HDFSx: An Enhanced Model to Handle Small Files in Hadoop with a Simulating Toolkit

Kafrawy, Passent M El; Sauber, Amr M.; Hafez, M.; Shawish, Amr F

doi:10.1109/cais.2018.8442036

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…There are problems of security including information loss, integrity, and botnet posing extreme threats to companies' information and software [ 8 ]. Security of sensitive data is a pressing need in trendy communication, mainly in cloud [ 9 , 10 ]. Every day, the number of people using cloud computing services increases, and lots of data have been stored in cloud computing environments.…”

Section: Introductionmentioning

confidence: 99%

A New Secure Model for Data Protection over Cloud Computing

Sauber

Elkafrawy

Shawish

et al. 2021

Computational Intelligence and Neuroscience

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The main goal of any data storage model on the cloud is accessing data in an easy way without risking its security. A security consideration is a major aspect in any cloud data storage model to provide safety and efficiency. In this paper, we propose a secure data protection model over the cloud. The proposed model presents a solution to some security issues of cloud such as data protection from any violations and protection from a fake authorized identity user, which adversely affects the security of the cloud. This paper includes multiple issues and challenges with cloud computing that impairs security and privacy of data. It presents the threats and attacks that affect data residing in the cloud. Our proposed model provides the benefits and effectiveness of security in cloud computing such as enhancement of the encryption of data in the cloud. It provides security and scalability of data sharing for users on the cloud computing. Our model achieves the security functions over cloud computing such as identification and authentication, authorization, and encryption. Also, this model protects the system from any fake data owner who enters malicious information that may destroy the main goal of cloud services. We develop the one-time password (OTP) as a logging technique and uploading technique to protect users and data owners from any fake unauthorized access to the cloud. We implement our model using a simulation of the model called Next Generation Secure Cloud Server (NG-Cloud). These results increase the security protection techniques for end user and data owner from fake user and fake data owner in the cloud.

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Section: Introductionmentioning

confidence: 99%

A New Secure Model for Data Protection over Cloud Computing

Sauber

Elkafrawy

Shawish

et al. 2021

Computational Intelligence and Neuroscience

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“…MR provides applications to work on thousands of machines and petabytes of information in parallel and in a cost-effective manner. This is accomplished by using commodity hardware to build cluster nodes as core basic components of Hadoop [ 4 – 7 ]. A Hadoop Cluster consists of a single master node that hosts the JobTracker service and a set of workers each hosting a TaskTracker service.…”

Section: Introductionmentioning

confidence: 99%

A Novel Hadoop Security Model for Addressing Malicious Collusive Workers

Sauber

Awad

Shawish

et al. 2021

Computational Intelligence and Neuroscience

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With the daily increase of data production and collection, Hadoop is a platform for processing big data on a distributed system. A master node globally manages running jobs, whereas worker nodes process partitions of the data locally. Hadoop uses MapReduce as an effective computing model. However, Hadoop experiences a high level of security vulnerability over hybrid and public clouds. Specially, several workers can fake results without actually processing their portions of the data. Several redundancy-based approaches have been proposed to counteract this risk. A replication mechanism is used to duplicate all or some of the tasks over multiple workers (nodes). A drawback of such approaches is that they generate a high overhead over the cluster. Additionally, malicious workers can behave well for a long period of time and attack later. This paper presents a novel model to enhance the security of the cloud environment against untrusted workers. A new component called malicious workers’ trap (MWT) is developed to run on the master node to detect malicious (noncollusive and collusive) workers as they convert and attack the system. An implementation to test the proposed model and to analyze the performance of the system shows that the proposed model can accurately detect malicious workers with minor processing overhead compared to vanilla MapReduce and Verifiable MapReduce (V-MR) model [1]. In addition, MWT maintains a balance between the security and usability of the Hadoop cluster.

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