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  1. 1

    Hybrid cryptography algorithm to improve security cloud storage by Abd Almohsen, Inam Razzaq

    Published 2017
    “…ECC, AES, and RSA algorithms will be used to encrypt the files to enhance security data on the cloud storage. …”
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    Thesis
  2. 2

    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

    Published 2021
    “…The encryption algorithms are playing an important part in the protection level for data. …”
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    Thesis
  3. 3

    Securing cloud data system (SCDS) for key exposure using AES algorithm by Thabet Albatol, Mohammed Samer Hasan

    Published 2021
    “…The AES algorithm has its own structure to encrypt and decrypt sensitive data that make the attackers difficult to get the real data when encrypting by AES algorithm. …”
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  4. 4

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

    Published 2014
    “…This research hopes to give a clear idea to the readers about ABS algorithm. Further research about this topic is recommended to increase the efficiency of ABS algorithm implemented in communication field, so that more different types of field can be encrypted and decrypted instead of plaintext.…”
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    Undergraduates Project Papers
  5. 5

    Design and Implementation of Data-at-Rest Encryption for Hadoop by Wan Nor Shuhadah, Wan Nik, Mohamad Afendee, Mohamed, Zarina, Mohamad, Siti Hanisah, Kamaruzaman

    Published 2017
    “…Therefore, the AES encryption algorithm has been implemented in HDFS to ensure the security of data stored in HDFS. …”
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    Conference or Workshop Item
  6. 6

    Design and Implementation of Data-at-Rest Encryption for Hadoop by Wan Nor Shuhadah, Wan Nik, Mohamad Afendee, Mohamed, Zarina, Mohamad, Siti Hanisah, Kamaruzaman

    Published 2017
    “…Therefore, the AES encryption algorithm has been implemented in HDFS to ensure the security of data stored in HDFS. …”
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    Conference or Workshop Item
  7. 7

    SANAsms: Secure short messaging system for secure GSM mobile communication by Anuar, N.B., Azlan, I.M., Wahid, A.W.A., Zakaria, O.

    Published 2008
    “…J2ME phone and Symbian Operating System (OS) as the platform for the application to run. The encryption algorithm that implemented in the system is Advanced Encryption Standard (AES) with 128-bit block size and together with the SHA1 (Secure Hash Algorithm) hash functions. …”
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    Conference or Workshop Item
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    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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    Thesis
  10. 10

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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    Thesis
  11. 11

    Campus safe: Safeguarding GPS-based Physical Identity and Access Management (PIAM) system with a lightweight Geo-Encryption by Yeo Zi Zian

    Published 2022
    “…The selected lightweight geo-encryption algorithm will be implemented in the proposed system, vi which develops by using Java language. …”
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    Academic Exercise
  12. 12

    Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

    Published 2025
    “…Email spam is a significant issue confronting both email consumers and providers. The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. …”
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    Article
  13. 13

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…Individual emotional states are highly variable and are subject to evolution from personal experiences. For this reason, the above system is designed to be able to perform learning and classification in real-time to account for inter-individual and intra-individual emotional drift over time. …”
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    Conference or Workshop Item
  14. 14

    Artificial fish swarm optimization for multilayer network learning in classification problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam

    Published 2012
    “…Nature-Inspired Computing (NIC) has always been a promising tool to enhance neural network learning. Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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    Article
  15. 15

    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2012
    “…In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems. …”
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    Article
  16. 16

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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    Conference or Workshop Item
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    A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

    Published 2019
    “…A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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    Article
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    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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    Article