scholarly journals Previously-Selected-Server-First based Scalable VM Placement Algorithm for Mitigating Side Channel Attacks in Cloud Computing

2018 ◽  
Vol 8 (1) ◽  
pp. 50-59
Author(s):  
Adi Maheswara Reddy G ◽  
◽  
K Venkata Rao ◽  
JVR Murthy
Keyword(s):  
Cloud Computing ◽  
Side Channel ◽  
Side Channel Attacks ◽  
Vm Placement ◽  
Placement Algorithm

Adaptive multilevel fuzzy-based authentication framework to mitigate Cache side channel attack in cloud computing

2018 ◽  
Vol 09 (05) ◽  
pp. 1850045 ◽  
Author(s):  
Bharati Ainapure ◽  
Deven Shah ◽  
A. Ananda Rao
Keyword(s):  
Cloud Computing ◽  
Private Information ◽  
Privacy Preservation ◽  
Virtual Machines ◽  
Fuzzy Rule ◽  
Data Access ◽  
Side Channel ◽  
Side Channel Attack ◽  
Side Channel Attacks ◽  
Cloud Providers

Cloud computing supports multitenancy to satisfy the users’ demands for accessing resources and simultaneously it increases revenue for cloud providers. Cloud providers adapt multitenancy by virtualizing the resources, like CPU, network interfaces, peripherals, hard drives and memory using hypervisor to fulfill the demand. In a virtualized environment, many virtual machines (VMs) can run on the same core with the help of the hypervisor by sharing the resources. The VMs running on the same core are the target for the malicious or abnormal attacks like side channel attacks. Among various side channel attacks in cloud computing, cache-based side channel attack is one that leaks private information of the users based on the shared resources. Here, as the shared resource is the cache, a process can utilize the cache usage of another by cache contention. Cache sharing provides a way for the attackers to gain considerable information so that the key used for encryption can be inferred. Discovering this side channel attack is a challenging task. This requires identification of a feature that influences the attack. Even though there are various techniques available in the literature to mitigate such attacks, an effective solution to reduce the cache-based side channel attack is still an issue. Therefore, a novel fuzzy rule-based mechanism is integrated to detect the cache side channel attackers by monitoring the cache data access (CDA). The factor that determines the attack is CDA in a log file created by the framework during authorization. The proposed framework also utilizes certain security properties including ECC and hashing for the privacy preservation and the decision is made with the aid of a fuzzy logic system.

scholarly journals Power Management as a Service (Pmaas) – An Energy Saving Service by ―Auto-Fit VM Placement‖ Algorithm in Cloud Computing for Maximum Resource Utilization at Minimum Energy Consumption Without Live-Migrating the Virtual Machines by using the Concept of Virtual-Servers

2019 ◽  
Vol 9 (2) ◽  
pp. 1437-1446
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Power Consumption ◽  
Power Management ◽  
Resource Utilization ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Memory Storage ◽  
Vm Placement ◽  
Placement Algorithm

Now a day Energy Consumption is one of the most promising fields amongst several computing services of cloud computing. A maximum amount of Power resources are absorbed by the data centre because of huge amount of data processing which is increased abnormally. So it’s the time to think about the energy consumption in cloud environment. Existing Energy Consumption systems are limited in terms of virtualization because improper virtualization leads to loads imbalance and excessive power consumption and inefficiency in terms of computational power. Billing[1,2 ] is another exciting feature that is closely related to energy consumption, because higher or lesser billing depends on energy consumption somehow-as we know that cloud providers allow cloud users to access resources as pay-per-use, so these resources need to be optimally selected to process the user request to maximize user satisfaction in the distributed virtualized environment. There may be an inequity between the actual power consumption by the users and the provided billing records by the providers, So any false accusation that may claimed by each other to get illegal compensations. To avoid such accusation, we propose a work to consolidate the VMs using the Power Management as a Service (PMaaS) model in such a way, to reduce power consumption by maximum resource utilization without live-migration of the virtual machines by using the concept of Virtual Servers. The proposed PMaaS model uses a new “Auto-fit VM placement algorithm”, which computes tasks resource demands, models a Virtual Machine that fits those demands, and places the Virtual Machines on a Virtual server made by the collective resources (CPU, Memory, Storage and Bandwidth) from the respective schedulers directly connected to the actual physical servers and that has the minimum remaining resources which is large enough to accommodate such a Virtual Machine.

scholarly journals Task Based Virtual Machine Placement in Cloud

2020 ◽  
Vol 9 (5) ◽  
pp. 1994-1998
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Test System ◽  
Vm Placement ◽  
Cloud Architecture ◽  
Use Of Resources ◽  
Placement Algorithm

Cloud computing offers many advantages by optimizing various parameters to meet the complex requirements .Some of the problems of cloud computing are utilization of resources and less energy consumption. More research and resources heterogeneity complicates the consolidation problem inside cloud architecture. VM placement refers to an ideal mapping of a task to virtual machines (VM) and virtual machines to physical machines (PM). The task-based VM placement algorithm is introduced in this research work. Here tasks are divided in accordance with their requirements, and then search for appropriate VM, again searching for appropriate PM, where selected VM could be sent. The algorithm decreases the use of resources by devaluation of the number of dynamic PMs while further decreases the rate of dismissal of make span and assignment. CloudSim test System is used to evaluate our algorithm in this research work. The outcomes of this implementation show the effectiveness of some current algorithms such as Round robin and Shortest Job First (SJF) algorithms.

Side Channel Attacks in Cloud Computing

2019 ◽  
pp. 77-98 ◽  
Author(s):  
Ramanujam Elangovan ◽  
Prianga M.
Keyword(s):  
Cloud Computing ◽  
Statistical Methods ◽  
Personal Computer ◽  
Service Provider ◽  
The Internet ◽  
Side Channel ◽  
Law And Order ◽  
Side Channel Attack ◽  
Side Channel Attacks ◽  
Privacy Concerns

Cloud computing is used for storing and managing information using the remote servers, which is hosted on the internet instead of storing it in a normal server or personal computer. The main purpose of why most of the companies use the cloud for storing and managing data is to not have to pay money for storing data. The main aim is to allow users to benefit from all technologies. Virtualization is considered to be the main technology of cloud computing. Several privacy concerns are caused by the cloud because the service provider can access the data at any time. Cloud providers can also share the information for the purpose of law and order. The information gathered from the physical implementation is called a side channel attack. Some technical knowledge is required for side channel attacks and these attacks are based on statistical methods. It works by monitoring the security critical operations. The side channel attack is based on the information which is leaking and the information which is kept secret.

Sign in / Sign up

Export Citation Format

Share Document