scholarly journals Dolus : cyber defense using pretense against DDoS attacks in cloud platforms

2017 ◽  
Author(s):  
◽  
Roshan Lal Neupane
Keyword(s):  
Virtual Machines ◽  
Service Providers ◽  
Denial Of Service ◽  
Cloud Service ◽  
Cloud Services ◽  
Ddos Attacks ◽  
Child Play ◽  
Original Target ◽  
Multiple Network ◽  
The Impact

Cloud-hosted services are being increasingly used in online businesses in e.g., retail, healthcare, manufacturing, entertainment due to benefits such as scalability and reliability. These benefits are fueled by innovations in orchestration of cloud platforms that make them totally programmable as Software Defined everything Infrastructures (SDxI). At the same time, sophisticated targeted attacks such as Distributed Denial-of-Service (DDoS) are growing on an unprecedented scale threatening the availability of online businesses. In this thesis, we present a novel defense system called Dolus to mitigate the impact of DDoS attacks launched against high-value services hosted in SDxI-based cloud platforms. Our Dolus system is able to initiate a pretense in a scalable and collaborative manner to deter the attacker based on threat intelligence obtained from attack feature analysis in a two-stage ensemble learning scheme. Using foundations from pretense theory in child play, Dolus takes advantage of elastic capacity provisioning via quarantine virtual machines and SDxI policy co-ordination across multiple network domains. To maintain the pretense of false sense of success after attack identification, Dolus uses two strategies: (i) dummy traffic pressure in a quarantine to mimic target response time profiles that were present before legitimate users were migrated away, and (ii) Scapy-based packet manipulation to generate responses with spoofed IP addresses of the original target before the attack traffic started being quarantined. From the time gained through pretense initiation, Dolus enables cloud service providers to decide on a variety of policies to mitigate the attack impact, without disrupting the cloud services experience for legitimate users. We evaluate the efficacy of Dolus using a GENI Cloud testbed and demonstrate its real-time capabilities to: (a) detect DDoS attacks and redirect attack traffic to quarantine resources to engage the attacker under pretense, and (b) coordinate SDxI policies to possibly block DDoS attacks closer to the attack source(s).

Security of the Cloud

2015 ◽  
pp. 363-404 ◽  
Author(s):  
Khalid Al-Begain ◽  
Michal Zak ◽  
Wael Alosaimi ◽  
Charles Turyagyenda
Keyword(s):  
Service Providers ◽  
Denial Of Service ◽  
Cloud Service ◽  
Future Research ◽  
Cloud Environment ◽  
Ddos Attacks ◽  
Security Attacks ◽  
Edos Attacks ◽  
Future Research Directions ◽  
Cloud Users

The chapter presents current security concerns in the Cloud Computing Environment. The cloud concept and operation raise many concerns for cloud users since they have no control of the arrangements made to protect the services and resources offered. Additionally, it is obvious that many of the cloud service providers will be subject to significant security attacks. Some traditional security attacks such as the Denial of Service attacks (DoS) and distributed DDoS attacks are well known, and there are several proposed solutions to mitigate their impact. However, in the cloud environment, DDoS becomes more severe and can be coupled with Economical Denial of Sustainability (EDoS) attacks. The chapter presents a general overview of cloud security, the types of vulnerabilities, and potential attacks. The chapter further presents a more detailed analysis of DDoS attacks' launch mechanisms and well-known DDoS defence mechanisms. Finally, the chapter presents a DDoS-Mitigation system and potential future research directions.

Security of the Cloud

2018 ◽  
pp. 1511-1554
Author(s):  
Khalid Al-Begain ◽  
Michal Zak ◽  
Wael Alosaimi ◽  
Charles Turyagyenda
Keyword(s):  
Service Providers ◽  
Denial Of Service ◽  
Cloud Service ◽  
Future Research ◽  
Cloud Environment ◽  
Ddos Attacks ◽  
Security Attacks ◽  
Edos Attacks ◽  
Future Research Directions ◽  
Cloud Users

The chapter presents current security concerns in the Cloud Computing Environment. The cloud concept and operation raise many concerns for cloud users since they have no control of the arrangements made to protect the services and resources offered. Additionally, it is obvious that many of the cloud service providers will be subject to significant security attacks. Some traditional security attacks such as the Denial of Service attacks (DoS) and distributed DDoS attacks are well known, and there are several proposed solutions to mitigate their impact. However, in the cloud environment, DDoS becomes more severe and can be coupled with Economical Denial of Sustainability (EDoS) attacks. The chapter presents a general overview of cloud security, the types of vulnerabilities, and potential attacks. The chapter further presents a more detailed analysis of DDoS attacks' launch mechanisms and well-known DDoS defence mechanisms. Finally, the chapter presents a DDoS-Mitigation system and potential future research directions.

scholarly journals Energy-Aware Autonomic Resource Scheduling Framework for Cloud

2019 ◽  
Vol 4 (1) ◽  
pp. 41-55 ◽  
Author(s):  
Bhupesh Kumar Dewangan ◽  
Amit Agarwal ◽  
Venkatadri M. ◽  
Ashutosh Pasricha
Keyword(s):  
Energy Consumption ◽  
Resource Utilization ◽  
Data Centers ◽  
Virtual Machines ◽  
Service Providers ◽  
Optimal Solution ◽  
Cloud Service ◽  
Cloud Services ◽  
Energy Aware ◽  
Increasing Demand

Cloud computing is a platform where services are provided through the internet either free of cost or rent basis. Many cloud service providers (CSP) offer cloud services on the rental basis. Due to increasing demand for cloud services, the existing infrastructure needs to be scale. However, the scaling comes at the cost of heavy energy consumption due to the inclusion of a number of data centers, and servers. The extraneous power consumption affects the operating costs, which in turn, affects its users. In addition, CO2 emissions affect the environment as well. Moreover, inadequate allocation of resources like servers, data centers, and virtual machines increases operational costs. This may ultimately lead to customer distraction from the cloud service. In all, an optimal usage of the resources is required. This paper proposes to calculate different multi-objective functions to find the optimal solution for resource utilization and their allocation through an improved Antlion (ALO) algorithm. The proposed method simulated in cloudsim environments, and compute energy consumption for different workloads quantity and it increases the performance of different multi-objectives functions to maximize the resource utilization. It compared with existing frameworks and experiment results shows that the proposed framework performs utmost.

Empirical Performance Assessment of Public Clouds Using System Level Benchmarks

2013 ◽  
Vol 3 (4) ◽  
pp. 81-91 ◽  
Author(s):  
Sanjay P. Ahuja ◽  
Thomas F. Furman ◽  
Kerwin E. Roslie ◽  
Jared T. Wheeler
Keyword(s):  
Virtual Machines ◽  
Service Providers ◽  
Cluster Formation ◽  
Cloud Service ◽  
Cloud Services ◽  
System Level ◽  
Processing Unit ◽  
Central Processing ◽  
Empirical Performance ◽  
Set Up

Amazon's Elastic Compute Cloud (EC2) Service is one of the leading public cloud service providers and offers many different levels of service. This paper looks into evaluating the memory, central processing unit (CPU), and input/output I/O performance of two different tiers of hardware offered through Amazon's EC2. Using three distinct types of system benchmarks, the performance of the micro spot instance and the M1 small instance are measured and compared. In order to examine the performance and scalability of the hardware, the virtual machines are set up in a cluster formation ranging from two to eight nodes. The results show that the scalability of the cloud is achieved by increasing resources when applicable. This paper also looks at the economic model and other cloud services offered by Amazon's EC2, Microsoft's Azure, and Google's App Engine.

The Role of Individualization and Project Learning for Cloud Service Profitability

2018 ◽  
Vol 16 (2) ◽  
pp. 64-82
Author(s):  
Alexander Herzfeldt ◽  
Thomas Wolfenstetter ◽  
Christoph Ertl ◽  
Helmut Krcmar
Keyword(s):  
Service Delivery ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
It Industry ◽  
Project Learning ◽  
Delivery Costs ◽  
Cloud Service Providers ◽  
The Impact

This article describes how cloud computing has been one of the most important IT topics in recent years. In increasingly greater numbers, service providers have entered this dynamic market turning it into one of the most competitive markets in modern IT industry. As the market matures, many providers are struggling with profitability issues. Studies on cloud services have primarily approached the topic from a technical or customer's perspective, neglecting the provider's perspective. In this article, the authors address business aspects of cloud services from the provider's perspective. Based on an empirical study of 78 cloud service providers, they analyse the impact of service individualization and project learning on service delivery cost and profitability. The results indicate that while project learning merely helps to reduce service delivery costs, service individualization positively affects profitability.

SCEF: A Model for Prevention of DDoS Attacks From the Cloud

2020 ◽  
Vol 10 (3) ◽  
pp. 67-80 ◽  
Author(s):  
Ganeshayya Ishwarayya Shidaganti ◽  
Amogh Shreedhar Inamdar ◽  
Sindhuja V. Rai ◽  
Anagha M. Rajeev
Keyword(s):  
Network Performance ◽  
Virtual Machines ◽  
Denial Of Service ◽  
Cloud Service ◽  
Packet Transmission ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Virtual Machine Monitor ◽  
Cloud Service Provider ◽  
Different Types

Distributed denial of service (DDoS) attacks are some of the biggest threats to network performance and security today. With the advent of cloud computing, these attacks can be performed remotely on rented virtual machines (VMs), potentially increasing their capabilities and making them harder to trace and mitigate, and negatively affecting the cloud service provider as well. By analyzing packet transmission statistics, attacks can be detected on a virtual machine monitor (VMM) that controls the behavior of the VMs. This article proposes a solution to stop such detected attacks from the source, and analyses solutions proposed for a few different types of such attacks. The authors propose a model called selective cloud egress filter (SCEF) which implements specific modules to deal with detected attacks. If an attack is detected, the SCEF relays information to the VMM about which VMs are participating in the attack, allowing for specific corrective action.

scholarly journals Improved DDoS Attacks Detection using Hybrid Statistical Model and Sparse Representation for Cloud Computing

2019 ◽  
Vol 8 (10) ◽  
pp. 32-37
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Denial Of Service ◽  
Cloud Service ◽  
Ddos Attacks ◽  
Service Accessibility ◽  
Ddos Attack ◽  
Redundant Data ◽  
Cloud Computing Service ◽  
Cloud Service Providers

While hosting various cloud based information technology facilities by handling various assets on the internet, Cloud service accessibility has remained one of the chief concerns of cloud service providers (CSP). Several security concerns associated to cloud computing service simulations, and cloud’s major qualities contribute towards its susceptibility of security threats related with cloud service availability, the liability of internet, and the dispense behavior of cloud computing. Distributed Denial of Service (DDoS) attacks is one of the main advanced threats that occur to be extremely problematic and stimulating to stand owing towards its dispersed behavior and resulted in cloud service interruption. Although there exist amount of interruption recognition resolutions anticipated by various investigation groups, there exists not at all such a faultless result that avoids the DDoS attack and cloud service providers (CSP) are presently consuming various detection resolutions by assuring that their product stays well protected. The features of DDoS attack consuming various forms with dissimilar scenarios make it problematic to identify. Inspecting and analyzing various surviving DDoS detecting methods contrary to several factors is accomplished by this paper. To enhance the system performance further, sparse based data optimization is proposed to remove the redundant data. This enhancement reduced the execution time of the system by0.2%.

Minimized False Alarm predictive Threshold for Cloud Service Providers

2019 ◽  
Vol 12 ◽  
Author(s):  
Amandeep Singh Arora ◽  
Linesh Raja ◽  
Barkha Bahl
Keyword(s):  
Machine Learning ◽  
Cross Validation ◽  
Service Providers ◽  
Denial Of Service ◽  
Cloud Service ◽  
Machine Learning Algorithms ◽  
Cloud Services ◽  
Estimation Accuracy ◽  
Denial Of Service Attacks

Cloud Security is a strong hindrance which discourage organizations to move toward cloud despite huge benefits. Denial of Service attacks [1] operated via distributed systems compromise availability of cloud services. Techniques to identify distributed denial of service attacks with minimized false positives is highly required to ensure availability of cloud services to genuine users. Classification of incoming requests and outgoing responses using machine learning algorithms is a quite effective way of detection and prevention. In this paper, Ten algorithms of machine learning have been evaluated for performance and detection accuracies. An estimation accuracy method known as F-Hold cross validation [2] is used for time efficient analysis.

scholarly journals Profit Maximization for Cloud Broker in Cloud Computing

2021 ◽  
Vol 9 (VII) ◽  
pp. 354-359
Author(s):  
Prof. M. S. Namose
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Providers ◽  
Current System ◽  
Profit Maximization ◽  
Cloud Service ◽  
Cloud Services ◽  
Market Demand ◽  
Cloud Broker ◽  
The Cost

As cloud computing evolves, more and more applications are moving to the cloud. Cloud brokers are are like Middlemen between cloud service providers and cloud users. Thus, cloud brokers can significantly reduce the cost of consumers. In addition to reducing the cost per user, the cloud broker can also accommodate the price difference between on-demand virtual machines and dedicated virtual machines. The problem with the current system is that if many customers request a large amount of cloud services at once, the cloud service broker cannot purchase enough cloud services from CSP to meet the needs of all customers. Then there is a peak demand problem where the customer cannot complete the job. As a result, dynamic conditions not only lead to financial problems, but can also negatively impact the customer experience. To solve this problem, the system focuses on guaranteed quality of service for all requests, reduces waste of resources, increases security and maximizes revenue. All jobs are scheduled by the job scheduler and assigned to different VMs in a centralized way. Many factors such as market demand, application volume, SLA, service rental cost, etc. are taken into account to formulate an optimal configuration problem of profit maximization.

scholarly journals A Generic Model for Identifying QoS Parameters Interrelations in Cloud Services Selection Ontology during Runtime

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 563
Author(s):  
Babu Rajendiran ◽  
Jayashree Kanniappan
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Operating Costs ◽  
Generic Model ◽  
Business Organizations ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Qos Parameters ◽  
Computer Based

Nowadays, many business organizations are operating on the cloud environment in order to diminish their operating costs and to select the best service from many cloud providers. The increasing number of Cloud Services available on the market encourages the cloud consumer to be conscious in selecting the most apt Cloud Service Provider that satisfies functionality, as well as QoS parameters. Many disciplines of computer-based applications use standardized ontology to represent information in their fields that indicate the necessity of an ontology-based representation. The proposed generic model can help service consumers to identify QoS parameters interrelations in the cloud services selection ontology during run-time, and for service providers to enhance their business by interpreting the various relations. The ontology has been developed using the intended attributes of QoS from various service providers. A generic model has been developed and it is tested with the developed ontology.

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