Security challenges in software defined network and their solutions

Patil, Varsha P.; C.H.Patil,; Awale, R. N.

doi:10.1109/icccnt.2017.8203978

Cited by 9 publications

(2 citation statements)

References 16 publications

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“…That is to cut the upper application environment of different tenants at the bottom process level and ensure the mutual isolation of tenant process communication. The software-defined network (SDN) [12,13] mainly refers to a new network architecture based on network virtualization, which separates the control plane and the data plane of network equipment. By increasing the programmability of the network, it innovates the current partial static and configures a complex network architecture; further, the network can be dynamically constructed according to the application requirements of the upper tenants.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Control Method for Tenants’ Sensitive Information Flow Based on Virtual Boundary Recognition

Lu¹,

Cao²,

Du³

2020

IEEE Access

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In the cloud environment, owing to the large-scale sharing of the upper application instance and the underlying virtual machine resources, the tenants' information flow boundary in the shared virtual machine is fuzzy and difficult to identify. In addition, protection of tenant information flow between processes is inadequate, resulting in the leakage of sensitive information of tenants. Therefore, a dynamic control method for tenants' sensitive information flow based on virtual boundary recognition is proposed. By analyzing the behavior and operation log of tenants, the behavior feature vectors of tenants are constructed, and an automatic recognition algorithm of tenant virtual boundary based on the dynamic spiking neural network is designed. This algorithm can realize dynamic identification of the tenant virtual security boundary when the application service demand changes dynamically. Further, combined with the concept of centralized and decentralized information flow control, a dynamic control method of sensitive information flow is established. The security label is formally defined by using the lattice structure, and the control rules of tenants' information flow and the rules of tenant label encryption-declassification are designed. Thus, the independent, dynamic and secure control of tenants' information flow inside and outside the tenant virtual boundary. Finally, the detailed design of a dynamic security control application system for cloud tenants' sensitive information flow is provided. Experiments confirm that the proposed algorithm can identify the security boundary of tenants more accurately and efficiently than the traditional spiking neural network classification methods. Further, the security and effectiveness of the method is verified by the intransitive noninterference theory and the experiment of information flow control.

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Section: Related Workmentioning

confidence: 99%

Dynamic Control Method for Tenants’ Sensitive Information Flow Based on Virtual Boundary Recognition

Lu¹,

Cao²,

Du³

2020

IEEE Access

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“…The capability of the centralized architecture used in the network is furthermore enhanced as it can now segregate the control plane to forwarding plane and can further offer more extensive programming capability to the network [4,5]. Irrespective of immense advantage, there are various security issues associated with the SDN [6][7][8][9][10]. Apart from the problem associated with the failure of a centralized point in the legacy centralized architecture, the SDN offers a mechanism using its controller system in order to study the security.…”

Section: Introductionmentioning

confidence: 99%

Preemptive modelling towards classifying vulnerability of DDoS attack in SDN environment

Narender¹,

Yuvaraju²

2020

IJECE

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Software-Defined Networking (SDN) has become an essential networking concept towards escalating the networking capabilities that are highly demanded future internet system, which is immensely distributed in nature. Owing to the novel concept in the field of network, it is still shrouded with security problems. It is also found that the Distributed Denial-of-Service (DDoS) attack is one of the prominent problems in the SDN environment. After reviewing existing research solutions towards resisting DDoS attack in SDN, it is found that still there are many open-end issues. Therefore, these issues are identified and are addressed in this paper in the form of a preemptive model of security. Different from existing approaches, this model is capable of identifying any malicious activity that leads to a DDoS attack by performing a correct classification of attack strategy using a machine learning approach. The paper also discusses the applicability of best classifiers using machine learning that is effective against DDoS attack.

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Impacts of blockchain in software‐defined Internet of Things ecosystem with Network Function Virtualization for smart applications: Present perspectives and future directions

Rahman

Islam

Kundu

et al. 2023

Int J Communication

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SummaryAs an emerging technology, blockchain (BC) has been playing a promising role in today's software‐defined networking (SDN)‐enabled Internet of Things (IoT) applications. Because of the salient feature of the network function virtualization (NFV) techniques, SDN can ensure an IoT system runs efficiently and smoothly in a cloud‐driven ecosystem. When cloud‐enabled systems encounter immense security and operational challenges caused mainly by third‐party dependency, large‐scale data communication, and maintenance, BC offers effective and robust data transfer solutions without incorporating intermediaries over the distributed network. With the increased SDN‐BC convergence in the IoT domain, the underlying challenges and perspectives deserve proper attention methodically and structurally. From the motivation of addressing such issues, this study provides necessary insights to combine those for successful plug‐and‐play. Therefore, the study includes purposefully investigating current state‐of‐the‐art to extract the research trends, future directions, and perspectives in this domain. This study provides a comprehensive survey of IoT, SDN, NFV, and BC‐enabled emerging technologies. More importantly, the authors intelligently integrated the four different technologies—IoT, SDN, BC, and NFV based on characteristics, scopes, challenges, taxonomies, and tables in numerous areas. Initially, the authors introduce the SDN‐IoT ecosystem in brief and address the features and applications. We took a close look at the SDN's overall taxonomy based on security, environment, scopes, and challenges. We also briefly describe the integration of SDN‐IoT with the NFV ecosystems. Moreover, we review the prospect of BC technology from security perspectives, its extent, challenges of practical implementation, and the possible integration of IoT regarding smart applications. Finally, this study highlights several future directions based on these technologies.

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Security challenges in software defined network and their solutions

Cited by 9 publications

References 16 publications

Dynamic Control Method for Tenants’ Sensitive Information Flow Based on Virtual Boundary Recognition

Dynamic Control Method for Tenants’ Sensitive Information Flow Based on Virtual Boundary Recognition

Preemptive modelling towards classifying vulnerability of DDoS attack in SDN environment

Impacts of blockchain in software‐defined Internet of Things ecosystem with Network Function Virtualization for smart applications: Present perspectives and future directions

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