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  1. 1
    A malware analysis and detection system for mobile devices / Ali Feizollah

    A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

    Published 2017
    “…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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  2. 2
    Network game (Literati) / Chung Mei Kuen

    Network game (Literati) / Chung Mei Kuen by Chung, Mei Kuen

    Published 2003
    “…Java applet is a well-known and widely used example of mobile code (a variation on the traditional client-server model). …”
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  3. 3
    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application

    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

    Published 2020
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  4. 4
    Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system

    Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

    Published 2011
    “…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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  5. 5
    Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider

    Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider by Omer Fadlelmola Elkhider, Samih

    Published 2011
    “…The studies show beyond technical algorithms, physical aspects plays a big rule in client server model. …”
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  6. 6
    Machine learning algorithms in context of intrusion detection

    Machine learning algorithms in context of intrusion detection by Mehmood, T., Rais, H.B.Md.

    Published 2016
    “…Asymmetrically, anomaly based detection method can detect novel attacks but it has high false positive rate. …”
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  7. 7
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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  8. 8
    Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework

    Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework by Asaad Aref, Ibrahim

    Published 2004
    “…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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  9. 9
    A Model for Evaluation of Cryptography Algorithm on UUM Portal

    A Model for Evaluation of Cryptography Algorithm on UUM Portal by Norliana, Abdul Majid

    Published 2004
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  10. 10
    Implementation of (AES) Advanced Encryption Standard algorithm in communication application

    Implementation of (AES) Advanced Encryption Standard algorithm in communication application by Moh, Heng Huong

    Published 2014
    “…On the basis of the results of this research, it can be concluded that the developed prototype had high accuracy and security when transferring the file between the sender and receiver that was implemented in client-server application. This research hopes to give a clear idea to the readers about ABS algorithm. …”
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  11. 11
    Dynamic intrusion detection method for mobile ad hoc network using CPDOD algorithm

    Dynamic intrusion detection method for mobile ad hoc network using CPDOD algorithm by Abdel-Fatah, Farhan, Md Dahalin, Zulkhairi, Jusoh, Shaidah

    Published 2010
    “…A series of experimental results demonstrate that the proposed method can effectively detect anomalies with low false positive rate, high detection rate and achieve higher detection accuracy.…”
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  12. 12
    Classification System for Heart Disease Using Bayesian Classifier

    Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

    Published 2007
    “…This system was mainly developing using java programming. Apache Tom cat was used as a server in order to run the application smoothly. …”
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  13. 13
    A study on advanced statistical analysis for network anomaly detection

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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  14. 14
    On the combination of adaptive neuro-fuzzy inference system and deep residual network for improving detection rates on intrusion detection

    On the combination of adaptive neuro-fuzzy inference system and deep residual network for improving detection rates on intrusion detection by Jia, Liu, Yin Chai, Wang, Chee Siong, Teh, Xinjin, Li, Liping, Zhao, Fengrui, Wei

    Published 2022
    “…The experimental results demonstrate that the proposed method is better than that of the original ResNet and other existing methods on various metrics, reaching a 98.88% detection rate and 1.11% false alarm rate on the KDDTrain+ dataset…”
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  15. 15
    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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  16. 16
    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…An efficient IDS uses computational methods as techniques of machine learning (ML) to enhance the rates of detection to obtain the lowest false positive rate, although such rates tend to be reduced by the big amount of irrelevant features as an optimization issue. …”
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  17. 17
    Methods of intrusion detection in information security incident detection: a comparative study

    Methods of intrusion detection in information security incident detection: a comparative study by Tan, Fui Bee, Yau, Ti Dun, M. N. M., Kahar

    Published 2018
    “…These algorithms and methods provide fast and high rate of detection. …”
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  18. 18
    Improved Switching-Basedmedian Filter For Impulse Noise Removal

    Improved Switching-Basedmedian Filter For Impulse Noise Removal by Teoh, Sin Hoong

    Published 2013
    “…Based on the evaluations from root mean square error (RMSE), false positive detection rate, false negative detection rate, mean structure similarity index (MSSIM), processing time, and visual inspection, it is shown that the proposed method is the best method when compared with seven other state-of-the art median filtering methods.…”
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  19. 19
    An immune-genetic algorithm with tabu local search for network intrusion detection system / Hamizan Suhaimi

    An immune-genetic algorithm with tabu local search for network intrusion detection system / Hamizan Suhaimi by Suhaimi, Hamizan

    Published 2021
    “…The performance of the proposed method and other existing techniques (Genetic Algorithm, Artificial Immune System and Immune-Genetic Algorithm) were analysed to evaluate and determine its efficiency in terms of maximum intrusion detection rate and the highest true positive rate. …”
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  20. 20
    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
    “…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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