Search Results - (( rate evaluation method algorithm ) OR ( attack detection method algorithm ))

An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm by Abdulkareem, Fatimah Saleem, Mohd Sani, Nor Fazlida

“…Therefore, an intrusion detection method for attacking and detecting anomalies in an IoT system must be enhanced. …”
Get full text
Get full text

An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack by Yusof, Ahmad Riza’ain, Udzir, Nur Izura, Selamat, Ali

Get full text
Get full text
Get full text

Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…Thus, this study proposes the development of algorithms to detect and classify jamming attacks using a set of parameters on the physical layer and MAC in MANET. …”
Get full text
Get full text

Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…While the effectiveness of some machine learning algorithms in detecting certain types of network intrusion has been ascertained, the situation remains that no single method currently exists that can achieve consistent results when employed for the detection of multiple attack types. …”
Get full text
Get full text

AI Meta-Learners and Extra-Trees Algorithm for the Detection of Phishing Websites by Alsariera, Y.A., Adeyemo, V.E., Balogun, A.O., Alazzawi, A.K.

Get full text
Get full text

Anomaly-based intrusion detection through K-means clustering and naives Bayes classification by Mohamed Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md. Nasir

“…Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
Get full text
Get full text
Get full text

Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification by Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md Nasir

“…Intrusion detection systems (IDSs) effectively balance extra security appliance by identifying intrusive activities on a computer system, and their enhancement is emerging at an unexpected rate.Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
Get full text
Get full text
Get full text

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

A clustering-based method for outlier detection under concept drift by Tahir, Mahjabeen, Abdullah, Azizol, Udzir, Nur Izura, Kasmiran, Khairul Azhar

“…The algorithm achieves notable results, with a detection rate of 99.12% on UNSWNB-15 and a 7.9% false positive rate on NSL-KDD, marking significant progress. …”
Get full text
Get full text
Get full text

Application of machine learning and artificial intelligence in detecting SQL injection attacks by Md Sultan, Abu Bakar, Agiliga, Nwabudike Augustine, Osman, Mohd Hafeez Bin, Sharif, Khaironi Yatim

“…The main aim of this work is focusing on solving the IT-related challenge lack-of-adequate knowledge bases and tools for security practitioners to monitor and mitigate SQL Injection attacks with AI/ML techniques. The study uses a mixed-methods approach to evaluate how well different AI and ML algorithms identify SQL injection attacks by combining algorithmic evaluation with empirical investigation. …”
Get full text
Get full text
Get full text

Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

“…Hence, there must be substantial improvement in network intrusion detection techniques and systems. Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
Get full text
Get full text
Get full text

An intelligent DDoS attack detection tree-based model using Gini index feature selection method by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik, Atigh, Hayate El

“…This paper proposes a novel intelligent DDoS attack detection model based on a Decision Tee (DT) algorithm and an enhanced Gini index feature selection method. …”
Get full text
Get full text

A multi-filter feature selection in detecting distributed denial-of-service attack by Yon, Yi Jun, Leau, Yu-Beng, Suraya Alias, Park, Yong Jin

“…Subsequently, an experimental evaluation of the proposed Multi-Filter Feature Selection (M2FS) method is performed by using the benchmark dataset, NSL-KDD and employed the J48 classification algorithm. …”
Get full text
Get full text
Get full text
Get full text

Compression Header Analyzer Intrusion Detection System (CHA - IDS) for 6LoWPAN Communication Protocol by Napiah, Mohamad Nazrin, Idris, Mohd Yamani Idna, Ramli, Roziana, Ahmedy, Ismail

“…However, these IDS methods only detect specific attack but fails when the attacks are combined. …”
Get full text
Get full text

An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons by Ghanem, Waheed Ali H. M., Aman, Jantan, Ahmed Ghaleb, Sanaa Abduljabbar, Naseer, Abdullah B.

“…This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
Get full text
Get full text
Get full text

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

“…Although the statistical-based anomaly detection (SAD) method fascinates researchers, the low attack detection rates (also known as the detection of true positive) that reflect the effectiveness of the detection system generally persist. …”
Get full text
Get full text

Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model by Jasim, Ahmed Abdulhadi, Idris, Mohd Yamani Idna, Azzuhri, Saaidal Razalli, Issa, Noor Riyadh, Noor, Noorzaily Mohamed, Kakarla, Jagadeesh, Amiri, Iraj Sadegh

“…To ensure the reliability of our proposed method, we simulate two well-known attacks, called Sybil and sinkhole attacks. …”
Get full text
Get full text

Modelling of intelligent intrusion detection system: making a case for snort by Olanrewaju, Rashidah Funke, Ku zahir, Ku Nor Afiza, Asnawi, Ani Liza, Sanni, Mistura Laide, Ahmed, Abdulkadir Adekunle

“…Hence, this study proposes a method for early detection of an intrusion by using Snort software. …”
Get full text
Get full text
Get full text
Get full text

A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
Get full text
Get full text
Get full text

A Cryptojacking Detection System With Product Moment Correlation Coefficient (Pmcc) Heatmap Intelligent by Kong, Jun Hao

“…This study aims to develop a cryptojacking detection system based to the random forest algorithm.…”
Get full text
Get full text