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Fine-Tuning Cyber Security Defenses: Evaluating Supervised Machine Learning Classifiers for Windows Malware Detection

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computers, Materials & Continua 2024年第8期80卷 2917-2939页

作者： Islam Zada Mohammed Naif Alatawi Syed Muhammad Saqlain Abdullah Alshahrani Adel Alshamran Kanwal Imran Hessa Alfraihi Department of Software Engineering International Islamic UniversityIslamabad25000Pakistan Information Technology Department Faculty of Computers and Information TechnologyUniversity of TabukTabuk71491Saudi Arabia Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Computer Science University of PeshawarPeshawar25121Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Malware attacks on Windows machines pose significant cybersecurity threats,necessitating effective detection and prevention *** machine learning classifiers have emerged as promising tools for malware ***,there remains a need for comprehensive studies that compare the performance of different classifiers specifically for Windows malware *** this gap can provide valuable insights for enhancing cybersecurity *** numerous studies have explored malware detection using machine learning techniques,there is a lack of systematic comparison of supervised classifiers for Windows malware *** the relative effectiveness of these classifiers can inform the selection of optimal detection methods and improve overall security *** study aims to bridge the research gap by conducting a comparative analysis of supervised machine learning classifiers for detecting malware on Windows *** objectives include Investigating the performance of various classifiers,such as Gaussian Naïve Bayes,K Nearest Neighbors(KNN),Stochastic Gradient Descent Classifier(SGDC),and Decision Tree,in detecting Windows *** the accuracy,efficiency,and suitability of each classifier for real-world malware detection *** the strengths and limitations of different classifiers to provide insights for cybersecurity practitioners and *** recommendations for selecting the most effective classifier for Windows malware detection based on empirical *** study employs a structured methodology consisting of several phases:exploratory data analysis,data preprocessing,model training,and *** data analysis involves understanding the dataset’s characteristics and identifying preprocessing *** preprocessing includes cleaning,feature encoding,dimensionality reduction,and optimization to prepare the data for *** training utilizes various

关键词： Security and privacy challenges in the context of requirements engineering supervisedmachine learning malware detection windows systems comparative analysis Gaussian Naive Bayes K Nearest Neighbors Stochastic Gradient Descent Classifier Decision Tree

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Review on the Effect of Student Learning Outcome and Teaching Technology in Omani’s Higher Education Institution’s Academic Accreditation Process

Review on the Effect of Student Learning Outcome and Teachin...

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2018年第七届软件与计算机应用国际会议

作者： Ragad M.Tawafak Muamer N.Mohammed Ruzaini bin Abdullah Arshah Awanis Romli Faculty of Computer Systems and Software Engineering University Malaysia Pahang Malaysia IBM Center of Excellence University Malaysia Pahang Faculty of Computer Systems and Software Engineering University Malaysia Pahang

Academic accreditation standards are defined clearly in Higher Educational Institutions（HEI） plans, management, and delivering results of assessment student with learning outcomes. In recent years, all universities and institutions work hard to increase their approval privileges, skills, achievements through getting the accreditation from HEI. The aim of this integrative review was to examine the current evidence on the impact of technology learning on student learning and academic performance and analysis the main factors of an institution accreditation process. The authors searched several electronic databases for relevant articles, with different learning techniques. The main contribution of this study lies in showing the general criteria’s of accreditation standards that focus on essential technology enhanced learning, student learning outcomes, and faculty technology experience on academic performance of universities. The result from this paper is showing the relations between what have been done and presented before with methods, factors, suggestions to identify these activities.

关键词： Higher Educational Institute （HEI） Student Learning Outcome （SLO） Technology Learning Quality Assurance Accreditation

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Land cover classification using Landsat data (study area: Pekan district, Pahang state, Malaysia) 4

Land cover classification using Landsat data (study area: Pe...

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4th International Conference on software engineering and computer systems, ICSECS 2015

作者： Jamaruppin, Mohamad Eliyass Bin Pebrianti, Dwi Bayuaji, Luhur Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Abdul Razak Kuantan Malaysia Faculty of Electrical and Electronic Engineering Universiti Malaysia Pahang Malaysia University Malaysia Pahang Lebuhraya Tun Abdul Razak Kuantan Malaysia

ISBN: (纸本)9781467367226

In order to investigate the terrain changed in areas of urban, vegetation, bare land, and water type mapping in Pekan, Pahang of Malaysia using Landsat data. The data of a district of educational and research on years 2000 and 2013, were analyzed. First, will evaluating the quality of the image of Landsat data. There were no obvious errors noticeable on the geometric and radiometric. In order to estimate the accuracy of the map derived from classification, a ground truth map was prepared using strip sampling on map. Image classification was performed using original and synthetic bands for following four land types: urban, water, bare land, vegetation, and cloud types. Classification was performed using maximum likelihood (ML). The highest accuracy was obtained by using ML classifier. According to the results of this study, the spectral data of Landsat data have a large potential for land type mapping in Pekan area mapping. © 2015 IEEE.

关键词： Landsat

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Smart Harvesting based on Image Processing

Smart Harvesting based on Image Processing

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2020 International computer Symposium, ICS 2020

作者： Joseph, S.P Wijerathna, L.L.M.C. Epa, K.G.R.D. Egalla, E.K.W.A.P.K. Abeygunawardhana, P.W.K. De Silva, R Sri Lanka Institute of Information Technology Dep. of Computer Systems Engineering Faculty of Computing Malabe10115 Sri Lanka Sri Lanka Institute of Information Technology Dep. of Software Engineering Faculty of Computing Malabe10115 Sri Lanka

ISBN: (纸本)9781728192550

Vision device is a critical component of fruit harvesting mobile robot which is designed for recognizing and harvesting of tomato fruits. The system of vision device of the moving robot, for a dedicated path identification with the use of colour detection algorithms and contour detection algorithms could be stated as an additional usage of the image-based technology. When the robot operates in real life, varying environmental parameters would not affect its activity, since the robot will be functioning mainly indoors, specifically in a greenhouse. Robust fruit segmentation algorithms for the visual system and the fruit plucking mechanism using a readymade robot arm with a soft gripper where it operates with basic hardware components like motors, controlled by a microcontroller with the intervention of kinematic theories, is being used with the goal of collecting fruit objects efficiently in the natural world. Plucking only the ripe and healthy object fruit without damaging both the fruit and the tree is the intended task of the system. The aim is to reduce human effort by promoting automation concepts in agriculture in developing countries like Sri Lanka with great potential, where agriculture plays a vital role in the development of the economy while indoor plantation and harvesting mechanism are also being developing to cater to the economy of the country as well. The way that this system is implemented will be discussed in this paper. © 2020 IEEE.

关键词： Fruits

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Analysis of Joint Channel Estimation and Joint Data Detection in TD-SCDMA systems

Analysis of Joint Channel Estimation and Joint Data Detectio...

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Asia-Pacific Conference on Communications

作者： Ali K. Marzook A. Ismail B. M. Ali A. Sali Mohannad H. Khalaf S. Khatun Department of Computer and Communication Systems Engineering Faculty of Engineering University Putra Malaysia Computer Engineering Department Basrah University Faculty of Computer Systems and Software Engineering University Malaysia Pahang

ISBN: (纸本)9781457703898

Time Division-Synchronous Code Division Multiple Access (TD-SCDMA) has several attractive characteristics that made it capable of meeting the requirements of G4 systems when applied as a platform directly. Joint detections, the unpaired spectrums with flexible sharing of resources, and some other advanced properties leads TD-SCDMA to achieve high data rate services. In this paper a comprehensive analysis is presented that involve accurate Joint Channel Estimation (JCE) for traditional and enhanced estimators based on two criterions: Least square (LS) & Minimum Mean Square Error (MMSE) at two scenarios of users' movements. In addition to a comprehensive Multi-Users Joint Detection (MUJD) is improved to mitigate Multiple Access Interference (MAI) and Inter-Symbol Interference (ISI) using the following detectors: Matched Filter (MF), Zero Forcing Block Linear Equalizer (ZF-BLE), and Minimum Mean Square Error Block Linear Equalizer (MMSE-BLE) for traditional and enhanced channel estimation criterions. Simulation results showed that equalizers fed by Channel Impulse Response (CIR) optimized according to enhanced LS or MMSE give a better performance to that ones when CIR obtained from traditional LS or MMSE criterion. The using of MMSE give the opportunity to implement adaptive equalizes to cope with fast fading and/or non stationary interference environments.

关键词： TD-SDMA system Joint channel estimation (JCE) Multi-users joint detection (MUJD)

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Leveraging Applications of Formal Methods, Verification, and Validation 1

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丛书名： Communications in computer and Information Science

1000年

作者： Reiner Hähnle Jens Knoop Tiziana Margaria Dietmar Schreiner Bernhard Steffen

ISBN: (数字)9783642347818

ISBN: (纸本)9783642347801

This volume contains a selection of revised papers that were presented at the software Aspects of Robotic systems, SARS 2011 Workshop and the Machine Learning for System Construction, MLSC 2011 Workshop, held during October 17-18 in Vienna, Austria, under the auspices of the International Symposium Series on Leveraging Applications of Formal Methods, Verification, and Validation, ISoLA. The topics covered by the papers of the SARS and the MLSC workshop demonstrate the breadth and the richness of the respective fields of the two workshops stretching from robot programming to languages and compilation techniques, to real-time and fault tolerance, to dependability, software architectures, computer vision, cognitive robotics, multi-robot-coordination, and simulation to bio-inspired algorithms, and from machine learning for anomaly detection, to model construction in software product lines to classification of web service interfaces. In addition the SARS workshop hosted a special session on the recently launched KOROS project on collaborating robot systems that is borne by a consortium of researchers of the faculties of architecture and planning, computer science, electrical engineering and information technology, and mechanical and industrial engineering at the Vienna University of Technology. The four papers devoted to this session highlight important research directions pursued in this interdisciplinary research project.

关键词： Artificial Intelligence Data Mining and Knowledge Discovery software engineering Computation by Abstract Devices Information Storage and Retrieval Pattern Recognition

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An Efficient Localization for Indoor Environment using Classification Algorithms

An Efficient Localization for Indoor Environment using Class...

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2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020

作者： Mulahuwaish, Aos Towne, Wyatt Ghafoor, Kayhan Zrar Maghdid, Halgurd S. Saginaw Valley State University Dept. of Computer Science and Information Systems Michigan United States Salahaddin University-Erbil Dep. of Software Engineering and Informatics Iraq Koya University Faculty of Engineering Dept. of Software Engineering Kurdistan Region-F.R. Iraq

ISBN: (纸本)9781728176246

The positioning accuracy of various kinds of devices is often calculated by using Wi-Fi fingerprints as a data source of Received Signal Strength (RSS). Through different matching algorithms, these RSS values are related to corresponding positioning coordinates for positioning estimation. In this paper, we compare two well known Machine Learning (ML) structures for calculating positioning accuracy: Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM) and a Decision Tree (DT). Both matching algorithms run through a series of datasets in two parts. In the first part, the datasets contain raw, non-normalized RSS values. In the second part, the RSS values are all normalized to remove noise in the datasets. After extensive testing and simulations, the tests showed that as long as RSS values are first normalized, a Decision Tree offers better average positioning accuracy. © 2020 IEEE.

关键词： Decision trees

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A Light Field Image Quality Assessment Method Based on Stereo Vision

A Light Field Image Quality Assessment Method Based on Stere...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Fu, Wei Shen, Xingfa Zhou, Wenhui Zhdanov, Andrei D. Geng, Chuntong Itmo Joint Institute Hangzhou Dianzi University Department of Computer Science Hangzhou China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Itmo University Faculty of Software Engineering and Computer Systems St.Petersburg Russia

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

Light field imaging is an important achievement in visual information exploration in recent years, which can capture more abundant visual information from the real world. However, most existing light field image quality assessment (LF-IQA) indicators rely heavily on feature extraction based on high complexity statistics in quality evaluation tasks, which is not comprehensive in future modern applications or power-limited devices. To solve this problem, the research puts forward a light field image quality evaluation method based on stereo vision. By introducing a brand-new light field image coding method and training the neural network, the purpose of image quality evaluation is finally achieved. Some experiments show that our model achieves good results in open source data sets. © 2022 IEEE.

关键词： Stereo vision

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DDoS Detection Using Active and Idle Features of Revised CICFlowMeter and Statistical Approaches 4

DDoS Detection Using Active and Idle Features of Revised CIC...

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4th International Conference on Advanced Science and engineering, ICOASE 2022

作者： Ali, Basheer Husham Sulaiman, Nasri Al-Haddad, S.A.R. Atan, Rodziah Hassan, Siti Lailatul Mohd Department of Electrical and Electronic Engineering Serdang Malaysia Faculty of Engineering Department of Electrical and Electronic Engineering Serdang Malaysia Department of Computer and Communication Systems Engineering Serdang Malaysia Software Eng. and Information Systems Dept Serdang Malaysia School of Electrical Engineering Universiti Teknologi Mara Shah Alam Malaysia

ISBN: (纸本)9781665472227

Distributed Denial of services (DDoS) attack is one of the most dangerous attacks that targeted servers. The main consequence of this attack is to prevent users from getting their legitimate services by bringing down targeted victim. CICFlowMeter tool generates bi-directional flows from packets. Each flow generates 83 of different features. The research focuses on 8 features which are active min (f1), active mean (f2), active max (f3), active std (f4), idle min (f5), idle mean (f6), idle max (f7), and idle std (f8). CICFlowMeter tool has several problems that affected on the detection accuracy of DDoS attacks. The idle and active based feature of Shannon entropy and sequential probability ratio test (SE-SPRT) approach was implemented in this research. The problems of original CICFlowMeter were presented, and the differences between original and revised version of CICFlowMeter tool were explored. The DARPA database and confusion matrix were used to evaluate the detection technique and present the comparison between two versions of CICFlowMeter. The detection method detected neptune and smurf attacks and had higher accuracy, f1-score, sensitivity, specificity, and precision when revised version of CICFlowMeter used to generate flows. However, the detection method failed to detect neptune attack and had higher miss-rate, lower accuracy, lower f1-score, and lower specificity, and lower precision when original version used in generating flows. © 2022 IEEE.

关键词： Denial-of-service attack

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A novelmethod to improve the retrieved multilingual documents score

A novelmethod to improve the retrieved multilingual document...

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2019 International Conference on computer, Control, Electrical, and Electronics engineering, ICCCEEE 2019

作者： Aboras, Abas Solyman, Aiman Abobieda, Albaraa Yousif, Hajer South China University of Technology School of Software Engineering Guangzhou China International University of Africa Faculty of Computer Studies Khartoum Sudan Sudan University of Science and Technology SUST Department of Computer Systems and Networks Khartoum Sudan

ISBN: (纸本)9781728110066

With an ever-increasing number of resources on the Web, different language resources such as newspapers, magazines, and articles have become available. This demands for an improved technique in the information retrieval to extirpate the communication barrier among languages. Search engines are the cornerstones for informational contents and the link between the two parties of publishing and retrieval of content. Moreover, the search for information is no longer narrowed to users of the native language of the original source. Most of the non-English users such as Arabic speakers are unable to express the terms in their own language. Also, the terminologies written in the native language of the source are acquired from the English language. This challenge drives users to use mixed terms (multilingual terms) to get better results, especially in the scientific domain. This paper attempts to address the problem of documents retrieval using multilingual queries. When users use mixed queries, the results of the multilingual documents will dominate the top of the retrieved documents rather than other relevant documents, and the scores of the mixed documents obtain extra weight values that are not really part of their actual weighting value. This paper proposes a novel method to improve the results of the retrieved documents by adjusting the score of multilingual documents. For experiments, we used a mixed test collection containing mixedlanguage documents (Arabic and English). The results showed that the proposed method led to an enhanced performance in documents retrieval from multilingual queries which made them relevant, effective and accurate thus proving that our approach is more reliable than other traditional approaches. © 2019 IEEE.

关键词： Information retrieval

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