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

Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

“…The project successfully achieves its predetermined objectives, culminating in the development of an effective Remote to Local (R2L) Intrusion Detection System utilizing the Decision Tree algorithm. …”
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An optimized attack tree model for security test case planning and generation by Omotunde, Habeeb, Ibrahim, Rosziati, Ahmed, Maryam

“…By leveraging on the optimized attack tree algorithm used in this research work, the threat model produces efficient test plans from which adequate test cases are derived to ensure a secured web application is designed, implemented and deployed. …”
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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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A novel steganography algorithm using edge detection and MPC algorithm by Aref Rezaei, Leili Farzinvash, Ali Farzamnia

“…With the rapid development of the Internet, preserving the security of confidential data has become a challenging issue. …”
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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

“…The results indicated that the Decision Tree and Random Forest algorithms provided the best detection accuracy at 96%, followed by the K-NN algorithm at 95%. …”
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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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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

Enhanced dynamic security assessment for power system under normal and fake tripping contingencies. by A. Salih, Qusay

“…The hybrid logistic model tree (hybrid LMT) approach proposed in this study combines the symmetrical uncertainties (SU) algorithm and the logistic model tree (LMT) algorithm. …”
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Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm by Arezoumand, Reza

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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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Optimized scheme for efficient and scalable key management in IEEE 802.16e-based networks by Sadeghi, Mohammad Mehdi Gilanian

“…To generate, update and distribute the keys for secure communication over IEEE 802.16e, the MBS applies Multicast and Broadcast Rekeying Algorithm (MBRA) as a basic key management algorithm. …”
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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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Anomaly detection in network traffic using machine learning by Amir Muhammad Hafiz, Othman, Mohd Faizal, Ab Razak, Mohd Izham, Mohd Jaya, Nurul Azma, Abdullah, Alanda, Alde

“…These findings demonstrate that machine learning techniques have strong potential to enhance network security by improving anomaly detection, providing a promising direction for developing intelligent, adaptive intrusion detection.…”
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A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

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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Research on risk detection of autonomous vehicle based on rapidly-exploring random tree by Yincong Ma, Lim, Kit Guan, Tan, Min Keng, Sin, Helen Ee Chuo, Ali Farzamnia, Tze, Kenneth Kin Teo

“…On the premise of ensuring safety and meeting the requirements of the vehicle’s kinematic constraints through the expansion of obstacles, the dynamic step size is used for random tree growth. A non-particle collision detection (NPCD) collision detection algorithm and path modification (PM) path modification strategy are proposed for the collision risk in the turning process, and geometric constraints are used to represent the possible security threats, so as to improve the efficiency and safety of vehicle global path driving and to provide reference for the research of driverless vehicles.…”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat by Selamat, Nur Syuhada

“…Currently, the size of malware grows faster each year and poses a thoughtful global security threat. The number of malware developed is increasing as computers became interconnected, at an alarming rate in the 1990s. …”
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A framework for classification software security using common vulnerabilities and exposures by Hassan, Nor Hafeizah

“…Formal-based classification framework with notation may increase accuracy and vi-sualization compared with hierarchy-tree only,but the conclusion remains tentative because of methodological limitation in the studies.…”
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