scholarly journals Assessing Risks and Cloud Readiness in PaaS Environments

2019 ◽  
Vol 8 (3S) ◽  
pp. 243-249
Keyword(s):  
Cloud Computing ◽  
Cloud Services ◽  
Risk Minimization ◽  
Cloud Infrastructure ◽  
Computing Environment ◽  
Configurable Computing ◽  
Cloud Computing Environment ◽  
Distributed Models ◽  
Software Vendor ◽  
Complex Architecture

The cloud computing has utilization of pervasive or distributed models on demand access to highly configurable computing devices for fast provision and less management efforts. The complex architecture, multitenant and virtual environment in cloud infrastructure asks for risks identification and mitigation. The cloud computing model business needs reassurances so it’s prime consideration for testing the cloud services. This research primarily identifies various risks, threats, testing models and vulnerabilities in cloud computing environment. This research has implemented the risk assessment and cloud readiness for PaaS environment by scanning its code with a software vendor. The research makes an emphasis on risk minimization strategies and trust evaluation in cloud computing environment.

scholarly journals Adaptive Learning and Automatic Filtering of Distributed Denial of Service (DDoS) Attacks in Cloud Computing Environment

2019 ◽  
Vol 9 (1S3) ◽  
pp. 200-205
Keyword(s):  
Cloud Computing ◽  
Adaptive Learning ◽  
Denial Of Service ◽  
Cloud Services ◽  
Detection Accuracy ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Automatic Filtering

Distributed Denial of Service (DDoS) attacks has become the most powerful cyber weapon to target the businesses that operate on the cloud computing environment. The sophisticated DDoS attack affects the functionalities of the cloud services and affects its core capabilities of cloud such as availability and reliability. The current intrusion detection system (IDS) must cope with the dynamicity and intensity of immense traffic at the cloud hosted applications and the security attack must be inspected based on the attack flow characteristics. Hence, the proposed Adaptive Learning and Automatic Filtering of Distributed Denial of Service (DDoS) Attacks in Cloud Computing Environment is designed to adapt with varying kind of protocol attacks using misuse detection. The system is equipped with custom and threshold techniques that satisfies security requirements and can identify the different DDoS security attacks. The proposed system provides promising results in detecting the DDoS attacks in cloud environment with high detection accuracy and good alert reduction. Threshold method provides 98% detection accuracy with 99.91%, 99.92% and 99.94% alert reduction for ICMP, UDP and TCP SYN flood attack. The defense system filters the attack sources at the target virtual instance and protects the cloud applications from DDoS attacks.

Controlled Intelligent Agents' Security Model for Multi-Tenant Cloud Computing Infrastructures

2017 ◽  
Vol 9 (1) ◽  
pp. 1-13
Author(s):  
Howard Hamilton ◽  
Hadi Alasti
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Intelligent Agents ◽  
Cloud Service ◽  
Cloud Services ◽  
Service Users ◽  
Security Model ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Service Models

Data security in the cloud continues to be a huge concern. The adoption of cloud services continues to increase with more businesses transitioning from on premise technology infrastructures to outsourcing cloud-based infrastructures. As the cloud becomes more popular, users are increasingly demanding control over critical security elements of the data and technology assets that are in the cloud. In addition, there are still cries for greater data and security in the cloud. The goal of this paper is to provide cloud service users with greater control over data security in the cloud while at the same time optimizing overall security in the multi-tenant cloud computing environment. This paper introduces cloud-based intelligent agents that are configurable by the users and are expected to give greater compliance for data security in any of the cloud service models.

scholarly journals Cache optimization cloud scheduling (COCS) algorithm based on last level caches

2019 ◽  
Vol 8 (3) ◽  
pp. 184
Author(s):  
K. Vinod Kumar ◽  
Ranvijay Ranvijay
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Average Power ◽  
Cloud Services ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Cache Optimization ◽  
Dynamic Voltage ◽  
Increasing Demand ◽  
And Storage

<p><span>Recently, the utilization of cloud services like storage, various software, networking resources has extremely enhanced due to widespread demand of these cloud services all over the world. On the other hand, it requires huge amount of storage and resource management to accurately cope up with ever-increasing demand. The high demand of these cloud services can lead to high amount of energy consumption in these cloud centers. Therefore, to eliminate these drawbacks and improve energy consumption and storage enhancement in real time for cloud computing devices, we have presented Cache Optimization Cloud Scheduling (COCS) Algorithm Based on Last Level Caches to ensure high cache memory Optimization and to enhance the processing speed of I/O subsystem in a cloud computing environment which rely upon Dynamic Voltage and Frequency Scaling (DVFS). The proposed COCS technique helps to reduce last level cache failures and the latencies of average memory in cloud computing multi-processor devices. This proposed COCS technique provides an efficient mathematical modelling to minimize energy consumption. We have tested our experiment on Cybershake scientific dataset and the experimental results are compared with different conventional techniques in terms of time taken to accomplish task, power consumed in the VMs and average power required to handle tasks.</span></p>

Cloud Computing

2012 ◽  
pp. 191-207 ◽  
Author(s):  
Shantanu Pal
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Effective Means ◽  
Cloud Service ◽  
Security And Privacy ◽  
Cloud Infrastructure ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Security Issues ◽  
Computing Platforms

In a cloud ecosystem, most of the data and software that users use reside on the remote server(s), which brings some new challenges for the system, especially security and privacy. At present, these security threats and attacks are the greatest concern for the service providers towards delivering a more secure cloud infrastructure. One of the major concerns is data security, implemented by the most effective means possible and the protection of stored data from unauthorized users and hackers. When considering these security issues, trust is one of the most important means to improve the system’s security and enable interoperability of current heterogeneous cloud computing platforms. The objective of this chapter is to discuss and understand the basic security and privacy challenges of a cloud computing environment as the security of cloud computing is the greatest challenge for delivering a safer cloud environment for both the service providers and the service customers. With this in mind, this chapter will introduce the risks and possible attacks in a cloud computing environment. The major goal is to specify the security risks and attacks and consider trust of cloud service users for delivering a safer and innovation business model.

Controlled Intelligent Agents' Security Model for Multi-Tenant Cloud Computing Infrastructures

2018 ◽  
pp. 471-484
Author(s):  
Howard Hamilton ◽  
Hadi Alasti
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Intelligent Agents ◽  
Cloud Service ◽  
Cloud Services ◽  
Service Users ◽  
Security Model ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Service Models

Data security in the cloud continues to be a huge concern. The adoption of cloud services continues to increase with more businesses transitioning from on premise technology infrastructures to outsourcing cloud-based infrastructures. As the cloud becomes more popular, users are increasingly demanding control over critical security elements of the data and technology assets that are in the cloud. In addition, there are still cries for greater data and security in the cloud. The goal of this paper is to provide cloud service users with greater control over data security in the cloud while at the same time optimizing overall security in the multi-tenant cloud computing environment. This paper introduces cloud-based intelligent agents that are configurable by the users and are expected to give greater compliance for data security in any of the cloud service models.

scholarly journals USE OF DISTRIBUTED HASH TABLES TO PROVIDE ACCESS TO CLOUD SERVICES

2020 ◽  
pp. 85-95
Author(s):  
Y.P. Klots ◽  
I.V. Muliar ◽  
V.M. Cheshun ◽  
O.V. Burdyug
Keyword(s):  
Cloud Computing ◽  
Cloud Services ◽  
Local Network ◽  
Cloud System ◽  
Information Flows ◽  
Access To Services ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Web Resource ◽  
Distributed Cloud

In the article the urgency of the problem of granting access to services of distributed cloud system is disclosed, in particular, the peer distributed cloud system is characterized. The process of interaction of the main components is provided to access the domain name web resource. It is researched that the distribution of resources between nodes of a peer distributed cloud system with the subsequent provision of services on request is implemented using the Kademlia protocol on a local network or Internet and contains processes for publishing the resource at the initial stage of its owner, replication and directly providing access to resources. Application of modern technologies of adaptive information security systems does not allow full control over the information flows of the cloud computing environment, since they function at the upper levels of the hierarchy. Therefore, to create effective mechanisms for protecting software in a cloud computing environment, it is necessary to develop new threat models and to create methods for displaying computer attacks that allow operatively to identify hidden and potentially dangerous processes of information interaction. Rules of access form the basis of security policy and include restrictions on the mechanisms of initialization processes access. Under the developed operations model, the formalized description of hidden threats is reduced to the emergence of context-dependent transitions in the multigraph transactions. The method of granting access to the services of the distributed cloud system is substantiated. It is determined that the Distributed Hash Table (DHT) infrastructure is used to find a replication node that has a replica of the requested resource or part of it. The study identified the stages of identification of the node's validation. The process of adding a new node, validating authenticity, publishing a resource, and accessing a resource is described in the form of a step-by-step sequence of actions within the framework of the method of granting access to services of a distributed cloud system by graphical description of information flows, interaction of processes of information and objects processing.

scholarly journals A Method of Extracting Ontology Module Using Concept Relations for Sharing Knowledge in Mobile Cloud Computing Environment

2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
Keonsoo Lee ◽  
Seungmin Rho ◽  
Seok-Won Lee
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Syntactic Structure ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Critical Issues ◽  
Ontology Module ◽  
The Right

In mobile cloud computing environment, the cooperation of distributed computing objects is one of the most important requirements for providing successful cloud services. To satisfy this requirement, all the members, who are employed in the cooperation group, need to share the knowledge for mutual understanding. Even if ontology can be the right tool for this goal, there are several issues to make a right ontology. As the cost and complexity of managing knowledge increase according to the scale of the knowledge, reducing the size of ontology is one of the critical issues. In this paper, we propose a method of extracting ontology module to increase the utility of knowledge. For the given signature, this method extracts the ontology module, which is semantically self-contained to fulfill the needs of the service, by considering the syntactic structure and semantic relation of concepts. By employing this module, instead of the original ontology, the cooperation of computing objects can be performed with less computing load and complexity. In particular, when multiple external ontologies need to be combined for more complex services, this method can be used to optimize the size of shared knowledge.

An Adaptive Service Monitoring System in a Cloud Computing Environment

2020 ◽  
Vol 12 (2) ◽  
pp. 47-63
Author(s):  
Sathiyamoorthy E. ◽  
Karthikeyan P
Keyword(s):  
Cloud Computing ◽  
Rapid Development ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Cloud Environment ◽  
Computing Environment ◽  
Time Duration ◽  
Cloud Computing Environment

Cloud computing is a trending area of information technology (IT). In a cloud environment, the Cloud service provider (CSP) provides all the functionalities to the users or customers in terms of services. With the rapid development of cloud computing, the performance of any cloud environment relies on the quality of services (QoS) at the time of providing the services. A service level agreement (SLA) increases the confidence of the user or customer to use the cloud services in a cloud environment. There should be negotiation between the CSP and users to achieve a strong SLA. Many existing SLA models are already developed. However, these models do not concentrate to maintain the quality in a long-time duration period. To solve this issue, a novel SLA model has been proposed in this article by using Fuzzy logic. Both the theoretical and simulation results show the proficiency of the proposed scheme over the existing schemes in a cloud computing environment.

scholarly journals A Reliable Friedman Hypothesis-Based Detection and Adaptive Load Balancing Scheme for Mitigating Reduction of Quality DDoS Attacks in Cloud Computing

2019 ◽  
Vol 9 (1) ◽  
pp. 360-366
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Cloud Environment ◽  
Cloud Infrastructure ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
On Demand ◽  
Demand Service

The computing resource availability in a cloud computing environment is considered as the vital attribute among the security essentialities due to the consequence of on its on demand service. The class of adversaries related to the Distributed Denial of Service (DDoS) attack is prevalent in the cloud infrastructure for exploiting the vulnerabilities during the implementation of their attack that still make the process of providing security and availability at the same time as a challenging objective. In specific, The in cloud computing is the major threat during the process of balancing security and availability at the same time. In this paper, A Reliable Friedman Hypothesis-based Detection and Adaptive Load Balancing Scheme (RFALBS-RoQ-DDOS) is contributed for effective detection of RoQDDoS attacks through Friedman hypothesis testing. It also inherited an adaptive load balancing approach that prevents the degree of imbalance in the cloud environment. The simulation results of the proposed RFALBS-RoQ-DDoS technique confirmed a superior detection rate and a adaptive load balancing rate of nearly 23% and 28% predominant to the baseline DDoS mitigation schemes considered for investigation.

Sign in / Sign up

Export Citation Format

Share Document