A Novel Hadoop Security Model for Addressing Malicious Collusive Workers
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, H...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , |
| Published: |
2021
|
| Online Access: | https://bspace.buid.ac.ae/handle/1234/2931 https://onlinelibrary.wiley.com/doi/full/10.1155/2021/5753948 https://doi.org/10.1155/2021/5753948 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1862980618013376512 |
|---|---|
| author | M. Sauber, Amr |
| author2 | Awad, Ahmed F. Shawish, Amr M. El-Kafrawy, Passent |
| author2_role | author author author |
| author_facet | M. Sauber, Amr Awad, Ahmed F. Shawish, Amr M. El-Kafrawy, Passent |
| author_role | author |
| dc.creator.none.fl_str_mv | M. Sauber, Amr Awad, Ahmed F. Shawish, Amr M. El-Kafrawy, Passent |
| dc.date.none.fl_str_mv | 2021 2025-05-06T09:21:25Z 2025-05-06T09:21:25Z |
| dc.identifier.none.fl_str_mv | Sauber, A.M. et al. (2021) “A Novel Hadoop Security Model for Addressing Malicious Collusive Workers,” Computational Intelligence and Neuroscience : CIN, 2021. 1687-5265, 1687-5273 https://bspace.buid.ac.ae/handle/1234/2931 https://onlinelibrary.wiley.com/doi/full/10.1155/2021/5753948 https://doi.org/10.1155/2021/5753948 |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | ProQuest Central |
| dc.relation.none.fl_str_mv | Computational Intelligence and Neuroscience : CINv2021 (2021) |
| dc.title.none.fl_str_mv | A Novel Hadoop Security Model for Addressing Malicious Collusive Workers |
| dc.type.none.fl_str_mv | Article |
| description | 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. *is 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 |
| id | budr_db1476ce8aae4f29f5c5b13398fad481 |
| identifier_str_mv | Sauber, A.M. et al. (2021) “A Novel Hadoop Security Model for Addressing Malicious Collusive Workers,” Computational Intelligence and Neuroscience : CIN, 2021. 1687-5265, 1687-5273 |
| language_invalid_str_mv | en |
| network_acronym_str | budr |
| network_name_str | The British University in Dubai repository |
| oai_identifier_str | oai:bspace.buid.ac.ae:1234/2931 |
| publishDate | 2021 |
| publisher.none.fl_str_mv | ProQuest Central |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | A Novel Hadoop Security Model for Addressing Malicious Collusive WorkersM. Sauber, AmrAwad, AhmedF. Shawish, AmrM. El-Kafrawy, PassentWith 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. *is 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 clusterProQuest Central2025-05-06T09:21:25Z2025-05-06T09:21:25Z2021ArticleSauber, A.M. et al. (2021) “A Novel Hadoop Security Model for Addressing Malicious Collusive Workers,” Computational Intelligence and Neuroscience : CIN, 2021.1687-5265, 1687-5273https://bspace.buid.ac.ae/handle/1234/2931https://onlinelibrary.wiley.com/doi/full/10.1155/2021/5753948https://doi.org/10.1155/2021/5753948enComputational Intelligence and Neuroscience : CINv2021 (2021)oai:bspace.buid.ac.ae:1234/29312025-08-13T07:41:44Z |
| spellingShingle | A Novel Hadoop Security Model for Addressing Malicious Collusive Workers M. Sauber, Amr |
| title | A Novel Hadoop Security Model for Addressing Malicious Collusive Workers |
| title_full | A Novel Hadoop Security Model for Addressing Malicious Collusive Workers |
| title_fullStr | A Novel Hadoop Security Model for Addressing Malicious Collusive Workers |
| title_full_unstemmed | A Novel Hadoop Security Model for Addressing Malicious Collusive Workers |
| title_short | A Novel Hadoop Security Model for Addressing Malicious Collusive Workers |
| title_sort | A Novel Hadoop Security Model for Addressing Malicious Collusive Workers |
| url | https://bspace.buid.ac.ae/handle/1234/2931 https://onlinelibrary.wiley.com/doi/full/10.1155/2021/5753948 https://doi.org/10.1155/2021/5753948 |