Secure key agreement for multi-device home IoT environment

Garg, Anshul; Lee, Taehee

doi:10.1016/j.iot.2020.100249

Cited by 5 publications

(4 citation statements)

References 23 publications

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“…O LiKe é caracterizado por materiais de criptografia efêmeros, suporte para conectividade intermitente com um terceiro confiável (Trusted Third Party -TTP), operac ¸ões leves de re-chaveamento e robustez contra ataques de personificac ¸ão. Garg et al [11] propõe um protocolo de seguranc ¸a com acordo de chaves em IoT para casas inteligentes (smart home) chamado Multi-device Key Agreement (MKA). O protocolo é baseado nas propriedades de func ¸ões hash e criptografia de curva elíptica.…”

Section: Trabalhos Relacionadosunclassified

Análise de Desempenho de um Esquema de Acordo de Chaves de Conferência para IoT

Marim,

Coelho,

Vieira

et al. 2023

Anais Estendidos Do XIII Simpósio Brasileiro De Engenharia De Sistemas Computacionais (SBESC Estendido 2023)

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Wireless networks and their recent applications in the Internet of Things (IoT) have the evident necessity of mechanisms that increase its exchanged data reliability and integrity. Therefore, key agreement schemes are strong candidates to meet these requirements. Considering the resource constraints in IoT networks, verifying these limitations is vital. In this work, an analysis of computational feasibility and a proposal for using a one-way key agreement method based on second-degree equations for an IoT environment are performed. For the analysis, we simulated a network of up to 50 devices. It considered memory consumption, the time for session key generation, the size of the generated key, and the overhead in time for message exchange. The results show that the method applies to IoT networks, presenting a linear growth in the key agreement time and constant processing even with increasing the key size.

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Section: Trabalhos Relacionadosunclassified

Análise de Desempenho de um Esquema de Acordo de Chaves de Conferência para IoT

Marim,

Coelho,

Vieira

et al. 2023

Anais Estendidos Do XIII Simpósio Brasileiro De Engenharia De Sistemas Computacionais (SBESC Estendido 2023)

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“…Li et al [15] proposed a low-cost mutual authentication method and anonymous key agreement. However, Garg and Lee [16] showed that Li et al' method is vulnerable to some attacks, such as node capture and personification. Hence, Garg and Lee proposed a method to mitigate the vulnerable found in [15].…”

Section: Related Workmentioning

confidence: 99%

LORENA: Low memORy symmEtric-Key geNerAtion Method for Based on Group Cryptography Protocol Applied to the Internet of Healthcare Things

et al. 2022

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The advent of the Internet of Things (IoT) has revolutionized the way we, as a society, perform different daily tasks, such as healthcare. The Internet of Health Things (IoHT) is an example of the IoT specialization handling sensitive user data and applications requiring solutions to address different security and privacy issues. IoHT requires security mechanisms in communication. However, these mechanisms need to consider the limitations of the IoHT devices and communication. Hence, symmetric cryptography is suitable to IoHT once it uses less computational and communication resources than asymmetric cryptography. But, symmetric cryptography relies on the agreement of the cryptography material (e.g., the cryptography key) among the devices, a challenge in networks with resource constraints, such as IoHT. Therefore, this article presents a Low memORy symmEtric-key geNerAtion (LORENA) method based on group secret key agreement protocol for IoHT environments. Evaluations have focused on computational efficiency, data security requirements, and scalability in a network with up to ten devices per group using a simulator and a device with limited computational resources. Results show that the protocol is lightweight, secure, and feasible to IoHT networks, presenting a linear growth in the 128-bit key distribution time for each device entering the group.

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“…At this juncture, real world consequences may arise when the attacker is potential in generating illegitimate control command to the indoor smart home devices, and further this false control command generated by the attackers has the possibility of being received by the end devices. For instance, the attacker in a smart home environment has the feasibility of gaining physical access to the home in order to carry out criminal activities such as larceny or assault, when an attacker successfully compromises the smart door look for accepting the attacker generated fake open door command 13 . In this context, a diversified number of authentication protocols were contributed in the literature for concentrating on the generation of secure session keys that could be utilized for the generation of well authenticated channels.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, the attacker in a smart home environment has the feasibility of gaining physical access to the home in order to carry out criminal activities such as larceny or assault, when an attacker successfully compromises the smart door look for accepting the attacker generated fake open door command. 13 In this context, a diversified number of authentication protocols were contributed in the literature for concentrating on the generation of secure session keys that could be utilized for the generation of well authenticated channels. Majority of the IoT integrated in the smart home environment does not possess adequate storage, memory, and computation power for supporting the implementation of the existing authentication protocols as they computationally depend on intensive cryptographic algorithms.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Forest of Random Subsets‐based supervised hash signature scheme for secure user authentication in smart home environment

Sudha

Jeyanthi

2021

Concurrency and Computation

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SummaryThe advent of information and communication technology has revolutionized the application of smart home through which the residents remotely establish superior control over the smart devices. The users and the smart devices interact over an insecure communication channel that may help an illegitimate user to gain access on the data disseminated by the smart devices, resulting in high exploiting attacks like privileged insider attack, smart device and gateway node impersonation attack, and smart node capture attack in the smart home. Thus, a secure remote authentication scheme that permits only legitimate users to gain access to the smart devices based on supervised learning becomes essential. In this article, Dynamic Forest of Random Subsets‐based supervised hash signature (DFORS‐SHS) scheme is proposed for robust user authentication in smart homes. This proposed DFORS‐SHS scheme concurrently performs the signed generation of random subsets such that each element of a signature is used for the generation of successive random subset elements for authentication. It utilized the strength of revealed secret keys through chaining approach that bundles the random subset generation and signature. This supervised learning approach only permits the signer of the original message to potentially generate a random subset and prevents the malicious intruder from gaining the access of the smart devices. The formal verification and the security investigation of the proposed DFORS‐SHS scheme are conducted using the Burrows‐Abadi‐Needham (BAN) and AVIPSA toolkit for determining communication cost, communication time, computation time, and energy consumptions incurred during the authentication process. It can be stated that, the communication cost and storage costs of the proposed DFORS‐SHS scheme was also identified to be comparatively minimized than the baseline smart home authentication schemes.

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Secure key agreement for multi-device home IoT environment

Cited by 5 publications

References 23 publications

Análise de Desempenho de um Esquema de Acordo de Chaves de Conferência para IoT

Análise de Desempenho de um Esquema de Acordo de Chaves de Conferência para IoT

LORENA: Low memORy symmEtric-Key geNerAtion Method for Based on Group Cryptography Protocol Applied to the Internet of Healthcare Things

Dynamic Forest of Random Subsets‐based supervised hash signature scheme for secure user authentication in smart home environment

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