SODA: A software-defined security framework for IoT environments

Kim, Yeonkeun; Nam, Jaehyun; Park, Taejune; Scott-Hayward, Sandra; Shin, Seungwon

doi:10.1016/j.comnet.2019.106889

Cited by 31 publications

(16 citation statements)

References 24 publications

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“…This taxonomy process produces the following eight categories, are shown in Figure 3 with their included number of publications: Authentication : [ 12 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , ...…”

Section: Taxonomy and Trendsmentioning

confidence: 99%

Systematic Review of Authentication and Authorization Advancements for the Internet of Things

Trnka

Abdelfattah

Shrestha

et al. 2022

Sensors

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Technologies for the Internet of Things (IoT) are maturing, yet no common standards dictate their direction, leaving space for a plethora of research directions and opportunities. Among the most important IoT topics is security. When we design a robust system, it is important to know the available options for facing common tasks related to access control, authentication, and authorization. In this review, we systematically analyze 1622 peer-reviewed publications from October 2017 to December 2020 to find the taxonomy of security solutions. In addition, we assess and categorize current practices related to IoT security solutions, commonly involved technologies, and standards applied in recent research. This manuscript provides a practical road map to recent research, guiding the reader and providing an overview of recent research efforts.

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Section: Taxonomy and Trendsmentioning

confidence: 99%

Systematic Review of Authentication and Authorization Advancements for the Internet of Things

Trnka

Abdelfattah

Shrestha

et al. 2022

Sensors

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“…The mechanism was demonstrated to be efficient against brute force and DDoS attacks. Kim et al 138 used NFV to provide security services within the gateway and SDN controller to manage traffic flow. The mechanism seems to handle policy resolution automatically, achieve access control and perform security functions that are successful at Botnet and brute force attack mitigation.…”

Section: Heterogeneous Sdn-and Nfv-based Solutionsmentioning

confidence: 99%

A comprehensive survey on secure software‐defined network for the Internet of Things

Mohamed

Alofe

Azad

et al. 2021

Trans Emerging Tel Tech

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The Internet of Things (IoT) is the network of smart devices, sensors, and machines that continuously monitored the surrounding environment and execute meaningful decisions on the data or information it receives. The Internet-enabled devices could facilitate computer-mediated strategies for various tasks, for example, smart health care, managing the cities or smart factories, smart manufacturing, automating the home and business, etc. IoT commonly uses Internet technology for establishing communication among devices, thus inherits all the security threats that are currently affecting Internet users along with other security threats that are specific to IoTs due to resources constrained nature of the smart devices and sensors. The greater footprint, the distributed nature of the network and the existence of a huge number of IoT devices has also attracted criminals, fraudsters, and attackers to utilize this medium for spreading malicious content or making devices unavailable for legitimate use.It is imperative to ensure that the Confidentiality, Integrity, Security, and Privacy of information and users should remain intact while using these devices and thus they require an effective security system. Software-defined Networks (SDN) and Network Function are the way to control and configure devices from a centralized location and have been proven to offer scalability and versatility to their deployed ecosystems. In this paper, we systematically review the adoption of SDN and Network Function Virtualization (NFV) for securing the IoT network from emerging threats. To this extent, we provide a comprehensive survey on security solutions based on SDN, Blockchain, NFV, and SDN/NFV proposed for the security of the IoT network. We have also identified open challenges in this domain which includes lack of standardization, low cost, and effective machine learning systems for identifying malicious traffic and handling great attack surface and different attack vectors. The deployed technologies exhibit positive strides in their usage for the provision of security in IoT environments offering security enhancements, scalability, and versatility.

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“…Resolving policy conflict in traditional methods often take advantage of the most commonly used priority mechanism [23,24], and this method is applied to deal with conflicts in many current architectures [25][26][27][28][29]. However, rationally assign priority to each policy is almost impossible.…”

Section: Related Workmentioning

confidence: 99%

Fast Policy Interpretation and Dynamic Conflict Resolution for Blockchain‐Based IoT System

Fang

Jian

Jin

et al. 2021

Wireless Communications and Mobile Computing

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Although the blockchain-based Internet of Things (BC-IoT) has been applied in many fields, it still faces many security attacks due to lacking policy-based security management (PbSM). Previous PbSM is usually time-consuming, which is difficult to integrate into BC-IoT directly. The high-latency policy conflict resolving in traditional PbSM cannot meet the BC-IoT’s low-latency requirement. Moreover, the conflict resolution rate is low as the PbSM usually neglects the runtime information. Therefore, it is challenging that achieving an efficient PbSM for BC-IoT and overcomes both time and resource consumption. To address the problem, we propose a novel PbSM for BC-IoT named FPICR to realize fast policy interpretation and dynamic conflict resolution efficiently. We first present policy templates based on system log to interpret policy in high speed in BC-IoT. Benefiting from matching the characteristics of the system processing, FPICR supports interpreting a policy into the smart contract directly without complex content parsing. We then propose a weighted directed policy graph (WDPG) to evaluate the importance of the deployed policies more accurately. To improve the policy conflict resolution rate, we implement the resolution algorithm through reconstructing the WDPG. Taking the traits of these properties, FPICR thus can also remove the redundant data to compress storage space by the WDPG. Experiment results highlight that FPICR outperforms the baseline in all measure metrics. Especially, compared with the state-of-the-art method, the speedup of interpretation in FPICR is about up to 2.1 × . The conflict resolution rate in FPICR can be improved by 6.2% on average and achieve up to 96.1%.

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SODA: A software-defined security framework for IoT environments

Cited by 31 publications

References 24 publications

Systematic Review of Authentication and Authorization Advancements for the Internet of Things

Systematic Review of Authentication and Authorization Advancements for the Internet of Things

A comprehensive survey on secure software‐defined network for the Internet of Things

Fast Policy Interpretation and Dynamic Conflict Resolution for Blockchain‐Based IoT System

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