Quantum-based Rivest–Shamir–Adleman (RSA) approach for digital forensic reports

2020 ◽  
Vol 34 (06) ◽  
pp. 2050085 ◽  
Author(s):  
Jaishree Jain ◽  
Ajit Singh
Keyword(s):  
Cloud Computing ◽  
Simulation Environment ◽  
Security Attacks ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Digital Forensic ◽  
Important Concern ◽  
Multiple Clouds ◽  
Cloud Users ◽  
Multi Cloud

Cloud computing is a model that permits usage of a distributed resource for cloud users using the pay-as-you-use method. It offers many advantages to users and companies, in terms of various resources and applications as a service. In spite of the existence of these advantages, there are a few limitations that place constraints on the utilization of a cloud computing environment. Security is an important concern in a cloud computing environment as it probes various security attacks. Therefore, in this work, a novel quantum-based Rivest–Shamir–Adleman (RSA) model is proposed for encryption of forensic reports during storage or data sharing on clouds. To evaluate the effectiveness of the proposed approach, a suitable simulation environment is designed for a multi-cloud environment. Experimental results reveal the proposed approach can efficiently encrypt and store data on multiple clouds without introducing potential overheads. Therefore, the proposed approach is more efficient for real-time applications.

Optimal Resource Usage in Multi-Cloud Computing Environment

2013 ◽  
Vol 3 (1) ◽  
pp. 44-57 ◽  
Author(s):  
Veena Goswami ◽  
Choudhury Nishkanta Sahoo
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Queueing Network ◽  
Computing Environment ◽  
New Paradigm ◽  
Cloud Computing Environment ◽  
Optimal Resource ◽  
Optimal Resource Management ◽  
And Performance ◽  
Multi Cloud

Cloud computing has emerged as a new paradigm for accessing distributed computing resources such as infrastructure, hardware platform, and software applications on-demand over the internet as services. This paper presents an optimal resource management framework for multi-cloud computing environment. The authors model the behavior and performance of applications to integrate different service-providers for end-to-end-requirements. Each service model caters to specific type of requirements and there are already number of players with own customized products/services offered. Intercloud Federation and Service delegation models are part of Multi-Cloud environment where the broader target is to achieve infinite pool of resources. They propose an analytical queueing network model to improve the efficiency of the system. Numerical results indicate that the proposed provisioning technique detects changes in arrival pattern, resource demands that occur over time and allocates multiple virtualized IT resources accordingly to achieve application Quality of Service targets.

scholarly journals Proposed Proactive Digital Forensic Approach for Cloud Computing Environment

2018 ◽  
Vol 7 (4.15) ◽  
pp. 12
Author(s):  
Ganthan Narayana Samy ◽  
Nurazean Maarop ◽  
Doris Hooi-Ten Wong ◽  
Fiza Abdul Rahim ◽  
Noor Hafizah Hassan ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Digital Forensics ◽  
Massive Data ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Digital Forensic ◽  
Multi Stakeholder

There are many challenges for the digital forensic process in the cloud computing due to the distinguished features of the cloud computing environment. Many of well-known digital forensic methods and tools are not suitable for cloud computing environment. The multi-tenancy, multi-stakeholder, Internet-based, dynamics expendability, and massive data, logs and datasets are examples of the cloud computing environment features that make conducting digital forensics in the cloud computing environment a very difficult task. Therefore, there is a need to develop an appropriate digital forensic approach for cloud computing environment. Thus, this paper proposed a proactive digital forensic approach for cloud computing environment. 

scholarly journals A binary Bird Swarm Optimization based load balancing algorithm for cloud computing environment

2021 ◽  
Vol 11 (1) ◽  
pp. 146-160
Author(s):  
Kaushik Mishra ◽  
Santosh Kumar Majhi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Service Providers ◽  
Scheduling Algorithm ◽  
Simulation Environment ◽  
Computing Environment ◽  
Swarm Optimization ◽  
Cloud Computing Environment ◽  
Np Hard Problem ◽  
Load Balancing Algorithm

Abstract Task scheduling and load balancing are a concern for service providers in the cloud computing environment. The problem of scheduling tasks and balancing loads in a cloud is categorized under an NP-hard problem. Thus, it needs an efficient load scheduling algorithm that not only allocates the tasks onto appropriate VMs but also maintains the trade-off amidst VMs. It should keep an equilibrium among VMs in a way that reduces the makespan while maximizing the utilization of resources and throughput. In response to it, the authors propose a load balancing algorithm inspired by the mimicking behavior of a flock of birds, which is called the Bird Swarm Optimization Load Balancing (BSO-LB) algorithm that considers tasks as birds and VMs as destination food patches. In the considered cloud simulation environment, tasks are assumed to be independent and non-preemptive. To evaluate the efficacy of the proposed algorithm under real workloads, the authors consider a dataset (GoCJ) logged by Goggle in 2018 for the execution of cloudlets. The proposed algorithm aims to enhance the overall system performance by reducing response time and keeping the whole system balanced. The authors have integrated the binary variant of the BSO algorithm with the load balancing method. The proposed technique is analyzed and compared with other existing load balancing algorithms such as MAX-MIN, RASA, Improved PSO, and other scheduling algorithms as FCFS, SJF, and RR. The experimental results show that the proposed method outperforms when being compared with the different algorithms mentioned above. It is noteworthy that the proposed approach illustrates an improvement in resource utilization and reduces the makespan of tasks.

scholarly journals Hybrid Cryptography based E2EE for Integrity & Confidentiality in Multimedia Cloud Computing

2019 ◽  
Vol 8 (10) ◽  
pp. 918-924
Keyword(s):  
Cloud Computing ◽  
Multimedia Data ◽  
Computing Environment ◽  
Computing Power ◽  
Cloud Computing Environment ◽  
Multimedia Cloud ◽  
Cloud Providers ◽  
High Level ◽  
And Storage ◽  
Cloud Users

Cloud Computing has become a desirable state for the mobile users by providing anytime and anywhere access to various services and resources. Likewisemultimedia data such as audio, images, video and gif files covers the maximum part of the network traffic, as most of the data shared, produced, processed and stored through numerous sources such as smart phones, computers, sensor networks, satellites, medical records etc. is of multimedia type. Such form of data requires huge computing power and storage capacities along with the major security constraints. Mobile devices with limited configuration and low computing powers are not able to match with the high level computing and manipulations required by costly multimedia softwares. That’s why demand for the Multimedia Cloud Computing came into frames. As multimedia data has distinct computing, storage and security constraints, this field has become anemerging and latest area of research. Many researches have also proposed separate architectures for Multimedia Cloud Computing. Security, integrity and confidentiality of private and secret media files is always a matter of stake for cloud users as well as for cloud providers. For multimedia cloud security concerns, cryptography is a guaranteed solution.This paper has discussed about the various needs and challenges faced by the multimedia cloud providers. This work has also proposed a hybrid cryptography algorithm based end-to-end encryption (E2EE) approach to maintain integrity and confidentiality in multimedia cloud computing environment. The second last section provides a performance analysis for the algorithm in terms of tables and graphs to justify the results

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