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Malware Detection Using Dual Siamese Network Model

Computer Modeling in Engineering & Sciences 2024年第10期141卷 563-584页

作者： ByeongYeol An JeaHyuk Yang Seoyeon Kim Taeguen Kim department of Software convergence Soonchunhyang UniversityAsan31538Republic of Korea department of Mobility convergence security Soonchunhyang UniversityAsan31538Republic of Korea department of information security Engineering Soonchunhyang UniversityAsan31538Republic of Korea

This paper proposes a new approach to counter cyberattacks using the increasingly diverse malware in cyber *** signature detection methods that utilize static and dynamic features face limitations due to the continuous evolution and diversity of new ***,machine learning-based malware detection techniques,such as Convolutional Neural Networks(CNN)and Recurrent Neural Networks(RNN),have gained *** these methods demonstrate high performance by leveraging static and dynamic features,they are limited in detecting new malware or variants because they learn based on the characteristics of existing *** overcome these limitations,malware detection techniques employing One-Shot Learning and Few-Shot Learning have been *** on this,the Siamese Network,which can effectively learn from a small number of samples and perform predictions based on similarity rather than learning the characteristics of the input data,enables the detection of new malware or *** propose a dual Siamese network-based detection framework that utilizes byte images converted frommalware binary data to grayscale,and opcode frequency-based images generated after extracting opcodes and converting them into *** proposed framework integrates two independent Siamese network models,one learning from byte images and the other from opcode frequency-based *** detection models trained on the different kinds of images generated separately apply the L1 distancemeasure to the output vectors themodels generate,calculate the similarity,and then apply different weights to each *** proposed framework achieved a malware detection accuracy of 95.9%and 99.83%in the experimentsusingdifferentmalware *** experimental resultsdemonstrate that ourmalware detection model can effectively detect malware by utilizing two different types of features and employing the dual Siamese network-based model.

关键词： Siamese network malware detection few-shot learning

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Suboptimal Feature Selection Techniques for Effective Malicious Traffic Detection on Lightweight Devices

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1669-1687页

作者： So-Eun Jeon Ye-Sol Oh Yeon-Ji Lee Il-Gu Lee department of Future convergence Technology Engineering Sungshin Women’s UniversitySeoul02844Korea department of convergence security Engineering SungshinWomen’s UniversitySeoul02844Korea

With the advancement of wireless network technology,vast amounts of traffic have been generated,and malicious traffic attacks that threaten the network environment are becoming increasingly *** signature-based detection methods,static analysis,and dynamic analysis techniques have been previously explored for malicious traffic detection,they have limitations in identifying diversified malware traffic *** research has been focused on the application of machine learning to detect these ***,applying machine learning to lightweight devices like IoT devices is challenging because of the high computational demands and complexity involved in the learning *** this study,we examined methods for effectively utilizing machine learning-based malicious traffic detection approaches for lightweight *** introduced the suboptimal feature selection model(SFSM),a feature selection technique designed to reduce complexity while maintaining the effectiveness of malicious traffic *** performance was evaluated on various malicious traffic,benign,exploits,and generic,using the UNSW-NB15 dataset and SFSM sub-optimized hyperparameters for feature selection and narrowed the search scope to encompass all *** improved learning performance while minimizing complexity by considering feature selection and exhaustive search as two steps,a problem not considered in conventional *** experimental results showed that the detection accuracy was improved by approximately 20%compared to the random model,and the reduction in accuracy compared to the greedy model,which performs an exhaustive search on all features,was kept within 6%.Additionally,latency and complexity were reduced by approximately 96%and 99.78%,respectively,compared to the greedy *** study demonstrates that malicious traffic can be effectively detected even in lightweight device *** verified the possibility of detecting various attack

关键词： Feature selection lightweight device machine learning Internet of Things malicious traffic

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Ag-integrated mixed metallic Co-Fe-Ni-Mn hydroxide composite as advanced electrode for high-performance hybrid supercapacitors

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Journal of Energy Chemistry 2024年第1期88卷 579-591,I0013页

作者： Anki Reddy Mule Bhimanaboina Ramulu Shaik Junied Arbaz Anand Kurakula Jae Su Yu department of Electronics and information convergence Engineering Institute for Wearable Convergence ElectronicsKyung Hee UniversityYongin-siGyeonggi-do 17104Republic of Korea

Direct growth of redox-active noble metals and rational design of multifunctional electrochemical active materials play crucial roles in developing novel electrode materials for energy storage *** this regard,silver(Ag)has attracted great attention in the design of efficient *** by the house/building process,which means electing the right land,it lays a strong foundation and building essential columns for a complex ***,we report the construction of multifaceted heterostructure cobalt-iron hydroxide(CFOH)nanowires(NWs)@nickel cobalt manganese hydroxides and/or hydrate(NCMOH)nanosheets(NSs)on the Ag-deposited nickel foam and carbon cloth(i.e.,Ag/NF and Ag/CC)***,the formation and charge storage mechanism of Ag are described,and these contribute to good conductive and redox chemistry *** switching architectural integrity of metal and redox materials on metallic frames may significantly boost charge storage and rate performance with noticeable drop in *** as-fabricated Ag@CFOH@NCMOH/NF electrode delivered superior areal capacity value of 2081.9μA h cm^(-2)at 5 mA cm^(-2).Moreover,as-assembled hybrid cell based on NF(HC/NF)device exhibited remarkable areal capacity value of 1.82 mA h cm^(-2)at 5 mA cm^(-2)with excellent rate capability of 74.77%even at 70 mA cm^(-2)Furthermore,HC/NF device achieved maximum energy and power densities of 1.39 mW h cm^(-2)and 42.35 mW cm^(-2),*** verify practical applicability,both devices were also tested to serve as a self-charging station for various portable electronic devices.

关键词： Current collectors Redox-active silver Transition metal-hydroxides Electrochemical performance Hybrid supercapacitor

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Anomaly Detection in Imbalanced Encrypted Traffic with Few Packet Metadata-Based Feature Extraction

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 585-607页

作者： Min-Gyu Kim Hwankuk Kim department of Financial information security Kookmin UniversitySeoul02707Republic of Korea department of information security Cryptography Mathematics Kookmin UniversitySeoul02707Republic of Korea

In the IoT(Internet of Things)domain,the increased use of encryption protocols such as SSL/TLS,VPN(Virtual Private Network),and Tor has led to a rise in attacks leveraging encrypted *** research on anomaly detection using AI(Artificial Intelligence)is actively progressing,the encrypted nature of the data poses challenges for labeling,resulting in data imbalance and biased feature extraction toward specific *** study proposes a reconstruction error-based anomaly detection method using an autoencoder(AE)that utilizes packet metadata excluding specific node *** proposed method omits biased packet metadata such as IP and Port and trains the detection model using only normal data,leveraging a small amount of packet *** makes it well-suited for direct application in IoT environments due to its low resource *** experiments comparing feature extraction methods for AE-based anomaly detection,we found that using flowbased features significantly improves accuracy,precision,F1 score,and AUC(Area Under the Receiver Operating Characteristic Curve)score compared to packet-based ***,for flow-based features,the proposed method showed a 30.17%increase in F1 score and improved false positive rates compared to Isolation Forest and ***,the proposedmethod demonstrated a 32.43%higherAUCwhen using packet features and a 111.39%higher AUC when using flow features,compared to previously proposed oversampling *** study highlights the impact of feature extraction methods on attack detection in imbalanced,encrypted traffic environments and emphasizes that the one-class method using AE is more effective for attack detection and reducing false positives compared to traditional oversampling methods.

关键词： One-class anomaly detection feature extraction auto-encoder encrypted traffic CICIoT2023

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A Novel Framework to Construct S-Box Quantum Circuits Using System Modeling: Application to 4-Bit S-Boxes

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 545-561页

作者： Yongjin Jeon Seungjun Baek Jongsung Kim department of Financial information security Kookmin UniversitySeoul02707Republic of Korea

Quantum computers accelerate many algorithms based on the superposition principle of quantum *** Grover algorithm provides significant performance to malicious users attacking symmetric key *** the performance of attacks using quantum computers depends on the efficiency of the quantum circuit of the encryption algorithms,research research on the implementation of quantum circuits is *** paper presents a new framework to construct quantum circuits of substitution boxes(S-boxes)using system *** model the quantum circuits of S-boxes using two layers:Toffoli and linear *** generate vector spaces based on the values of qubits used in the linear layers and apply them to find quantum *** framework finds the circuit bymatching elements of vector spaces generated fromthe input and output of a given S-box,using the forward search or themeet-in-the-middle *** developed a tool to apply this framework to 4-bit *** the 4-bit S-box quantum circuit construction tool LIGHTER-R only finds circuits that can be implemented with four qubits,the proposed tool achieves the circuits with five *** proposed tool can find quantum circuits of 4-bit odd permutations based on the controlled NOT,NOT,and Toffoli gates,whereas LIGHTER-R is unable to perform this task in the same *** expect this technique to become a critical step toward optimizing S-box quantum circuits.

关键词： System modeling quantum circuit S-box circuit quantum computer

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Dragonfly Interaction Algorithm for Optimization of Queuing Delay in Industrial Wireless Networks

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Journal of Bionic Engineering 2024年第1期21卷 447-485页

作者： Sanjay Bhardwaj Da-Hye Kim Dong-Seong Kim department of IT convergence Engineering ICT Convergence Research CenterKumoh National Institute of TechnologyGumiSouth Korea

In industrial wireless networks,data transmitted from source to destination are highly *** often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increased energy consumption,and packet ***,a nature-inspired-based Dragonfly Interaction Optimization Algorithm(DMOA)is proposed for optimization of the queue delay in industrial wireless *** term“interaction”herein used is the characterization of the“flying movement”of the dragonfly towards damselflies(female dragonflies)for *** a result,interaction is represented as the flow of transmitted data packets,or traffic,from the source to the base *** includes each and every feature of dragonfly movement as well as awareness of the rival dragonflies,predators,and damselflies for the desired optimization of the queue *** features are juxtaposed as noise and interference,which are further used in the calculation of industrial wireless metrics:latency,error rate(reliability),throughput,energy efficiency,and fairness for the optimization of the queue *** analysis,convergence analysis,the Wilcoxon test,the Friedman test,and the classical as well as the 2014 IEEE Congress of Evolutionary Computation(CEC)on the benchmark functions are also used for the evaluation of DMOA in terms of its robustness and *** results demonstrate the robustness of the proposed algorithm for both classical and benchmarking functions of the IEEE CEC ***,the accuracy and efficacy of DMOA were demonstrated by means of the convergence rate,Wilcoxon testing,and ***,fairness using Jain’s index in queue delay optimization in terms of throughput and latency,along with computational complexity,is also evaluated and compared with other *** results show that DMOA exceeds other bio-inspired optimization algorithms in terms of fairness in queue delay management and average packet *** proposed a

关键词： Dragonfly Damselfly Interaction Queuing delay Optimization Industrial wireless networks

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A Comprehensive Survey on Federated Learning in the Healthcare Area: Concept and Applications

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2239-2274页

作者： Deepak Upreti Eunmok Yang Hyunil Kim Changho Seo department of convergence Science Kongju National UniversityChungcheongnam-doGongju-si32588South Korea department of information security Cryptologyand MathematicsKookmin UniversitySeoul02707South Korea department of information and Communication Engineering Chosun UniversityGwangju61452South Korea Basic Science Research Institution Kongju National UniversityChungcheongnam-doGongju-si32588South Korea

Federated learning is an innovative machine learning technique that deals with centralized data storage issues while maintaining privacy and *** involves constructing machine learning models using datasets spread across several data centers,including medical facilities,clinical research facilities,Internet of Things devices,and even mobile *** main goal of federated learning is to improve robust models that benefit from the collective knowledge of these disparate datasets without centralizing sensitive information,reducing the risk of data loss,privacy breaches,or data *** application of federated learning in the healthcare industry holds significant promise due to the wealth of data generated from various sources,such as patient records,medical imaging,wearable devices,and clinical research *** research conducts a systematic evaluation and highlights essential issues for the selection and implementation of federated learning approaches in *** evaluates the effectiveness of federated learning strategies in the field of *** offers a systematic analysis of federated learning in the healthcare domain,encompassing the evaluation metrics *** addition,this study highlights the increasing interest in federated learning applications in healthcare among scholars and provides foundations for further studies.

关键词： Federated learning artificial intelligence machine learning privacy healthcare

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Air-stable,all-dry transferred ReS_(2)/GaSe heterostructure-based NO_(2)gas sensor

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Journal of Materials Science & Technology 2024年第1期168卷 79-87页

作者： A.Venkatesan Hyeyoon Ryu Anupom Devnath Hyungyu Yoo Seunghyun Lee department of Electronic Engineering Kyung Hee UniversityYongin-Si 17104South Korea department of Electronics and information convergence Engineering Kyung Hee UniversityYongin-Si 17104South Korea

Two-dimensional(2D)materials have gained considerable attention in chemical sensing owing to their naturally high surface-to-volume ***,the poor response time and incomplete recovery re-strict their application in practical,high performance gas *** this work,we fabricated air-stable ReS_(2)/GaSe heterostructure-based NO_(2)gas sensors with excellent gas sensing response,recovery,selectiv-ity and a low limit of detection(LOD)toward nitrogen dioxide(NO_(2)).The ReS_(2)/GaSe heterostructure was prepared via mechanical exfoliation and an all-dry transfer *** the sensing measurements,temperature-dependant transport measurements were carried *** Schottky Barrier Height(SBH)of the ReS_(2)/GaSe heterostructure was calculated and the corresponding transport mechanisms were *** fabricated gas sensors showed a significant response enhancement with full reversibility to-ward ppm-level NO_(2)(response of∼17%at 3 ppm,a LOD of∼556 ppb)at an operating temperature of(33°C).In particular,the total response and recovery time of the ReS_(2)/GaSe was revealed to be less than 4 min(∼38 s and∼174 s,respectively)for the 250 ppm concentration,which is one of the best response and recovery time toward ppm-level NO_(2).The excellent sensing performances and recovery characteris-tics of the ReS_(2)/GaSe structure are attributed to its efficient charge separation,unique interlayer coupling and desirable band *** atomically thin,ultrasensitive gas sensor that operates at room tem-perature is a strong technological contender to conventional metal oxide gas sensors,which often require elevated temperatures.

关键词： 2D materials All-dry transfer Gas sensor Van der Waals heterostructure ReS_(2)/GaSe Gas sensing response Transition metal dichalcogenide

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A New Framework for Software Vulnerability Detection Based on an Advanced Computing

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Computers, Materials & Continua 2024年第6期79卷 3699-3723页

作者： Bui Van Cong Cho Do Xuan department of information Technology University of Economics and Technical IndustriesHanoi100000Vietnam Faculty of information security Posts and Telecommunications Institute of TechnologyHanoi100000Vietnam

The detection of software vulnerabilities written in C and C++languages takes a lot of attention and interest *** paper proposes a new framework called DrCSE to improve software vulnerability *** uses an intelligent computation technique based on the combination of two methods:Rebalancing data and representation learning to analyze and evaluate the code property graph(CPG)of the source code for detecting abnormal behavior of software *** do that,DrCSE performs a combination of 3 main processing techniques:(i)building the source code feature profiles,(ii)rebalancing data,and(iii)contrastive *** which,the method(i)extracts the source code’s features based on the vertices and edges of the *** method of rebalancing data has the function of supporting the training process by balancing the experimental ***,contrastive learning techniques learn the important features of the source code by finding and pulling similar ones together while pushing the outliers *** experiment part of this paper demonstrates the superiority of the DrCSE Framework for detecting source code security vulnerabilities using the Verum *** a result,the method proposed in the article has brought a pretty good performance in all metrics,especially the Precision and Recall scores of 39.35%and 69.07%,respectively,proving the efficiency of the DrCSE *** performs better than other approaches,with a 5%boost in Precision and a 5%boost in ***,this is considered the best research result for the software vulnerability detection problem using the Verum dataset according to our survey to date.

关键词： Source code vulnerability source code vulnerability detection code property graph feature profile contrastive learning data rebalancing

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MV-Honeypot:security Threat Analysis by Deploying Avatar as a Honeypot in COTS Metaverse Platforms

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 655-669页

作者： Arpita Dinesh Sarang Mohsen Ali Alawami Ki-Woong Park SysCore Lab.(convergence Engineering for Intelligent Drone) Sejong UniversitySeoul05006Republic of Korea Division of Computer Engineering Hankuk University of Foreign StudiesYongin-si17035Republic of Korea department of information security Sejong UniversitySeoul05006Republic of Korea

Nowadays,theuse of Avatars that are unique digital depictions has increased by users to access Metaverse—a virtual reality environment—through multiple devices and for various ***,the Avatar and Metaverse are being developed with a new theory,application,and design,necessitating the association of more personal data and devices of targeted users every *** Avatar and Metaverse technology explosion raises privacy and security concerns,leading to cyber ***-Honeypot,or Metaverse-Honeypot,as a commercial off-the-shelf solution that can counter these cyber attack-causing vulnerabilities,should be *** fill this gap,we study user’s engagements with Avatars in Metaverse,analyze possible security vulnerabilities,and create a model named Simplified Avatar Relationship Association with Non-linear Gradient(SARANG)that draws the full diagram of infrastructure components and data flow through accessing Metaverse in this *** also determine the most significant threat for each component’s cyberattacks that will affect user data and *** a result,the commercial off-the-shelf(COTS)of the MV-Honeypot must be established.

关键词： Avatar metaverse cybersecurity cloud computing internet of things artificial intelligence security analysis

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