Search Results - (( attack detection force algorithm ) OR ( java application mining algorithm ))

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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Features selection for IDS in encrypted traffic using genetic algorithm

    Features selection for IDS in encrypted traffic using genetic algorithm by Barati, Mehdi, Abdullah, Azizol, Mahmod, Ramlan, Mustapha, Norwati, Udzir, Nur Izura

    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.Brute Force attack traffic collected in a client-server model is implemented in proposed method.Our results prove that the most efficient features were selected by proposed method.…”
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  3. 3
    Features selection for ids in encrypted traffic using genetic algorithm

    Features selection for ids in encrypted traffic using genetic algorithm by Barati, Mehdi, Abdullah, Azizol, Mahmod, Ramlan, Mustapha, Norwati, Udzir, Nur Izura

    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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  4. 4
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  5. 5
    ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets

    ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Khan, Sheroz

    Published 2021
    “…The processed metadata is normalized for the easiness of algorithm analysis and modelled with machine learning-based latest deep learning ensemble LSTM algorithms for anomaly detection. …”
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  6. 6
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  7. 7
    CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning

    CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning by Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Azlee, Zabidi, Mohd Faizal, Ab Razak

    Published 2023
    “…Afterwards, this study adopts Convolutional Neural Network (CNN) for malware detection and classification algorithm. We compare CAGDeep with a state-of-the-art Android malware detection approach. …”
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  8. 8
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  9. 9
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  10. 10
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  11. 11
    Secure IIoT-enabled industry 4.0

    Secure IIoT-enabled industry 4.0 by Zeeshan Hussain, Adnan Akhunzada, Javed Iqbal, Iram Bibi, Abdullah Gani

    Published 2021
    “…IIoT-enabled botnets are highly scalable, technologically diverse, and highly resilient to classical and conventional detection mechanisms. Subsequently, we propose a deep learning (DL)-enabled novel hybrid architecture that can efficiently and timely tackle distributed, multivariant, lethal botnet attacks in industrial IoT. …”
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  12. 12
    Multistage quality control in manufacturing process using blockchain with machine learning technique

    Multistage quality control in manufacturing process using blockchain with machine learning technique by Gu, J., Zhao, L., Yue, X., Arshad, N.I., Mohamad, U.H.

    Published 2023
    “…BCT allows collecting sensor user access data, whereas ML classifiers distinguish between normal and malicious behavior to detect attacks. DoS, DDoS, intrusion, a man in the middle (MitM), brute force, cross-site scripting (XSS), and searching are the attacks detected by BCT. …”
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  13. 13
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  14. 14
    Secure multi-authority attribute-based encryption access control with cache-aware scheduling in mobile cloud computing

    Secure multi-authority attribute-based encryption access control with cache-aware scheduling in mobile cloud computing by Jamal, Fara

    Published 2021
    “…The result indicated that the Mean Downtime Time for the proposed solution was only 3.88 minutes compared to the existing solution, which was 38.56 minutes. During a security attack, the MTTD for the existing solution was very high because the existing scheme could not detect the attack. …”
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