SecureSense: End-to-end secure communication architecture for the cloud-connected Internet of Things

Raza, Shahid; Helgason, Tómas; Papadimitratos, Panos; Voigt, Thiemo

doi:10.1016/j.future.2017.06.008

Cited by 44 publications

(15 citation statements)

References 20 publications

(23 reference statements)

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“…Topic 12 includes studies on transport protocols for endto-end security [288][289][290]. To achieve end-to-end secure communication between an IoT back end and resourcelimited smart things, various studies on communication protocols such as DTLS and CoAP [291,292] and key setting protocols such as EDHOC have been conducted [293,294].…”

Section: Identification Of Topics In Iot Securitymentioning

confidence: 99%

Current Research Trends in IoT Security: A Systematic Mapping Study

Lee

2021

Mobile Information Systems

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The smart mobile Internet-of-things (IoT) network lays the foundation of the fourth industrial revolution, the era of hyperconnectivity, hyperintelligence, and hyperconvergence. As this revolution gains momentum, the security of smart mobile IoT networks becomes an essential research topic. This study aimed to provide comprehensive insights on IoT security. To this end, we conducted a systematic mapping study of the literature to identify evolving trends in IoT security and determine research subjects. We reviewed the literature from January 2009 to August 2020 to identify influential researchers and trends of keywords. We additionally performed structural topic modeling to identify current research topics and the most promising ones via topic trend estimation. We synthesized and interpreted the results of the systematic mapping study to devise future research directions. The results obtained from this study are useful to understand current trends in IoT security and provide insights into research and development of IoT security.

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Section: Identification Of Topics In Iot Securitymentioning

confidence: 99%

Current Research Trends in IoT Security: A Systematic Mapping Study

Lee

2021

Mobile Information Systems

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“…CoAP (Constrained Application Protocol) has been introduced by the IETF's (Internet Engineering Task Force) the core working group to ensure the unified transmissions [21,27]. It has been designed specifically to address the issues of low power and low memory devices along with the support of multicast messages and abridged consumption of energy [19]. CoAP uses the UDP as the transport layer protocol so the reliable transmission of packets.…”

Section: Literature Reviewmentioning

confidence: 99%

Scalable Asymmetric Security Mechanism for Internet of Things

Siddiqa¹,

Ahmed²

2020

IJACSA

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The Internet of things stances rigorous demands on excellence of quality and the vitality of security. It becomes vital to provide an extremely reliable encryption algorithm with less complexity and computational expense in IoT paradigm. Most of the protocols designed in past for communication between sender and the receiver based on asymmetric cryptography algorithms poses high computational cost. Therefore, this paper presents a less complex and more secure and fast encryption algorithm for communication between devices i.e. Asymmetric Scalable Security between sender and the receiver of the information. We present a reliable, secure, scalable and efficient communication protocol that used asymmetric algorithm for securing the exchange of information between sender and the receiver. The proposed communication protocol is lightweight encryption method that does not require complex resources to perform the computations involved for using the asymmetric cryptography. The simulation results also show that the proposed method is efficient in terms of time and space and ensures confidentiality. Therefore, the proposed scheme is beneficial for providing the secure communication for the power and resource constrained IoT devices.

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“…The end-to-end secure communication architecture is proposed for a cloud-connected IoT environment. Herein, a constrained application protocol is proposed for a secure communication between IoT and the cloud [5]. A homomorphic encryption system based on the ring learning with error algorithm is used for cloud user authentication [6].…”

Section: Introductionmentioning

confidence: 99%

Scalable and Secure Big Data IoT System Based on Multifactor Authentication and Lightweight Cryptography

et al. 2020

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Organizations share an evolving interest in adopting a cloud computing approach for Internet of Things (IoT) applications. Integrating IoT devices and cloud computing technology is considered as an effective approach to storing and managing the enormous amount of data generated by various devices. However, big data security of these organizations presents a challenge in the IoT-cloud architecture. To overcome security issues, we propose a cloud-enabled IoT environment supported by multifactor authentication and lightweight cryptography encryption schemes to protect big data system. The proposed hybrid cloud environment is aimed at protecting organizations' data in a highly secure manner. The hybrid cloud environment is a combination of private and public cloud. Our IoT devices are divided into sensitive and nonsensitive devices. Sensitive devices generate sensitive data, such as healthcare data; whereas nonsensitive devices generate nonsensitive data, such as home appliance data. IoT devices send their data to the cloud via a gateway device. Herein, sensitive data are split into two parts: one part of the data is encrypted using RC6, and the other part is encrypted using the Fiestel encryption scheme. Nonsensitive data are encrypted using the Advanced Encryption Standard (AES) encryption scheme. Sensitive and nonsensitive data are respectively stored in private and public cloud to ensure high security. The use of multifactor authentication to access the data stored in the cloud is also proposed. During login, data users send their registered credentials to the Trusted Authority (TA). The TA provides three levels of authentication to access the stored data: first-level authentication-read file, second-level authentication-download file, and thirdlevel authentication-download file from the hybrid cloud. We implement the proposed cloud-IoT architecture in the NS3 network simulator. We evaluated the performance of the proposed architecture using metrics such as computational time, security strength, encryption time, and decryption time.

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SecureSense: End-to-end secure communication architecture for the cloud-connected Internet of Things

Cited by 44 publications

References 20 publications

Current Research Trends in IoT Security: A Systematic Mapping Study

Current Research Trends in IoT Security: A Systematic Mapping Study

Scalable Asymmetric Security Mechanism for Internet of Things

Scalable and Secure Big Data IoT System Based on Multifactor Authentication and Lightweight Cryptography

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