Is DNS Ready for Ubiquitous Internet of Things?

Zhou, Yan; Li, Hongtao; Zeadally, Sherali; Zeng, Yu; Geng, Guanggang

doi:10.1109/access.2019.2901801

Cited by 13 publications

(5 citation statements)

References 66 publications

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“…It mainly focuses on functionality, security, and availability problems. The work in [147] investigates whether the current DNS is ready for IoT. The authors lay out criteria that should be met before using DNS with IoT and analyze whether these criteria are met or not.…”

Section: Impact Of Iot On Dnsmentioning

confidence: 99%

DNS for IoT: A Survey

Ayoub

Balakrichenan²,

Khawam³

et al. 2023

Sensors

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The Internet of Things (IoT) is paving the way to becoming necessary in numerous aspects of people’s lives. IoT is becoming integrated in many domains, such as medical, industrial, and personal. Recent years have witnessed the creation of many IoT technologies that differ not only in their applications and use cases but also in standards. The absence of universally accepted standards and the variety of technologies are only some challenges the IoT market faces. Other challenges include the constrained nature of most IoT devices, the diverse identification schemes, the inadequate security mechanisms, and the lack of interoperability between different technologies. The Domain Name System (DNS) persisted throughout the years as the Internet’s naming service and accumulated more trust from users with the introduction of its security extensions. DNS could be utilized to address some of the challenges the IoT market faces. However, using DNS for IoT applications might jeopardize DNS infrastructure. In this survey, we study the coexistence of DNS and IoT. We define IoT, present its architecture and discuss its main challenges. We then introduce DNS and its function; we discuss its security and privacy drawbacks and the extensions standardized to address them. We further discuss the uses of DNS in IoT environments to address some of IoT’s challenges and the impact these uses might have on DNS.

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Section: Impact Of Iot On Dnsmentioning

confidence: 99%

DNS for IoT: A Survey

Ayoub

Balakrichenan²,

Khawam³

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Siljanovski et al demonstrated the feasibility of successfully implemented mDNS/DNS-SD on embedded systems (ATMega1284p, 8 MHz, 128 KB flash, and 16 KB RAM) [7]. Despite its high compatibility and widespread use, mDNS/DNS-SD suffers from a lack of explicit guidelines concerning endpoint communication behavior, leading to considerable performance variances across different implementations [8]. As a result, much of the existing research aims to enhance efficiency and reduce network traffic.…”

Section: Related Workmentioning

confidence: 99%

“…These advancements render our proposed approach compatible with two of the most widely adopted low-power and lossy network (LLN) standards in the IoT landscape. In application-specific domains, research has explored the use of mDNS/DNS-SD in intelligent transportation systems (ITS) [8], smart cities [13], and microservices management [14].…”

Section: Related Workmentioning

confidence: 99%

Enabling Space-Aware Service Discovery Model in Home Networks through a Compatible Extension to mDNS/DNS-SD

Liao,

Weng

2023

Electronics

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The advent of the smart home, fueled by the rapid emergence of tiny embedded IoT devices and sensors, brings the consideration of space and location information to the forefront of service discovery. In a smart home environment, spaces often have composite capabilities and complex structures. Since residents may have varying preferences based on their location within different spaces, traditional service discovery results may be suboptimal without considering the spatial context. This paper introduces a seamless approach to integrate space and location information with mDNS/DNS-SD, a widely utilized service discovery protocol in home networks. We provide a formal specification for this approach, develop a prototype, and perform a series of experiments to evaluate the efficacy and potential of the proposed method.

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“…When the application process needs to map a host domain name to an IP address, the domain name resolution function is called, and the resolution function puts the converted domain name in the DNS request and sends it to the local domain name server via UDP message [32]. After the local domain name server searches the domain name, it returns the corresponding IP address in the reply message.…”

Section: B Construction Of Domain Name Whitelist Substring Setmentioning

confidence: 99%

Malicious Domain Names Detection Algorithm Based on Lexical Analysis and Feature Quantification

et al. 2019

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Malicious domain names usually refer to a series of illegal activities, posing threats to people's privacy and property. Therefore, the problem of detecting malicious domain names has aroused widespread concerns. In this study, a malicious domain names detection algorithm based on lexical analysis and feature quantification is proposed. To achieve efficient and accurate detection, the method includes two phases. The first phase checks an observed domain name against a blacklist of known malicious uniform resource locator (URLs). The observed domain name is classified as being definitely malicious or potentially malicious based on its edit distances to the domain names on the blacklist. The second phase further evaluates a potential malicious domain name by its reputation value that represents its lexical feature and is calculated based on an N-gram model. The top 100,000 normal domain names in Alexa are used to obtain a whitelist substring set using the N-gram method in which each domain name excluding the top-level domain is segmented into substrings with the length of 3, 4, 5, 6 and 7. The weighted values of the substrings are calculated according to their occurrence counts in the whitelist substring set. A potential malicious domain name is segmented by the N-gram method and its reputation value is calculated based on the weighted values of its substrings. Finally, the potential malicious domain name is determined to be malicious or normal based on its reputation value. The effectiveness of the proposed detection method has been demonstrated by experiments on public available data.INDEX TERMS Malicious domain names, N-gram, domain name substring, edit distance, reputation value.

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Is DNS Ready for Ubiquitous Internet of Things?

Cited by 13 publications

References 66 publications

DNS for IoT: A Survey

DNS for IoT: A Survey

Enabling Space-Aware Service Discovery Model in Home Networks through a Compatible Extension to mDNS/DNS-SD

Malicious Domain Names Detection Algorithm Based on Lexical Analysis and Feature Quantification

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