SUESSA: Sustainable & Ultra-Elastic Stack Security Architecture for Securing IoT Networks of Future Smart Cities
Authors:
- 1 November 2020
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 387-390
Abstract
Recently, the concept of a super smart city has received special attention and has become the most popular agenda among city planners, policy makers and IT industries around the globe. In this paper, we proposed a novel Sustainable Ultra-Elastic Stack Security Architecture (SUESSA) which can address various future security challenges of artificial intelligence (AI), big data and communication networks. Our architecture employs the holistic approach based on sustainability of network security which is different than that of the prevailing security practices. We propose to apply the sustainable approach in the Network security architecture through augmentation of cloud, networks and end-point level, our approach provides a robust and ultra-elastic mechanism of security that surpasses the prevailing architecture. We evaluated the feasibility and performance of the security stack containing a machine learning component, Elastic search engine, Kibana and Logstash as the building blocks of the architecture. Based on our survey, SUESSA architecture overcomes the disadvantages of current architecture specifically solving the problem of sustainability strongly demanded in security architecture of the future smart cities.Keywords
Funding Information
- Japan Society for the Promotion of Science
This publication has 9 references indexed in Scilit:
- CAMLPAD: Cybersecurity Autonomous Machine Learning Platform for Anomaly Detection2020
- A Survey on Big Data for Network Traffic Monitoring and AnalysisIEEE Transactions on Network and Service Management, 2019
- Architectural Tactics for Big Data Cybersecurity Analytics Systems: A ReviewJournal of Systems and Software, 2019
- Cyber Security Attacks on Smart Cities and Associated Mobile TechnologiesProcedia Computer Science, 2017
- A survey of approaches combining safety and security for industrial control systemsReliability Engineering & System Safety, 2015
- Towards the Model-Driven Engineering of Secure yet Safe Embedded SystemsElectronic Proceedings in Theoretical Computer Science, 2014
- Traffic classification based on port connection pattern2011
- Unexpected means of protocol inference2006
- Machine learning approaches to power-system security assessmentIEEE Expert, 1997