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Orbit Weighting Scheme in the Context of Vector Space Information Retrieval

Computers, Materials & Continua 2024年第7期80卷 1347-1379页

作者： Ahmad Ababneh yousef sanjalawe Salam Fraihat Salam Al-E’mari Hamzah Alqudah Department of Computer Science Faculty of Information TechnologyAmerican University of MadabaAmman11821Jordan Department of Cybersecurity Faculty of Information TechnologyAmerican University of MadabaAmman11821Jordan Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityP.O.Box 346Ajman13306United Arab Emirates Information Security Department Faculty of Information TechnologyUniversity of PetraAmman11196Jordan Department of Data Science and Artificial Intelligence Faculty of Information TechnologyAmerican University of MadabaAmman11821Jordan

This study introduces the Orbit Weighting Scheme(OWS),a novel approach aimed at enhancing the precision and efficiency of Vector Space information retrieval(IR)models,which have traditionally relied on weighting schemes like tf-idf and *** conventional methods often struggle with accurately capturing document relevance,leading to inefficiencies in both retrieval performance and index size *** proposes a dynamic weighting mechanism that evaluates the significance of terms based on their orbital position within the vector space,emphasizing term relationships and distribution patterns overlooked by existing *** research focuses on evaluating OWS’s impact on model accuracy using Information Retrieval metrics like Recall,Precision,InterpolatedAverage Precision(IAP),andMeanAverage Precision(MAP).Additionally,we assessOWS’s effectiveness in reducing the inverted index size,crucial for model *** compare OWS-based retrieval models against others using different schemes,including tf-idf variations and *** reveal OWS’s superiority,achieving a 54%Recall and 81%MAP,and a notable 38%reduction in the inverted index *** highlights OWS’s potential in optimizing retrieval processes and underscores the need for further research in this underrepresented area to fully leverage OWS’s capabilities in information retrieval methodologies.

关键词： Information retrieval orbit weighting scheme semantic text analysis Tf-Idf weighting scheme vector space model

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Cloud Datacenter Selection Using Service Broker Policies:A Survey

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 1-41页

作者： Salam Al-E’mari yousef sanjalawe Ahmad Al-Daraiseh Mohammad Bany Taha Mohammad Aladaileh Department of Information Security Faculty of ITUniversity of PetraAmman11196Jordan Department of Cybersecurity School of ITAmerican University of Madaba(AUM)Amman11821Jordan Department of Computer Science School of ITAmerican University of Madaba(AUM)Amman11821Jordan Department of Data Science and Artificial Intelligence School of ITAmerican University of Madaba(AUM)Amman11821Jordan

Amid the landscape of Cloud Computing(CC),the Cloud Datacenter(DC)stands as a conglomerate of physical servers,whose performance can be hindered by bottlenecks within the realm of proliferating CC services.A linchpin in CC’s performance,the Cloud Service Broker(CSB),orchestrates DC *** to adroitly route user requests with suitable DCs transforms the CSB into a bottleneck,endangering service *** tackle this,deploying an efficient CSB policy becomes imperative,optimizing DC selection to meet stringent Qualityof-Service(QoS)*** numerous CSB policies,their implementation grapples with challenges like costs and *** article undertakes a holistic review of diverse CSB policies,concurrently surveying the predicaments confronted by current *** foremost objective is to pinpoint research gaps and remedies to invigorate future policy ***,it extensively clarifies various DC selection methodologies employed in CC,enriching practitioners and researchers *** synthetic analysis,the article systematically assesses and compares myriad DC selection *** analytical insights equip decision-makers with a pragmatic framework to discern the apt technique for their *** summation,this discourse resoundingly underscores the paramount importance of adept CSB policies in DC selection,highlighting the imperative role of efficient CSB policies in optimizing CC *** emphasizing the significance of these policies and their modeling implications,the article contributes to both the general modeling discourse and its practical applications in the CC domain.

关键词： Cloud computing cloud service broker datacenter selection quality-of-service user request

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DDoS Attack Detection in Cloud Computing Based on Ensemble Feature Selection and Deep Learning

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Computers, Materials & Continua 2023年第5期75卷 3571-3588页

作者： yousef sanjalawe Turke Althobaiti Cybersecurity Department Faculty of Information TechnologyAmerican University of Madaba(AUM)Amman11821Jordan Computer Science Department PY CollageNorthern Border University(NBU)9280 NBUAr’arSaudi Arabia Computer Science Department Faculty of ScienceNorthern Border University(NBU)9280 NBUAr’arSaudi Arabia Remote Sensing Northern Border University(NBU) 9280 NBUAr’arSaudi Arabia

Intrusion Detection System(IDS)in the cloud Computing(CC)environment has received paramount interest over the last few *** the latest approaches,Deep Learning(DL)-based IDS methods allow the discovery of attacks with the highest *** the CC environment,Distributed Denial of Service(DDoS)attacks are *** cloud services will be rendered unavailable to legitimate end-users as a consequence of the overwhelming network traffic,resulting in financial *** various researchers have proposed many detection techniques,there are possible obstacles in terms of detection performance due to the use of insignificant traffic ***,in this paper,a hybrid deep learning mode based on hybridizing Convolutional Neural Network(CNN)with Long-Short-Term Memory(LSTM)is used due to its robustness and efficiency in detecting normal and attack ***,the ensemble feature selection,mutualization aggregation between Particle Swarm Optimizer(PSO),Grey Wolf Optimizer(PSO),Krill Hird(KH),andWhale Optimization Algorithm(WOA),is used to select the most important features that would influence the detection performance in detecting DDoS attack in CC.A benchmark dataset proposed by the Canadian Institute of Cybersecurity(CIC),called CICIDS 2017 is used to evaluate the proposed *** results revealed that the proposed IDS outperforms the state-of-the-art IDSs,as it achieved 97.9%,98.3%,97.9%,98.1%,*** a result,the proposed IDS achieves the requirements of getting high security,automatic,efficient,and self-decision detection of DDoS attacks.

关键词： CIC IDS 2017 cloud computing distributed denial of service ensemble feature selection intrusion detection system

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Intrusion Detection Systems Using Blockchain Technology: A Review, Issues and Challenges

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Computer Systems Science & Engineering 2022年第1期40卷 87-112页

作者： Salam Al-E’mari Mohammed Anbar yousef sanjalawe Selvakumar Manickam Iznan Hasbullah National Advanced IPv6 Centre of Excellence(NAv6) Universiti Sains Malaysia11800 USMPenangMalaysia Computer Sciences Department Northern Border University(NBU)9280 NBUAr’arthe Kingdom of Saudi Arabia

Intrusion detection systems that have emerged in recent decades can identify a variety of malicious attacks that target networks by employing several detection ***,the current approaches have challenges in detecting intrusions,which may affect the performance of the overall detection system as well as network *** the time being,one of the most important creative technological advancements that plays a significant role in the professional world today is blockchain *** technology moves in the direction of persistent revolution and *** is a chain of blocks that covers information and maintains trust between individuals no matter how far apart they ***,blockchain was integrated into intrusion detection systems to enhance their overall *** has also been adopted in health-care,supply chain management,and the Internet of *** uses robust cryptography with private and public keys,and it has numerous properties that have leveraged security’s performance over peer-to-peer networks without the need for a third *** explore and highlight the importance of integrating blockchain with intrusion detection systems,this paper provides a comprehensive background of intrusion detection systems and blockchain ***,a comprehensive review of emerging intrusion detection systems based on blockchain technology is ***,this paper suggests important future research directions and trending topics in intrusion detection systems based on blockchain technology.

关键词： Blockchain intrusiondetectionsystem networksecurity maliciousattacks

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Cloud Data Center Selection Using a Modified Differential Evolution

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Computers, Materials & Continua 2021年第12期69卷 3179-3204页

作者： yousef sanjalawe Mohammed Anbar Salam Al-E’mari Rosni Abdullah Iznan Hasbullah Mohammed Aladaileh National Advanced IPv6 Center(NAv6) Universiti Sains Malaysia11800 USMPenangMalaysia Computer Science Department PY CollageNorthern Border University(NBU)9280 NBUAr’arKingdom of Saudi Arabia

The interest in selecting an appropriate cloud data center is exponentially increasing due to the popularity and continuous growth of the cloud computing *** data center selection challenges are compounded by ever-increasing users’requests and the number of data centers required to execute these *** service broker policy defines cloud data center’s selection,which is a case of an NP-hard problem that needs a precise solution for an efficient and superior *** evolution algorithm is a metaheuristic algorithm characterized by its speed and robustness,and it is well suited for selecting an appropriate cloud data *** paper presents a modified differential evolution algorithm-based cloud service broker policy for the most appropriate data center selection in the cloud computing *** differential evolution algorithm is modified using the proposed new mutation technique ensuring enhanced performance and providing an appropriate selection of data *** proposed policy’s superiority in selecting the most suitable data center is evaluated using the CloudAnalyst *** results are compared with the state-of-arts cloud service broker policies.

关键词： Cloud computing data center data center selection cloud service broker differential evolution user request

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Entropy-Based Approach to Detect DDoS Attacks on Software Defined Networking Controller

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Computers, Materials & Continua 2021年第10期69卷 373-391页

作者： Mohammad Aladaileh Mohammed Anbar Iznan H.Hasbullah yousef K.sanjalawe Yung-Wey Chong National Advanced IPv6 Centre of Excellence Universiti Sains MalaysiaPenangMalaysia Department of Computer Sciences Northern Border UniversityAr’arKingdom of Saudi Arabia

The Software-Defined Networking(SDN)technology improves network management over existing technology via centralized network *** SDN provides a perfect platform for researchers to solve traditional network’s outstanding ***,despite the advantages of centralized control,concern about its security is *** more traditional network switched to SDN technology,the more attractive it becomes to malicious actors,especially the controller,because it is the network’s brain.A Distributed Denial of Service(DDoS)attack on the controller could cripple the entire *** that reason,researchers are always looking for ways to detect DDoS attacks against the controller with higher accuracy and lower false-positive *** paper proposes an entropy-based approach to detect low-rate and high-rate DDoS attacks against the SDN controller,regardless of the number of attackers or *** proposed approach generalized the Rényi joint entropy for analyzing the network traffic flow to detect DDoS attack traffic flow of varying *** two packet header features and generalized Rényi joint entropy,the proposed approach achieved a better detection rate than the EDDSC approach that uses Shannon entropy metrics.

关键词： Software-defined networking DDoS attack distributed denial of service Rényi joint entropy

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Securing Cloud Computing from Flash Crowd Attack Using Ensemble Intrusion Detection System

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Computer Systems Science & Engineering 2023年第10期47卷 453-469页

作者： Turke Althobaiti yousef sanjalawe Naeem Ramzan Department of Computer Science Faculty of ScienceNorthern Border University(NBU)Arar73222Saudi Arabia Remote Sensing Unit Northern Border University(NBU)Arar73222Saudi Arabia Deparment of Cybersecurity American University of Madaba(AUM)Amman11821Jordan School of Engineering and Computing University of West of ScotlandPaisleyPA12BEUK

Flash Crowd attacks are a form of Distributed Denial of Service(DDoS)attack that is becoming increasingly difficult to detect due to its ability to imitate normal user behavior in Cloud Computing(CC).Botnets are often used by attackers to perform a wide range of DDoS *** advancements in technology,bots are now able to simulate DDoS attacks as flash crowd events,making them difficult to *** it comes to application layer DDoS attacks,the Flash Crowd attack that occurs during a Flash Event is viewed as the most intricate *** is mainly because it can imitate typical user behavior,leading to a substantial influx of requests that can overwhelm the server by consuming either its network bandwidth or ***,identifying these types of attacks on web servers has become crucial,particularly in the *** this article,an efficient intrusion detection method is proposed based on White Shark Optimizer and ensemble classifier(Convolutional Neural Network(CNN)and LighGBM).Experiments were conducted using a CICIDS 2017 dataset to evaluate the performance of the proposed method in real-life *** proposed IDS achieved superior results,with 95.84%accuracy,96.15%precision,95.54%recall,and 95.84%F1 *** crowd attacks are challenging to detect,but the proposed IDS has proven its effectiveness in identifying such attacks in CC and holds potential for future improvement.

关键词： Cloud computing CNN flash crowd attack intrusion detection system LightGBM White Shark Optimizer

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