Project Report / IMRAD
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    Quranic diacritic and character segmentation and recognition using flood fill and k-nearest neighbors algorithm by Alotaibi, Faiz E A L

    Published 2019
    “…The diacritic detections are performed using a region-based algorithm with 89% accuracy and 95% improved by using flood fill segmentations method. 2DMED feature extraction accuracy was 90% for diacritics and 96% improved by applied CNN. …”
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    Thesis
  3. 3

    Improving The Algorithm To Detect Internet Worms by Rasheed, Mohmmad M

    Published 2008
    “…Active worm spread in an automated fashion and can flood the internet in a very short time. The aim of this project is to improved algorithm to detect internet worm by two sub algorithm. …”
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    Thesis
  4. 4

    SYN Flood detection via machine learning / Muhammad Muhaimin Aiman Mazlan by Mazlan, Muhammad Muhaimin Aiman

    Published 2018
    “…Therefore, the aim of this project is to develop a firewall software called “FIREARMS” that can prevent one type of DDoS which is SYN-Flood attack. The core detection and prevention algorithm which is the support vector machine (SVM) were implemented in this project. …”
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    Student Project
  5. 5

    Flood detector with IoT notifications / Mohammad Fazrul Fahmi Mohammad Razali by Mohammad Razali, Mohammad Fazrul Fahmi

    Published 2024
    “…This abstract presents a cutting-edge Internet of Things (IoT)-enabled flood detection system that is intended to provide prompt notifications and alarms in the case of flooding. …”
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    Student Project
  6. 6

    Design and Implementation of a Robot for Maze-Solving using Flood-Fill Algorithm by Elshamarka, Ibrahim, Saman, Abu Bakar Sayuti

    Published 2012
    “…This paper describes an implementation of a maze-solving robot designed to solve a maze based on the flood-fill algorithm. Detection of walls and opening in the maze were done using ultrasonic range-finders. …”
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    Citation Index Journal
  7. 7

    Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

    Published 2025
    “…While further research requires a special algorithm to improve malware attack detection, in addition to KNN, SVM and Neural Network. …”
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    Article
  8. 8

    Detection and mapping of May 2021 flood in Beaufort, Sabah using Sentinel-1 SAR and Sentinel-2 multispectral in Google Earth Engine by Stanley Anak Suab, Hitesh Supe, Ram Avtar, Ramzah Dambul, Xinyu Chen

    Published 2022
    “…This study provides the basis of detection and mapping floods using S-1 and S-2 imageries through Machine Learning techniques in GEE for local scope of Sabah, Borneo region and Malaysia.…”
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    Conference or Workshop Item
  9. 9

    Image processing-based flood detection by Ariawan, Angga, Pebrianti, Dwi, Ronny, Akbar, Yudha Maulana, Margatama, Lestari, Bayuaji, Luhur

    Published 2019
    “…This paper discusses about the design of an online ftood detection and early warning system which integrated to using Raspberry-PI and optical sensor. …”
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    Conference or Workshop Item
  10. 10

    Intelligent DNA signature detection for internet worms by Ghazali, Osman

    Published 2011
    “…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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    Monograph
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    Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband by Shamshirband, Shahaboddin

    Published 2014
    “…Adaptive optimization techniques such as fuzzy logic controller (FLC), reinforcement learning are discussed in this thesis in order to adopt Q-leaning algorithm to FLCs. We investigate the detection capability based on the fuzzy Q-learning (FQL) algorithm and evaluate it using distribute denial of service attacks (DDoS). …”
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    Thesis
  12. 12

    An algorithm to group defects on printed circuit board for automated visual inspection by Khalid, Noor Khafifah, Ibrahim, Zuwairie, Zainal Abidin, Mohamad Shukri

    Published 2008
    “…The proposed algorithm includes several image processing operations such as image subtraction, image adding, logical XOR and NOT, and flood fill operator…”
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    Article
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    Evaluation of boruta algorithm in DDoS detection by Noor Farhana, Mohd Zuki, Ahmad Firdaus, Zainal Abidin, Mohd Faaizie, Darmawan, Mohd Faizal, Ab Razak

    Published 2023
    “…To evaluate the Boruta algorithm, multiple classifiers (J48, random forest, naïve bayes, and multilayer perceptron) were used so as to determine the effectiveness of the features selected by the the Boruta algorithm. …”
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    Article
  16. 16

    River segmentation with Atrous Convolution via DeepLabv3 / Nur Adilah Hamid by Hamid, Nur Adilah

    Published 2020
    “…Flood has been identified as a common issue for years. …”
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    Student Project
  17. 17

    A survey of interest flooding attack in named-data networking: Taxonomy, performance and future research challenges by Ren-Ting Lee, Yu-Beng Leau, Yong Jin Park, Mohammed Anbar

    Published 2021
    “…This study aimed to conduct a comprehensive survey of state-of-the-art IFA detection mechanisms and analyzed the algorithms used. …”
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    Article
  18. 18

    DDoS Classification using Combined Techniques by Mohd Yusof, Mohd Azahari, Mohd Safar, Noor Zuraidin, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Jofri, Muhamad Hanif, Mohamed, Juliana, Omar, Abdul Halim, Bahrudin, Ida Aryanie, Mohamed Ali @ Md Hani, Mohd Hatta

    Published 2024
    “…An attacker has the capability to generate various types of DDoS attacks simultaneously, including the Smurf attack, ICMP flood, UDP flood, and TCP SYN flood. This DDoS issue encouraged the design of a classification technique against DDoS attacks that enter a computer network environment. …”
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    Article
  19. 19

    DDoS Classification using Combined Techniques by Mohd Yusof, Mohd Azahari, Mohd Safar, Noor Zuraidin, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Jofri, Muhamad Hanif, Mohamed, Juliana, Omar, Abdul Halim, Bahrudin, Ida Aryanie, Mohamed Ali @ Md Hani, Mohd Hatta

    Published 2024
    “…An attacker has the capability to generate various types of DDoS attacks simultaneously, including the Smurf attack, ICMP flood, UDP flood, and TCP SYN flood. This DDoS issue encouraged the design of a classification technique against DDoS attacks that enter a computer network environment. …”
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    Article
  20. 20

    RFID-enabled supply chain detection using clustering algorithms by Azahar, T.F., Mahinderjit-Singh, M., Hassan, R.

    Published 2015
    “…We propose to use clustering algorithms in order to detect counterfeit in supply chain management. …”
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    Conference or Workshop Item