Matching Between SIEM Tools and Smart DLC Systems
Mohammed EL ARASS1, Iman TIKITO2, Nissrine SOUISSI3
1Mohammed EL ARASS*, Mohammed V University in Rabat, EMI-SIWEB Team, Rabat Morocco.
2Iman TIKITO, Mohammed V University in Rabat, EMI-SIWEB Team, Rabat Morocco.
3Nissrine SOUISSI, Mines-Rabat School, Department of Computer Science, Rabat Morocco.
Manuscript received on November 11, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on 30 November, 2019. | PP: 4475-4482 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8414118419/2019©BEIESP | DOI: 10.35940/ijrte.D8414.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Nowadays, cybersecurity data management has become a challenging issue especially with the emergence of Big Data. This paper introduces the System of Systems (SoS) paradigm to design a new generation SIEM POC (Security Information Event Management Proof Of Concept) made up of an open source Big Data platform ELK and integrated with other open source security and load-balancing tools. To do this, we first focused on the Big Data and Smart Data requirements to model a data lifecycle from the literature named Smart DLC to the System of 7 Systems, So7S. Second, we used the proposed cycle as SoS tools design, implement and test the proposed SIEM POC by matching the cybersecurity tools to each system of the SoS modeled. The proposed open source SIEM is operational and meets all cybersecurity monitoring requirements with challenging results and may interest small and medium-sized companies dealing with cybersecurity issues.
Keywords: Big Data, Cybersecurity, Data Life Cycle, Smart DLC, Security Information Event Management, System of Systems.
Scope of the Article: Big Data Security.