Detection Of Dynamic Vulnerabilites In Hadoop Systems For Controlling The Fuzzy Adaptive Security Profiles (FASP)
Main Article Content
Abstract
Hadoop is big data processing framework with capability to process large volumes of data using map reduce parallel processing paradigm. Big data analytics on these large volumes of information provides various intelligent information for business process optimization and governance. With wide acceptance of Hadoop for big data analytics, there is also an increased security vulnerability. In our earlier work [1], Fuzzy Adaptive Security Profile (FASP) was proposed to provide increased security to Hadoop processing platform. The work has shortcoming in terms of protection against wide variety of security vulnerabilities. The approach considered only denial of service attack. Common vulnerability Exposure (CVE) has detailed 23 different vulnerabilities in Hadoop and this work designs a vulnerability scanner based on Hidden Markov model to detect the CVE attacks specific to Hadoop. The designed vulnerability scanner is integrated with FASP using an adaptive security scoring technique to trigger adaptive mitigation mechanisms.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.