Computer Science Research Articles
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Design of Maintaining Data Security on IoT Data Transferred Through IoT Gateway System to Cloud Storage
S. Alexander Suresh, R. Jemima Priyadarsini
Abstract - IoT is a smart-device environment; it acts smarter and gives higher quality to enhance the user experience. IoT is an open network environment. However, IoT's security challenges are more vulnerable because the devices are openly accessible to all in the network. IoT communication can be formed in different ways, where the device generates the data is communicated to other devices or gateway or cloud. Therefore, security challenges are in everywhere IoT environment. IoT Communication considered in this paper is gateway communication. Data generated from the IoT environment are directed to the cloud over a gateway system. Hence, the data essentials to be protected from the IoT devices to the gateway system and the gateway system to the cloud storage. The cloud is a public environment that makes security is a challenge to keep data secure. Therefore, securing IoT data to the cloud environment is the most significant focus. This paper focuses on securing the data from the gateway system to the cloud storage. The paper proposes an enhanced modern symmetrical encryption to secure data to ensure data security in the travel and storage of IoT data to the cloud. The proposed Enhanced Modern Symmetric Data Encryption (EMSDE) is a block cipher encryption technique. It encrypts data by 64-bit block. Proposed encryption is tested according to time and level of security. Thingspeak stores the IoT data sent from the IoT gateway system for implementation and testing. Based on the testing, the proposed EMSDE produces better results, and it is tailored to secure data stored in the cloud from IoT devices.
Published: 2022Read / Download
Optimum Selection of Virtual Machine Using Improved Particle Swarm Optimization in Cloud Environment
R.Jeena, Logesh R
Abstract - Nowadays, Cloud Computing acts a major role in every field. These days, more large data centers are in service and many small cloud data centers are enlarging all over the universe. Cloud Computing is a catchword in the domain of HPC and offers on-demand services to the resources on the internet. The VMs (Virtual Machines) specified in the cloud data centres may have different specifications and instable resource usage, which causes imbalanced resource utilization within servers. Thus, it leads to performance degradation. Hence to achieve efficient selection of VM, these challenges must be addressed and solved by using meta-heuristics algorithms. In order to process the data, the VMs are placed on the PMs (Physical Machines). There will be multiple and dynamic request of input in the IaaS(Infrastructure as a Service) framework, hence the system's responsibility is to create a VMs without knowing the types of tasks. Therefore, the fixed tasks scheduling is not right for this system. The most important research area that needs to be addressed is its performance in scheduling. The best and optimal solution is to find out in the cloud environment. Metaheuristics-based algorithms provide the near-optimal solution. In this paper, we proposed an Improved Particle Swarm Optimization algorithm to reduce the makespan and improve the throughput. We have compared our results with adaptive three-threshold energy-aware (ATEA) algorithm and PSO. The investigational results display the proposed Improved PSO algorithm will schedule and balance the load in the dynamic cloud environment better than the other approaches.
Published: 2022Read / Download
A Novel Algorithm for Secured Data Sharing in Cloud using GWOA-DNA Cryptography
Mercy Joseph, Gobi Mohan
Abstract - Cloud is a recent technology that enables wide access and storage on the internet. Moreover, the cloud computing environment allows storing and sharing plenty of digital data including text, image, video, audio, etc. through the internet. Although it is cost-effective and has numerous advantages, cloud technology still faces a lot of challenges like data loss, quality issues, and data security. In this paper, an effective algorithm is introduced using deoxyribonucleic acid (DNA)-based cryptography to enhance data security while sharing the data over the internet. For this process, an optimized encryption model is implemented using Grey Wolf Optimization (GWO) Algorithm to generate optimal encrypted data while sharing. Various datasets have been implemented to verify the efficiency of the proposed GWO Assisted-DNA (GWOA-DNA) cryptography in terms of accuracy and execution time.
Published: 2022Read / Download
Migration Prediction Approach for Predict the Overloaded and Under Loaded Workload in Cloud Environment
Senthamarai N
Abstract - The resource necessity of any application substance differs dynamically dependent on its plan and other computational conditions like processor, memory, etc. A migration prediction approach is proposed to foresee the over-burden and under stacked hosts, in light of the previous history of execution time taken for different workloads during VM migration. The rough set theory is incorporated in this proposed model to analyze the execution time taken for different workloads. The rough set theory is a popular prediction technique to predict execution time for different workloads during VM. The migration delay is minimized based on the past execution time of each processor for different categories of jobs. The execution time for each processor is calculated and maintained inside the prediction table. The quantity of future migrations is calculated based totally at the feasible allocations that can be made, in order that the migration delay is minimized based at the beyond execution time of each processor for extraordinary categories of jobs. Finally, optimized resource utilization is executed to give the exceptional answer amongst all possible solutions and it reduces makespan fee of jobs.
Published: 2022Read / Download
Constrained Cuckoo Search Optimization Based Protocol for Routing in Cloud Network
J. Ramkumar, R.Vadivel, B.Narasimhan
Abstract - Cloud Computing (CC) is the process of providing on-demand data to the user via the internet. In CC, users don't need to manage data storage and computational power actively. Finding the best route in a cloud network is entirely different from other general networks which it is due to high scalability. Protocols developed for other general networks will never suit or give better performance in cloud networks due to its scalability. This paper proposes a bio-inspired protocol for routing in a cloud network, namely Constrained Cuckoo Search Optimization-based Protocol (CCSOP). The routing strategy of CCSOP is inspired by the natural characteristics of the cuckoo bird towards finding a nest to lay its eggs. Levy Flight concept is applied with different constraints to enhance optimization performance towards finding the best route in a cloud network that minimizes energy consumption. CCSOP is evaluated in Greencloud using benchmark network performance metrics against the current routing protocols. The efficacy of CCSOP is evaluated using benchmark performance measures. CCSOP appears to outperform current cloud network routing protocols in terms of energy consumption.
Published: 2021Read / Download
Hybrid Intrusion Detection Method Based on Constraints Optimized SAE and Grid Search Based SVM-RBF on Cloud
Nirmalajyothi Narisetty, Gangadhara Rao Kancherla, Basaveswararao Bobba, K. Swathi
Abstract - The present era is facing lot of Security, Privacy, and Integrity issues because of tremendous development in communication technology, data storage devices, and computing advancements leading to unavoidable losses. As a result of the aforementioned technological revolutions day by day, many of the organizations or institutions started migrating to cloud environment. Because of this, security issues have increased coupled with the advent of new ways of penetration into networks. Unauthorized users and many professionals with malicious intent started exploiting the legitimate users through cyber-crimes. So, there is a need to implement a proper Intrusion Detection System with optimization procedures. This paper proposes a hybrid Intrusion Detection approach with a combination of Constraints Optimized Stacked Autoencoder (COSAE) for dimension reduction and grid search based SVM-RBF classifier (GSVM-RBF). The COSAE+GSVM-RBF model enhanced the performance using a two-fold. i) The SAE is optimized through regularization techniques with the adoption of weight and dropout constraints, ii) To enhance the performance of the SVM classifier with RBF for tuning the hyperparameters using grid search. Various experiments are conducted to validate this model with four activation functions Scaled Exponential Linear Unit (SELU), Rectified Linear Unit, softplus, and Exponential Linear Unit (ELU) for dimension reduction using COSAE. The improvements carried out in this paper result in exploding gradients and vanishing gradients avoids overfitting in large datasets, intrusion detection rate, gain in computational time, and 100% F-Measure in classifying minor class labels. The proposed approach is validated on the CICIDS2017 dataset. Further, a comparative analysis of the proposed approach with state-of-the-art approaches has been conducted. Based on the experimental results it is observed that the proposed approach outperforms the prevailing approaches.
Published: 2021Read / Download
A Novel Three Layer Filtering (3L-F) Framework for Prevention of DDoS Attack in Cloud Environment
A. Somasundaram, V. S. Meenakshi
Abstract - Data security is an integral requirement of any modern information system as attackers are gaining chances due to the prompt improvement in digital technology. However, in the current decade, the use of cloud computing is rising steeply, and so is network traffic. As the cloud computing model is based on the distributed computing, cloud servers are widely distributed and cloud users can access the service from anywhere and at any time. This makes the cloud servers, a target for the adversaries. The most common attack in a cloud environment is the DDoS attack that causes bulky and abnormal traffic to the cloud server. The cloud server is incapable to manage such unusual traffic and stops momentarily by making the server down with excessive traffic. DDoS attacks can be avoided by diligent traffic control prior to the DDoS attack. This paper proposes a novel three-layer filtering mechanism to prevent various forms of DDoS attacks. The first layer of the proposed DDoS attack prevention mechanism uses two-level authentication processes. Second layer filtering verifies whether the user accesses the resources within the pre-defined limits and the third layer filtering sieves out the spoofed packets. The proposed model has been analyzed for evaluating the performance in terms of CPU overhead and load, the throughput of the victim, the reduction in connection delay. The result analysis shows that the proposed model has improved performance with a higher detection rate of 0.92 and a lower dropout rate of 0.10.
Published: 2021Read / Download
Lucid Firefly Based Routing Protocol (LFRP) for Accessing Big Data in Cloud
S. A. Gunasekaran, M. Senthilkumar
Abstract - Minimizing energy consumption is a significant issue in cloud computing. Nodes present in cloud computing are heterogeneous in nature. Traditional routing protocols fit best for homogenous networks and while using in heterogeneous network it will never give its better performance. Accessing big data in cloud is a challenging task because more stable route is necessary for the access of big data. Routes failures are unexpected and if a route gets failed in cloud computing while accessing big data, then it will affect the network performance drastically. In this paper, Lucid Firefly based Routing Protocol (LFRP) is proposed to identify the optimized route to access the big data and to minimize the energy consumption. LFRP utilizes the natural characteristics of firefly to identify the best route and to share the identified best route with others. LFRP finds the route based on the size of data where the fitness function plays a major role in identifying the best route. The simulation results make an indication that the proposed routing protocol LFRP has consumed less amount of energy i.e., 3.95J in accessing the big data than other routing protocols which makes an indication that the routing protocol has found the better route to destination which faces low delay (65ms) and packet delivery ratio as 94.20%.
Published: 2021Read / Download
Energy Efficient Data Transfer in Mobile Cloud Computing Environment Using Particle-Salp Swarm Optimization Technique
C.T.K. Amarnath, S.K. Mahendran
Abstract - Mobile cloud computing (MCC) can request the service of cloud from the mobile appliance, such as mobile phones, laptops, palm tops and so on for data transfer in such a way to provide more beneficial applications. The consumption of energy is a major problem during the transfer of data in MCC that is needed to be optimized with the allocation of the tasks to mobile or cloud environment in an efficient manner. In order to deal this issue, a hybrid particle-salp (PS-SALP) swarm optimization technique is proposed in this research that incorporates the characteristic features of the particles and the salps leading to better convergence to enhanced solution in the resource allocation of data transfer. The main aim of this paper is to minimize the utility cost (UC) representing a better balance between energy consumption and the period of execution of the task. Initially, the local optimal solutions for each problem is found, followed by which the global optimal solution is obtained using the proposed PS-SALP optimization algorithm. The performance of the proposed technique of data transfer in MCC is analyzed in terms of the metrics, such as UC, energy consumption, and the task execution time. The results show the superiority of the proposed technique in energy efficient data transfer in the MCC environment.
Published: 2021Read / Download
Evolutionary Computing Assisted Visually-Imperceptible Hybrid Cryptography and Steganography Model for Secure Data Communication over Cloud Environment
Denis R, Madhubala P
Abstract - The exponential growth of communication technologies and related application environments has broadened the cloud computing ecosystem horizon to meet major communication needs. However, in-parallel upsurge in online attacks, security breaches or allied intrusion events has alarmed industries to ensure optimal data security. Unlike text data transmission, image, or other multimedia communication over the cloud requires computational efficiency, imperceptibility, etc. to meet attack-resilient transmission. Amongst the major available security systems, the combination of cryptosystems and steganography has been identified as an augmented security model for data transmission. However, it demands enhancement in both stages to meet cloud-specific communication efficiency...........................
Published: 2020Read / Download
Robust Resource Scheduling With Optimized Load Balancing Using Grasshopper Behavior Empowered Intuitionistic Fuzzy Clustering in Cloud Paradigm
G. Kiruthiga, S. Mary Vennila
Abstract - With the advancement in internet technology, everyone can able to utilize resources with low cost using cloud resources. There will be numerous requests for task scheduling to share resources in the cloud environment. When the task request is received by the cloud technology it should have the ability to distribute the workload among sharable resources in a balanced manner and effective utilization of resources. Machine learning and metaheuristic algorithms provide a dynamic part in balanced task assignments in the cloud paradigm. Existing unsupervised models-based load balancing, centroid selection is done randomly and imprecise job requests are not well handled by them. This paper aims to develop a clustering model-based task scheduling with the knowledge of behavioural inspired optimization algorithm .........................
Published: 2020Read / DownloadEnergy Efficient Load Balancing Aware Task Scheduling in Cloud Computing using Multi-Objective Chaotic Darwinian Chicken Swarm Optimization
G. Kiruthiga, S. Mary Vennila
Abstract - Scheduling of tasks in a cloud environment has larger influence on time and energy depletion. Different heuristic models were developed to solve the NP-hard task scheduling problem based on time. However, ideal task scheduling algorithms must also maximize energy efficiency with good load balancing and ensure better Quality-of-Service (QoS). An innovative multi-objective Chaotic Darwinian Chicken Swarm Optimization (CDCSO) system is suggested in this article to provide energy efficient QoS and load balancing aware task scheduling. The multi-objective CDCSO algorithm incorporates the chaotic and Darwinian Theory to the standard Chicken Swarm Optimization to increase its global exploration and maximize the convergence rate. This performance enhanced CDCSO algorithm models.......................
Published: 2020Read / Download
Grid and Cloud Computing Security: A Comparative Survey
Sarra Namane, Nacira Ghoualmi
Abstract - The major purpose of this article is to know the security requirements and their solutions in grid and cloud computing environments. We first focused generally on the security issue in grids as in cloud computing where we examined all the articles proposed in the literature. Then, we classify them according to the treated security issue (authentication, access control, integrity, confidentiality or multiple security issues). A comparative study was carried out between the different techniques presented in each class of each environment. The same classification is done with research articles concerning security issues in cloud computing environment. The study was followed by a comparison between the different proposed techniques for each class in grid computing with those proposed within the same class in cloud. As a result we found that the access control issue is the most considered research area in both grid and cloud computing environments.
Published: 2019Read / DownloadA Diffie-Hellman and Two Step Verification based Secure Cloud Computing Paradigm
Mir Shahnawaz Ahmad, Syed Rameem Zahra
Abstract - The foundation of cloud computing has been laid on five important traits: self-service on appeal, wide network access, pooling of resources (location independence), quick elasticity and quantified service. In least complex terms, it is to say that any cloud product (whether infrastructure, platform or software) is offered in a way that it can be rented by consumers over the internet (pay for what you use on demand). Owing to all these characteristics, there are enormous advantages from the viewpoint of both the vendor and the user and hence the cloud is gaining limelight day by day. However, it should not be forgotten that every coin has two sides; the level of dangers against IT frameworks is specifically corresponding to the level of developing technology. In order to make any new reliable technology, the security professionals need to pay attention to discover............................
Published: 2018Read / Download
Congestion Aware Packet Routing For Delay Sensitive Cloud Communications
Vincent O. Nyangaresi, Silvance O. Abeka, Solomon. O. Ogara
Abstract - In the recent years, many organizations have turned to cloud technology to support their information technology services. The cloud servers are therefore increasingly holding huge and sensitive information belonging to diverse groups of individuals and companies. Additionally, some organizations employ the cloud to provide them with online backup services. One of the most outstanding requirements for cloud customers is availability - the customers must be able to access their information and other resources stored in the cloud any time and from anywhere on the globe. This means that there should be efficient network design such that any delays are averted. The connection between the customer and the cloud can therefore be regarded as delay senstive. Network congestions often lead to delays and packet losses.............................
Published: 2017Read / DownloadA Novel Approach for Data Privacy Using Attribute Based Scheme Algorithm for Cloud Computing
A.Nithya, B. Ramakrishnan, Resul Das
Abstract - Cloud computing is the mass storage area that helps the user to access the data anywhere. There are so many platforms provided by the cloud service provider. They are SaaS (Software as a Service), PaaS (Platform as a Service) and IaaS (Infrastructure as a Service) etc. Though security is not fully provided by the cloud service provider to reshape the advances in information technology, cloud computing is expected as an updated technology. The data was securely stored in the cloud and if it is corrupted then the proxy is implemented to regenerate the corrupted data in the cloud. Thus security and integrity is successfully achieved. This is further extended by implementing efficient file fetching by the third party user. To maintain efficient file fetching system Multi authority cloud model is proposed. The model is .............................
Published: 2016Read / Download
Distributed File Systems Implementation on an Edge Router using GlusterFS for Cloud Applications
Souryendu Das
Abstract - A distributed file system (DFS) is a client/server-based application that allows clients to access and process data stored on the server as if it were on their own computer. An edge router has series of data cards, to handle data inflow and outflow which can be of the form of email headers, data packets, etc. Each of these data cards have their own file system architecture. This paper implements a distributed file system approach on all these data cards, so as to make it a centrally controlled one file system and not having parallel many file systems. Convenience of usage and file handling capacity is also looked in this paper. The servers are portrayed as the data cards of an edge router and the client access points are the router processor cards. The DFS on Edge Router is implemented using GlusterFS which is a scale-out network-attached storage file system.
Published: 2016Read / DownloadTask scheduling in Cloud Using Hybrid Cuckoo Algorithm
Sumandeep Aujla , Amandeep Ummat
Abstract - Cloud computing is used for delivering and managing the services over the internet. Cloud computing provides data access and storage devices without the knowledge of the physical location of the end user. Cloud computing has three types of services: software as a service (SaaS), platform as a service (PaaS) and infrastructure as a service (IaaS). Task scheduling is the main issue in cloud computing and it is very important part of cloud computing. Various types of algorithms are used for scheduling for example FIFO, Genetic algorithm, round robin algorithm etc. This paper is focused on the optimization solution for the task scheduling using hybrid cuckoo algorithm. This algorithm combines the results of genetic algorithm and cuckoo search algorithm.
Published: 2015Read / Download
Security Concerns at Various Levels of Cloud Computing Paradigm: A Review
Aarti Singh, Manisha Malhotra
Abstract - Cloud computing has become a buzzword in IT industry these days and organization are getting attracted towards this magnet for expanding their infrastructure at cheaper rates. However, with all flexibility offered by cloud there are concerns about security, integrity and availability of precious information of cloud users. Conventional protection mechanisms need to be reconsidered for their effectiveness, since cloud service model is distinctly different from other internet based service models. Recently, much research efforts are being done in cloud security but still more efforts are desired. Since cloud security is a sensitive dimension affecting its wide commercial acceptance. This work explores various levels of security concerns in cloud environment and lists available mechanism for addressing them.
Published: 2015Read / Download