A survey on privacy and security of Internet of Things

Ogonji, Mark Mbock; Okeyo, George; Wafula, Joseph Muliaro

doi:10.1016/j.cosrev.2020.100312

Cited by 113 publications

(47 citation statements)

References 78 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Many works in the literature cover the various aspects of the threats and attacks in IoT. Authors in [20][21][22][23][24][25][26] cover the taxonomy of the threats and attacks pertaining to the IoT. These works mainly focus on two broad categories: the architecture of IoT and protocols/standards in IoT.…”

Section: Comparison With Existing Surveysmentioning

confidence: 99%

See 1 more Smart Citation

State-of-the-Art Review on IoT Threats and Attacks: Taxonomy, Challenges and Solutions

et al. 2021

View full text Add to dashboard Cite

The Internet of Things (IoT) plays a vital role in interconnecting physical and virtual objects that are embedded with sensors, software, and other technologies intending to connect and exchange data with devices and systems around the globe over the Internet. With a multitude of features to offer, IoT is a boon to mankind, but just as two sides of a coin, the technology, with its lack of securing information, may result in a big bane. It is estimated that by the year 2030, there will be nearly 25.44 billion IoT devices connected worldwide. Due to the unprecedented growth, IoT is endangered by numerous attacks, impairments, and misuses due to challenges such as resource limitations, heterogeneity, lack of standardization, architecture, etc. It is known that almost 98% of IoT traffic is not encrypted, exposing confidential and personal information on the network. To implement such a technology in the near future, a comprehensive implementation of security, privacy, authentication, and recovery is required. Therefore, in this paper, the comprehensive taxonomy of security and threats within the IoT paradigm is discussed. We also provide insightful findings, presumptions, and outcomes of the challenges to assist IoT developers to address risks and security flaws for better protection. A five-layer and a seven-layer IoT architecture are presented in addition to the existing three-layer architecture. The communication standards and the protocols, along with the threats and attacks corresponding to these three architectures, are discussed. In addition, the impact of different threats and attacks along with their detection, mitigation, and prevention are comprehensively presented. The state-of-the-art solutions to enhance security features in IoT devices are proposed based on Blockchain (BC) technology, Fog Computing (FC), Edge Computing (EC), and Machine Learning (ML), along with some open research problems.

show abstract

Section: Comparison With Existing Surveysmentioning

confidence: 99%

“…The countermeasures have also been discussed. Ogonji has comprehensively presented a threat taxonomy for the IoT environment in [22], including two broad categories: security threat and privacy threat. The authors of this survey presented taxonomy and countermeasures for the three-layer domain-specific IoT architecture.…”

Section: Comparison With Existing Surveysmentioning

confidence: 99%

State-of-the-Art Review on IoT Threats and Attacks: Taxonomy, Challenges and Solutions

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Moreover, the loss from security events can be severe due to the effective connectivity and scale of the IoT networks. Earlier research on IoT security [ 14 , 15 ] has discussed some significant factors; one is key management. According to the studies, security keys can be sniffed by several attacks, considering that IoT devices are usually deployed wherever the attacker can reach them.…”

Section: Introductionmentioning

confidence: 99%

“…LoRaWAN protocol [24] is designed for limited battery applications where wide-range communication with low power consumption is primary. LoRaWAN v1.02 specification defines the network ranges to be (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15) km; data rates range between 0.3 and 50 kbps, and the network is operated over the 868-MHz and 900-MHz bands. LoRaWAN is one of the essential technologies for IoT that has grown based on the network star topology.…”

mentioning

confidence: 99%

A Key Management Protocol Based on the Hash Chain Key Generation for Securing LoRaWAN Networks

Hakeem

El-Kader

Kim

2021

Sensors

View full text Add to dashboard Cite

Recently, many Low Power Wide Area Network (LPWAN) protocols have been proposed for securing resource-constrained Internet of Things (IoT) devices with negligible power consumption. The Long Range Wide Area Network (LoRaWAN) is a low power communication protocol that supports message authentication, integrity, and encryption using two-session preshared secret keys. However, although the LoRaWAN supports some security functions, it suffers from session key generation and key update problems. This motivates us to introduce a new key management protocol that resolves the LoRaWAN problems and supports key updates. The proposed protocol is based on hash chain generation using a one-way hash function. Network entities share a common hash chain of n key elements to allow using a unique signing key per message. We also propose a salt hashing algorithm that encrypts the original keys into a different form to avoid the physical attacks at the end device side. We analyzed the proposed key generation performance in terms of the computation time, the required storage, and the communication overhead. We implemented and tested the proposed key generation protocol using the NS-3 network simulator. The proposed lightweight key generation protocol significantly enhances the security of the original LoRaWAN at a negligible overhead. The proposed protocol reduces the power consumption and transmission time by two times compared with some previous protocols. In addition, the proposed key generation protocol can resist attacks, such as key compromising attacks and replay attacks, and it supports the Perfect Forward Secrecy, which was not supported by LoRaWAN.

show abstract

“…The Internet of Things (IoT) is a growing platform and expands exponentially. This newfound innovation has had a remarkable effect on people's lives and the business sector as it empowers companies to automate processes and decrease employment costs [1]. It improved service quality, making it economical for production and goods delivery.…”

Section: Introductionmentioning

confidence: 99%

Modified Key Derivation Function for Enhanced Security of Speck in Resource-Constrained Internet of Things

Lustro¹

2021

IJCNIS

View full text Add to dashboard Cite

Randomness is an imperative component in every cryptographic algorithm to guarantee secret keys are unpredictable and secured against all forms of attacks. Speck generated sequence is non-random, a clear sign that it falls beyond the acceptable success rate when tested in statistical analysis. Thus, this study resolves the non-randomness by integrating a novel key derivation function that uses elementary operators designed for lightweight application. This design aims not to compromise performance when implemented on software and hardware. As a result, the modified Speck successfully passed the NIST SP 800 - 22 and Dieharder v3.31.0 Statistical Test Analysis as no p-value is flagged as failed during testing. Hence, making modified Speck cryptographically secured. Nevertheless, a 1.06% decrease in the figure of merit of the modified Speck still makes it worthier in a resource-constrained Internet of Things application as contrasted to Speck because it is proven to be beyond cryptographically secured.

show abstract

A survey on privacy and security of Internet of Things

Cited by 113 publications

References 78 publications

State-of-the-Art Review on IoT Threats and Attacks: Taxonomy, Challenges and Solutions

State-of-the-Art Review on IoT Threats and Attacks: Taxonomy, Challenges and Solutions

A Key Management Protocol Based on the Hash Chain Key Generation for Securing LoRaWAN Networks

Modified Key Derivation Function for Enhanced Security of Speck in Resource-Constrained Internet of Things

Contact Info

Product

Resources

About