Search Results - (( developing security bayes algorithm ) OR ( java implication based algorithm ))

Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

“…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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Comparison of hidden Markov Model and Naïve Bayes algorithms among events in smart home environment by Babakura, Abba, Sulaiman, Md Nasir, Mustapha, Norwati, Kasmiran, Khairul A.

“…In this paper, we propose Hidden Markov Model (HMM) and Naïve Bayes (NB) to test the accuracy and response time of the home data and to compare between the two algorithms. …”
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A New Model For Network-Based Intrusion Prevention System Inspired By Apoptosis by Mohammed Nadir bin Ali

Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.] by Mohd Fuzi, Mohd Faris, Mohd Shahirudin, Syamir, Abd Halim, Iman Hazwam, Jamaluddin, Muhammad Nabil Fikri

“…This study includes the scripting and development of supervised ML techniques such as Decision Tree (DT), K-Nearest Neighbors (KNN), Naive Bayes, Random Forest, and Neural Networks. …”
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Android Mobile Malware Classification Based on System Call and Permission Using Tokenization by Intan Nurfarahin Binti Ahmad

Evaluating Machine Learning Algorithms for Fake Currency Detection by Keerthana, S.N, Chitra, K.

“…Our findings contribute to developing reliable, automated systems for counterfeit detection, and enhancing financial security…”
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Phishing attack detection using machine learning method by Jupin, John Arthur

“…The Naïve Bayes algorithm, Decision Tree algorithm and Support Vector Machine algorithm has been used to prevent the spam attack, as well as the phishing attack. …”
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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems by Azad, Saiful, Mahmud, Mufti, Kamal Zuhairi, Zamli, Kaiser, M. Shamim, Jahan, Sobhana, Razzaque, Md Abdur

“…Therefore, this paper proposes an ARL-based intelligent Behavioural Trust Model (iBUST) for securing the CPPS. For this intelligent TMM, a variant of Frequency Pattern Growth (FP-Growth), called enhanced FP-Growth (EFP-Growth) algorithm is developed by altering the internal data structures for faster execution and by developing a modified exponential decay function (MEDF) to automatically calculate minimum supports for adapting trust evolution characteristics. …”
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Android Ransomware Detection Based on Dynamic Obtained Features by Abdullah Z., Muhadi F.W., Hamid I.R.A., Foozy C.F.M., Madihah Mohd Saudi

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Internet of Things (IoT) intrusion detection by Machine Learning (ML): a review by Dehkordi, Iman Farhadian, Manochehri, Kooroush, Aghazarian, Vahe

“…The goal of this study is to show the results of analyzing various classification algorithms in terms of confusion matrix, accuracy, precision, specificity, sensitivity, and f-score to Develop an Intrusion Detection System (IDS) model.…”
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Android malware detection using permission based static analysis by Mohd Ariffin, Noor Afiza, Casinto, Hanna Pungo

“…Then, K-nearest Neighbor (KNN) and Naïve Bayes (NB) algorithms are applied, and the proposed method is compared with the previous studies and the expected experimental results of the proposed approach will be higher.…”
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Android malware detection using permission based static analysis by Mohd Ariffin, Noor Afiza, Casinto, Hanna Pungo

“…Then, K-nearest Neighbor (KNN) and Na¯ve Bayes (NB) algorithms are applied, and the proposed method is compared with the previous studies and the expected experimental results of the proposed approach will be higher.…”
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Improving malicious detection rate for Facebook application in OSN platform by Angamuthu, Laavanya

“…Our key contribution in this part is in developing malware detection in Facebook third party application by using Naïve Bayes algorithm technique .We identify a set of features that help us distinguish malicious apps from benign ones. …”
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Detection of SQL injection attack using machine learning by Tung, Tean Thong

“…The machine learning algorithms employed in this study encompass Convolutional Neural Networks (CNN), Logistic Regression, Naïve Bayes Classifier, Support Vector Machine, and Random Forest. …”
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Detection of DDoS attacks in IoT networks using machine learning algorithms by Abdulrahman Alwan, Alwan Ahmed, Shah, Asadullah, Abdulrahman Alwan, Alwan Abdullah, Laghari, Shams Ul Arfeen

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Spear- phishing attack detection using artificial intelligence by Rajkumaradevan, Sanglidevan

“…By integrating these applications into broader security frameworks, their impact could be further enhanced. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach by Mohamed Yassin, Warusia

“…Intrusion detection systems (IDSs) effectively balance additional security in a computer system by identifying intrusive activities on a computer system, and their enhancements are developing at a surprising rate. …”
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