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Intrusion Detection System Using FKNN and Improved PSO

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Computers, Materials & Continua 2021年第5期67卷 1429-1445页

作者： raniyah wazirali College of Computing and Informatics Saudi Electronic UniversitySaudi ArabiaRiyadh

Intrusion detection system(IDS)techniques are used in cybersecurity to protect and safeguard sensitive *** increasing network security risks can be mitigated by implementing effective IDS methods as a defense *** proposed research presents an IDS model based on the methodology of the adaptive fuzzy k-nearest neighbor(FKNN)*** this method,two parameters,i.e.,the neighborhood size(k)and fuzzy strength parameter(m)were characterized by implementing the particle swarm optimization(PSO).In addition to being used for FKNN parametric optimization,PSO is also used for selecting the conditional feature subsets for *** proficiently regulate the indigenous and comprehensive search skill of the PSO approach,two control parameters containing the time-varying inertia weight(TVIW)and time-varying acceleration coefficients(TVAC)were applied to the *** addition,continuous and binary PSO algorithms were both executed on a multi-core *** proposed IDS model was compared with other state-of-the-art *** results of the proposed methodology are superior to the rest of the techniques in terms of the classification accuracy,precision,recall,and *** results showed that the proposed methods gave the highest performance scores compared to the other conventional algorithms in detecting all the attack types in two ***,the proposed method was able to obtain a large number of true positives and negatives,with minimal number of false positives and negatives.

关键词： FKNN PSO approach machine learning-based cybersecurity intrusion detection

Hybrid Feature Extractions and CNN for Enhanced Periocular Identification During Covid-19

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Computer Systems Science & Engineering 2022年第4期41卷 305-320页

作者： raniyah wazirali Rami Ahmed College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia The School of Information Technology Sebha UniversitySebha71Libya

The global pandemic of novel coronavirus that started in 2019 has ser-iously affected daily lives and placed everyone in a panic *** coronavirus led to the adoption of social distancing and people avoiding unneces-sary physical contact with each *** present situation advocates the require-ment of a contactless biometric system that could be used in future authentication systems which makesﬁngerprint-based person identiﬁcation ***-lar biometric is the solution because it does not require physical contact and is able to identify people wearing face ***,the periocular biometric region is a small area,and extraction of the required feature is the point of *** paper has proposed adopted multiple features and emphasis on the periocular *** the proposed approach,combination of local binary pattern(LBP),color histogram and features in frequency domain have been used with deep learning algorithms for classiﬁ***,we extract three types of fea-tures for the classiﬁcation of periocular regions for *** LBP represents the textual features of the iris while the color histogram represents the frequencies of pixel values in the RGB *** order to extract the frequency domain fea-tures,the wavelet transformation is *** learning from these features,a convolutional neural network(CNN)becomes able to discriminate the features and can provide better recognition *** proposed approach achieved the highest accuracy rates with the lowest false person identiﬁcation.

关键词： Person identiﬁcation convolutional neural network local binary pattern periocular region Covid-19

Machine Learning Approaches to Detect DoS and Their Effect on WSNs Lifetime

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Computers, Materials & Continua 2022年第3期70卷 4921-4946页

作者： raniyah wazirali Rami Ahmad College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia The School of Information Technology Sebha UniversitySebha71Libya

Energy and security remain the main two challenges in Wireless Sensor Networks(WSNs).Therefore,protecting these WSN networks from Denial of Service(DoS)and Distributed DoS(DDoS)is one of the WSN networks security *** packet deep scan systems that rely on open field inspection in transport layer security packets and the open field encryption trend are making machine learning-based systems the only viable choice for these types of *** paper contributes to the evaluation of the use machine learning algorithms in WSN nodes traffic and their effect on WSN network life *** examined the performance metrics of different machine learning classification categories such asK-Nearest Neighbour(KNN),Logistic Regression(LR),Support Vector Machine(SVM),Gboost,Decision Tree(DT),Na飗e Bayes,Long Short Term Memory(LSTM),and Multi-Layer Perceptron(MLP)on aWSN-dataset in different *** test results proved that the statistical and logical classification categories performed the best on numeric statistical datasets,and the Gboost algorithm showed the best performance compared to different algorithms on average of all performance *** performance metrics used in these validations were accuracy,F1-score,False Positive Ratio(FPR),False Negative Ratio(FNR),and the training execution ***,the test results showed the Gboost algorithm got 99.6%,98.8%,0.4%0.13%in accuracy,F1-score,FPR,and FNR,*** training execution time,it obtained 1.41 s for the average of all training time execution *** addition,this paper demonstrated that for the numeric statistical data type,the best results are in the size of the dataset ranging from3000 to 6000 records and the percentage between categories is not less than 50%for each category with the other ***,this paper investigated the effect of Gboost on the WSN lifetime,which resulted in a 32%reduction compared to other Gboost-free scenarios.

关键词： WSN intrusion detection machine learning DoS attack WSN security WSN lifetime

A Multi-Stage Secure IoT Authentication Protocol

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Computer Systems Science & Engineering 2023年第4期45卷 459-481页

作者： Khalid Alhusayni raniyah wazirali Mousa AlAkhras Marwah Almasri Samah Alhazmi College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia King Abdullah II School for Information Technology The University of JordanAmman11942Jordan

The Internet of Things(IoT)is a network of heterogeneous and smart devices that can make decisions without human *** can connect millions of devices across the *** ability to collect information,perform analysis,and even come to meaningful conclusions without human capital intervention *** circumstances require stringent security measures and,in particular,the extent of *** applied in the IoT paradigm point out high-interest levels since enormous damage will occur if a malicious,wrongly authenticated device finds its way into the IoT *** research provides a clear and updated view of the trends in the IoT authentication *** the issues covered include a series of authentication protocols that have remained research gaps in various *** study applies a comparative evaluation of authentication protocols,including their strengths and ***,it forms the foundation in the IoT authentication field of *** that direction,a multi authentication architecture that involves secured means is proposed for protocol *** analysis can affect the security of the ***-Abadi-Needham(BAN)logic provides proof of the attainment of mutual ***3 simulator tool is used to compare the performance of the proposed protocol to verify the formal security offered by the BAN logic.

关键词： Internet of Things(IoT) security authentication BAN logic sensor networks