Title | STADS: Security Threats Assessment and Diagnostic System in Software Defined Networking (SDN) |
Publication Type | Conference Paper |
Year of Publication | 2022 |
Authors | Sharma, Pradeep Kumar, Kumar, Brijesh, Tyagi, S.S |
Conference Name | 2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COM-IT-CON) |
Date Published | may |
Keywords | Big Data, computer network reliability, control plane, controller., data plane, machine learning, OpenFlow, Organizations, parallel processing, pubcrawl, resilience, Resiliency, Scalability, SDN, SDN security, security, software reliability, Threat Assessment |
Abstract | Since the advent of the Software Defined Networking (SDN) in 2011 and formation of Open Networking Foundation (ONF), SDN inspired projects have emerged in various fields of computer networks. Almost all the networking organizations are working on their products to be supported by SDN concept e.g. openflow. SDN has provided a great flexibility and agility in the networks by application specific control functions with centralized controller, but it does not provide security guarantees for security vulnerabilities inside applications, data plane and controller platform. As SDN can also use third party applications, an infected application can be distributed in the network and SDN based systems may be easily collapsed. In this paper, a security threats assessment model has been presented which highlights the critical areas with security requirements in SDN. Based on threat assessment model a proposed Security Threats Assessment and Diagnostic System (STADS) is presented for establishing a reliable SDN framework. The proposed STADS detects and diagnose various threats based on specified policy mechanism when different components of SDN communicate with controller to fulfil network requirements. Mininet network emulator with Ryu controller has been used for implementation and analysis. |
DOI | 10.1109/COM-IT-CON54601.2022.9850804 |
Citation Key | sharma_stads_2022 |