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3-multi ranked encryption with enhanced security in cloud computing

Digital Communications and Networks 2023年第2期9卷 313-326页

作者： YeEun Kim Junggab Son reza m.parizi Gautam Srivastava Heekuck Oh major in Bio Artificial Intelligence Dept.of Computer Science and EngineeringHanyang UniversityAnsanRepublic of Korea Department of Computer Science Kennesaw State UniversityMariettaUSA Department of Software Engineering Kennesaw State UniversityMariettaUSA Department of mathematics and Computer Science Brandon UniversityBrandonCanada Research Center for Interneural Computing China Medical UniversityTaichungTaiwanChina Dept.of Computer Science and Engineering Hanyang UniversityAnsanRepublic of Korea

Searchable Encryption(SE)enables data owners to search remotely stored ciphertexts selectively.A practical model that is closest to real life should be able to handle search queries with multiple keywords and multiple data owners/users,and even return the top-k most relevant search results when *** refer to a model that satisfies all of the conditions a 3-multi ranked search ***,SE schemes that have been proposed to date use fully trusted trapdoor generation centers,and several methods assume a secure connection between the data users and a trapdoor generation *** is,they assume the trapdoor generation center is the only entity that can learn the information regarding queried keywords,but it will never attempt to use it in any other manner than that requested,which is impractical in real *** this study,to enhance the security,we propose a new 3-multi ranked SE scheme that satisfies all conditions without these security *** proposed scheme uses randomized keywords to protect the interested keywords of users from both outside adversaries and the honest-but-curious trapdoor generation center,thereby preventing attackers from determining whether two different queries include the same ***,we develop a method for managing multiple encrypted keywords from every data owner,each encrypted with a different *** evaluation demonstrates that,despite the trade-off overhead that results from the weaker security assumption,the proposed scheme achieves reasonable performance compared to extant schemes,which implies that our scheme is practical and closest to real life.

关键词： Searchable encryption multi-keyword search multiple data owners/users Ranked search Enhanced security

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An ensemble deep learning model for cyber threat hunting in industrial internet of things

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Digital Communications and Networks 2023年第1期9卷 101-110页

作者： Abbas Yazdinejad mostafa Kazemi reza m.parizi Ali Dehghantanha Hadis Karimipour Cyber Science Lab School of Computer ScienceUniversity of GuelphOntarioCanada Department of Electrical Engineering Faculty of EngineeringShahed UniversityTehranIran College of Computing and Software Engineering Kennesaw State UniversityGAUSA School of Engineering University of GuelphOntarioCanada

By the emergence of the fourth industrial revolution,interconnected devices and sensors generate large-scale,dynamic,and inharmonious data in Industrial Internet of Things(IIoT)*** vast heterogeneous data increase the challenges of security risks and data analysis *** IIoT grows,cyber-attacks become more diverse and complex,making existing anomaly detection models less effective to *** this paper,an ensemble deep learning model that uses the benefits of the Long Short-Term memory(LSTm)and the AutoEncoder(AE)architecture to identify out-of-norm activities for cyber threat hunting in IIoT is *** this model,the LSTm is applied to create a model on normal time series of data(past and present data)to learn normal data patterns and the important features of data are identified by AE to reduce data *** addition,the imbalanced nature of IIoT datasets has not been considered in most of the previous literature,affecting low accuracy and *** solve this problem,the proposed model extracts new balanced data from the imbalanced datasets,and these new balanced data are fed into the deep LSTm AE anomaly detection *** this paper,the proposed model is evaluated on two real IIoT datasets-Gas Pipeline(GP)and Secure Water Treatment(SWaT)that are imbalanced and consist of long-term and short-term dependency on *** results are compared with conventional machine learning classifiers,Random Forest(RF),multi-Layer Perceptron(mLP),Decision Tree(DT),and Super Vector machines(SVm),in which higher performance in terms of accuracy is obtained,99.3%and 99.7%based on GP and SWaT datasets,***,the proposed ensemble model is compared with advanced related models,including Stacked Auto-Encoders(SAE),Naive Bayes(NB),Projective Adaptive Resonance Theory(PART),Convolutional Auto-Encoder(C-AE),and Package Signatures(PS)based LSTm(PS-LSTm)model.

关键词： Internet of things IIoT Anomaly detection Ensemble deep learning Neural networks LSTm

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Accurate threat hunting in industrial internet of things edge devices

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Digital Communications and Networks 2023年第5期9卷 1123-1130页

作者： Abbas Yazdinejad Behrouz Zolfaghari Ali Dehghantanha Hadis Karimipour Gautam Srivastava reza m.parizi Cyber Science Lab School of Computer ScienceUniversity of GuelphOntarioCanada Department of Electrical and Software Engineering University of CalgaryAlbertaCanada Department of mathematics and Computer Science Brandon UniversityBrandonCanada College of Computing and Software Engineering Kennesaw State UniversityGAUSA Research Center for Interneural Computing China Medical UniversityTaichungTaiwanChina Department of Computer Science and mathematics Lebanese American UniversityBeirut1102Lebanon

Industrial Internet of Things(IIoT)systems depend on a growing number of edge devices such as sensors,controllers,and robots for data collection,transmission,storage,and *** kind of malicious or abnormal function by each of these devices can jeopardize the security of the entire ***,they can allow malicious software installed on end nodes to penetrate the *** paper presents a parallel ensemble model for threat hunting based on anomalies in the behavior of IIoT edge *** proposed model is flexible enough to use several state-of-the-art classifiers as the basic learner and efficiently classifies multi-class anomalies using the multi-class AdaBoost and majority *** evaluations using a dataset consisting of multi-source normal records and multi-class anomalies demonstrate that our model outperforms existing approaches in terms of accuracy,F1 score,recall,and precision.

关键词： IIoT Threat hunting Edge devices multi-class anomalies Ensemble methods

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Software Defect Prediction Harnessing on multi 1-Dimensional Convolutional Neural Network Structure

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Computers, materials & Continua 2022年第4期71卷 1521-1546页

作者： Zuhaira muhammad Zain Sapiah Sakri Nurul Halimatul Asmak Ismail reza m.parizi Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Computer Science and Information Technology College of CommunityPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia College of Computing and Software Engineering Kennesaw State UniversityMariettaGA30060USA

Developing successful software with no defects is one of the main goals of software *** order to provide a software project with the anticipated software quality,the prediction of software defects plays a vital *** learning,and particularly deep learning,have been advocated for predicting software defects,however both suffer from inadequate accuracy,overfitting,and complicated *** this paper,we aim to address such issues in predicting software *** propose a novel structure of 1-Dimensional Convolutional Neural Network(1D-CNN),a deep learning architecture to extract useful knowledge,identifying and modelling the knowledge in the data sequence,reduce overfitting,and finally,predict whether the units of code are defects *** design large-scale empirical studies to reveal the proposed model’s effectiveness by comparing four established traditional machine learning baseline models and four state-of-the-art baselines in software defect prediction based on the NASA *** experimental results demonstrate that in terms of f-measure,an optimal and modest 1DCNN with a dropout layer outperforms baseline and state-of-the-art models by 66.79%and 23.88%,respectively,in ways that minimize overfitting and improving prediction performance for software *** to the results,1D-CNN seems to be successful in predicting software defects and may be applied and adopted for a practical problem in software ***,in turn,could lead to saving software development resources and producing more reliable software.

关键词： Defects software defect prediction deep learning convolutional neural network machine learning

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BlockHDFS:Blockchain-integrated Hadoop distributed file system for secure provenance traceability

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Blockchain(Research and Applications) 2021年第4期2卷 30-36页

作者： Viraaji mothukuri Sai S.Cheerla reza m.parizi Qi Zhang Kim-Kwang Raymond Choo College of Computing and Software Engineering Kennesaw State UniversityKennesawGA30144USA IBm Thomas J.Research Center Yorktown HeightsNY10598USA Department of Information Systems and Cyber Security University of Texas at San AntonioSan AntonioTX78249USA

Hadoop Distributed File System(HDFS)is one of the widely used distributed file systems in big data analysis for frameworks such as *** allows one to manage large volumes of data using low-cost commodity ***,vulnerabilities in HDFS can be exploited for nefarious *** reinforces the importance of ensuring robust security to facilitate file sharing in Hadoop as well as having a trusted mechanism to check the authenticity of shared *** is the focus of this paper,where we aim to improve the security of HDFS using a blockchain-enabled approach(hereafter referred to as BlockHDFS).Specifically,the proposed BlockHDFS uses the enterprise-level Hyperledger Fabric platform to capitalize on files'metadata for building trusted data security and traceability in HDFS.

关键词： Big data Hadoop Blockchain Hyperledger fabric Hadoop distributed file system(HDFS) Traceability Security Privacy

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A systematic literature review of blockchain cyber security

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Digital Communications and Networks 2020年第2期6卷 147-156页

作者： Paul J.Taylor Tooska Dargahi Ali Dehghantanha reza m.parizi Kim-Kwang Raymond Choo School of Computing Science&EngineeringUniversity of SalfordManchesterUK Cyber Science Lab School of Computer ScienceUniversity of GuelphOntarioCanada Department of Software Engineering and Game Development Kennesaw State UniversityMariettaGA30060USA Department of Information Systems and Cyber Security University of Texas at San AntonioSan AntonioTX78249USA

Since the publication of Satoshi Nakamoto's white paper on Bitcoin in 2008,blockchain has(slowly)become one of the most frequently discussed methods for securing data storage and transfer through decentralized,trustless,peer-to-peer *** research identifies peer-reviewed literature that seeks to utilize blockchain for cyber security purposes and presents a systematic analysis of the most frequently adopted blockchain security *** findings show that the Internet of Things(IoT)lends itself well to novel blockchain applications,as do networks and machine visualization,public-key cryptography,web applications,certification schemes and the secure storage of Personally Identifiable Information(PII).This timely systematic review also sheds light on future directions of research,education and practices in the blockchain and cyber security space,such as security of blockchain in IoT,security of blockchain for AI data,and sidechain security.

关键词： Blockchain Smart contracts Cyber security Distributed ledger technology IoT Cryptocurrency Bitcoin

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Cancer cell cycle heterogeneity as a critical determinant of therapeutic resistance

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Genes & Diseases 2024年第1期11卷 189-204页

作者： Ebrahim H.maleki Ahmad reza Bahrami maryam m.matin Department of Biology Faculty of ScienceFerdowsi University of Mashhad*** MashhadIran Jagiellonian Centre for Experimental Therapeutics(JCET) Jagiellonian University31-007 KrakowPoland Doctoral School of Exact and Natural Sciences Jagiellonian University30-348 KrakowPoland Industrial Biotechnology Research Group Institute of BiotechnologyFerdowsi University of Mashhad*** MashhadIran Novel Diagnostics and Therapeutics Research Group Institute of BiotechnologyFerdowsi University of Mashhad***MashhadIran Stem Cell and Regenerative medicine Research Group Iranian Academic Center for EducationCulture and Research(ACECR)Khorasan Razavi Branch917751376 MashhadIran

Intra-tumor heterogeneity is now arguably one of the most-studied topics in tumor biology,as it represents a major obstacle to effective cancer *** tumor cells are highly diverse at genetic,epigenetic,and phenotypic levels,intra-tumor heterogeneity can be assumed as an important contributing factor to the nullification of chemotherapeutic effects,and recurrence of the *** on the role of heterogeneous subpopulations of cancer cells with varying cell-cycle dynamics and behavior during cancer progression and treatment;herein,we aim to establish a comprehensive definition for adaptation of neoplastic cells against *** discuss two parallel and yet distinct subpopulations of tumor cells that play pivotal roles in reducing the effects of chemotherapy:"resistant"and"tolerant"***,this review also highlights the impact of the quiescent phase of the cell cycle as a survival mechanism for cancer *** understanding the mechanisms under-lying the quiescence,it provides an insightful perspective on cancer stem cells(CsCs)and their dual and intertwined functions based on their cell cycle state in response to ***-over,CSCs,epithelial-mesenchymal transformed cells,circulating tumor cells(CTCs),and disseminated tumor cells(DTCs),which are mostly in a quiescent state of the cell cycle are proved to have multiple biological links and can be implicated in our viewpoint of cell cycle heterogeneity in ***,increasing our knowledge of cell cycle heterogeneity is a key to identifying new therapeutic solutions,and this emerging concept may provide us with new opportunities to prevent the dreadful cancer recurrence.

关键词： Cancer stem cells(CSCs) Carcinoma Cell cycle heterogeneity Quiescence Therapy resistance Therapy tolerance Tumor dormancy

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AGGREGATE SPECIAL FUNCTIONS TO APPROXImATE PERmUTING TRI-HOmOmORPHISmS AND PERmUTING TRI-DERIVATIONS ASSOCIATED WITH A TRI-ADDITIVEψ-FUNCTIONAL INEQUALITY IN BANACH ALGEBRAS

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Acta mathematica Scientia 2024年第1期44卷 311-338页

作者： Safoura rezaei ADERYANI Azam AHADI reza SAADATI Hari m.SRIVASTAVA School of mathematics Iran University of Science and TechnologyNarmakTehranIran Department of mathematics and Statistics Universtity of VictoriaVictoriaCanada Department of medical Research China Medical University HospitalChina Medical UniversityTaichung40402China Department of mathematics and Informatics Azerbaijan University71 Jeyhun Hajibeyli StreetAZ1007BakuAzerbaijan Section of mathematics International TelematicUniversity UninettunoI-00186RomeItaly

In this paper,we define a new class of control functions through aggregate special *** class of control functions help us to stabilize and approximate a tri-additiveψ-functional inequality to get a better estimation for permuting tri-homomorphisms and permuting tri-derivations in unital C*-algebras and Banach algebras by the vector-valued alternative fixed point theorem.

关键词： permuting tri-homomorphism in Banach algebra permuting tri-derivation on C*-algebra fixed point theorem Ulam-Hyers-Rassias stability aggregate special functions tri-additiveψ-functional inequality

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Temperature-jump tensile tests to induce optimized TRIP/TWIP effect in a metastable austenitic stainless steel

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International Journal of minerals,metallurgy and materials 2024年第9期31卷 2025-2036页

作者： mohammad Javad Sohrabi Hamed mirzadeh Saeed Sadeghpour Abdol reza Geranmayeh reza mahmudi School of metallurgy and materials Engineering College of EngineeringUniversity of Tehran14395-515TehranIran Centre for Advanced Steels Research Materials and Mechanical EngineeringUniversity of Oulu90014 OuluFinland

In the present work,plastic deformation mechanisms were initially tailored by adjusting the deformation temperature in the range of 0 to 200℃ in AISI 304L austenitic stainless steel,aiming to optimize the strength-ductility *** was shown that the combined twinning-induced plasticity(TWIP)/transformation-induced plasticity(TRIP)effects and a wider strain range for the TRIP effect up to higher strains by adjusting the deformation temperature are good strategies to improve the strength-ductility synergy of this metastable stainless *** this regard,by consideration of the observed temperature-dependency of plastic deformation,the controlled sequence of TWIP and TRIP effects for archiving superior strength-ductility trade-off was intended by the pre-designed temperature jump tensile ***,the optimum tensile toughness of 846 mJ/m^(3) and total elongation to 133% were obtained by this strategy via exploiting the advantages of the TWIP effect at 100℃ and the TRIP effect at 25℃ at the later stages of the ***,a deformation-temperature-transformation(DTT)diagram was developed for this metastable ***,based on work-hardening analysis,it was found that the main phenomenon constraining further improvement in the ductility and strengthening was the yielding of the deformation-induced α′-martensite.

关键词： metastable stainless steels transformation-induced plasticity twinning-induced plasticity stacking fault energy mechanical properties

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Particle size distribution in a multi-zone circulating fluidized bed polymerization reactor

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PARTICUOLOGY 2024年第10期93卷 291-299页

作者： Hadadiyan, mohammadhossein mostou, Navid marandi, reza Univ Tehran Coll Engn Proc Design & Simulat Res Ctr Sch Chem Engn POB 11155-4563 Tehran Iran Natl Petrochem Co Petrochem Res & Technol Co Polymer Res Grp POB 14358-84711 Tehran Iran

This research focuses on modeling a multi-zone circulating reactor (mZCR) in the polypropylene production process. In these reactors, designed for polyolefin production, small catalyst particles (20-300 mm) initiate polymerization in the presence of monomer gas. The reactor consists of two main regions: the riser and the downer. The riser operates in the fast fluidization and the downer is in the moving bed regime. Employing the two-fluid model with the Eulerian-Eulerian approach, the dynamics of both solid and gas phases were modeled by applying Newton's laws of motion and assuming spherical particles. The population balance of particles within the reactor was also coupled with the equations of motion. The simultaneous solution of these equations provides valuable insights into particle and fluid behavior, revealing trends such as the growth of polymer particles. Furthermore, the impact of various operating conditions was explored. This study also examined the effects of design parameters (gas inlet velocity, average inlet diameter, and temperature) on the system performance. For instance, it was shown that in the case where the solid circulation flux is 30 kg/(m2 2 s) the velocity of particles in the bed increases from 0.4 at the inlet to 1.1 m/s in the fully developed zone, when it is 43 kg/(m2 2 s) the velocity of particles increases from 0.3 to 1.4 m/s, and when it is 55 kg/(m2 2 s), it is increased from 0.22 to 1.5 m/s. Additionally, trends in particle size distribution based on temperature adjustments were revealed. This study showed that higher temperatures accelerate the polymerization reaction rate, promoting faster growth kinetics and the formation of larger particles. (c) 2024 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： Fluidization Polymerization Gas-solid flow multi-zone circulating reactor (mZCR) CFD-PBm Two-fluid model GAS-PHASE POLYmERIZATION CFD SImULATION 2-FLUID mODEL HYDRODYNAmICS FLOW DYNAmICS SOLIDS PBm

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