Enabling secure data transmission for wireless sensor networks based IoT applications

Panahi, Pejman; Bayılmış, Cüneyt

doi:10.1016/j.asej.2022.101866

Cited by 32 publications

(17 citation statements)

References 31 publications

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“…IoT devices like Hardware (MICAz mote) and Riverbed (OPNET) Modeler use Camellia. The IoT platform uses hardware (MICAz mote) to enable lowpower and wireless sensor networks [28]. Riverbed (OP-NET) Modeler is a modeling and analysis environment for communication networks and distributed systems [28].…”

Section: Relationship Between Iot Devices and Camellia Algorithmmentioning

confidence: 99%

“…The IoT platform uses hardware (MICAz mote) to enable lowpower and wireless sensor networks [28]. Riverbed (OP-NET) Modeler is a modeling and analysis environment for communication networks and distributed systems [28]. For security and privacy, hardware (MICAz mote) and Riverbed (OPNET) embed a Camellia algorithm in Random Access Memory (RAM) and Read-Only Memory (ROM) [28].…”

Section: Relationship Between Iot Devices and Camellia Algorithmmentioning

confidence: 99%

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An Application of the Khumbelo Function on the Camellia Algorithm to Prevent Attacks in IoT Devices

Muthavhine,

Sumbwanyambe

2023

IEEE Access

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Camellia is an encryption algorithm implemented in many Internet of Things (IoT) devices. However, intruders attack the Camellia cipher using Substitution Box (S-Box) distinguishers. The distinguishers are tables that provide probabilities for guessing the secret keys of the algorithms. Distinguishers are used in the majority of attacks. The most wellknown distinguishers are Linear Approximation Table (LAT), Dierence-Distribution Table (DDT), and Dierential-Linear Connectivity Table (DLCT). This research focuses on preventing these attacks using a novel function called the Khumbelo function to distract the construction of S-Box distinguishers. The Khumbelo function distracted the distinguishers' constructions by reducing the probability of building the table. The Khumbelo function successfully decreased the attack probability of LAT (from 54.6875 percent to 0 percent), DDT (from 1.5625 percent to 0 percent), and DLCT (from 50.0000 percent to 0 percent). The Khumbelo function is generated using a 4-Byte output S-Box instead of the original 1-Byte output S-Box in Camellia. INDEX TERMS Camellia, Cryptographic Attacks, Internet of Things (IoT), IoT devices, K_Camellia, S-Box, The Khumbelo Function. I. INTRODUCTION T HE Internet of Things (IoT) is a modern critical system that connects devices, things, individuals, objects, digital machines, computers, and objects for the transmission of information [1]. IoT is emerging as an eective technique with devices in signicant elds to create unique networks [1] [2]. IoT customers use these networks depending on the task needed at that time, [3]. Companies use IoT devices and networks to exchange top secret and condential information, [4]. Some of this information is sent unencrypted or encrypted by algorithms that are vulnerable to attacks [4].Cryptographic algorithms are primarily used to ensure security and privacy [4]. One of the cryptographic algorithms used on IoT devices is Camellia. This study shows that dierent types of IoT devices use Camellia. Some S-Box-based cryptographic algorithms are compromised on IoT devices, including Camellia and Advanced Encryption Standard (AES). An S-Box, for example, could resist or allow attacks. Assume an S-Box with less than 32 output bits, such as in Camellia and AES, which have eight output bits [5]. In that case, intruders could easily construct dierent distinguishers to get the probability of guessing the encryption key. Camellia and AES share some similarities in that all S-Boxes in these two algorithms are built using similar transformations that take the multiplicative inverse over a nite eld, and they are all 8 x 8 in size [5]. Therefore, if an intruder could attack one S-Box, all S-Boxes would be vulnerable. According to the ndings of this study, these S-Boxes are vulnerable to various attacks. Cryptographic algorithms are unavoidable, but they must be designed in advance to withstand attacks [4].The existing studies show that intruders attack the Camellia algorithm with various attack methods. For instance:i. Camellia is vu...

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Section: Relationship Between Iot Devices and Camellia Algorithmmentioning

confidence: 99%

Section: Relationship Between Iot Devices and Camellia Algorithmmentioning

confidence: 99%

An Application of the Khumbelo Function on the Camellia Algorithm to Prevent Attacks in IoT Devices

Muthavhine,

Sumbwanyambe

2023

IEEE Access

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“…This study elucidates that symmetric cryptographic algorithms typically require fewer resources and less computational time relative to their asymmetric counterparts. Lastly, Panahi and Bayılmış [26] examines the Camellia algorithm's performance by evaluating the end-toend delay across different payloads. The findings indicate that while the Camellia algorithm is robust, it incurs higher usage of read-only memory (ROM) and longer processing times when juxtaposed with other algorithms within the study.…”

Section: Related Workmentioning

confidence: 99%

A Lightweight Blockchain to Secure Data Communication in IoT Network on Healthcare System

Rangappa,

Manu,

Kariyappa

et al. 2023

IJSSE

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The burgeoning domain of the Internet of Things (IoT) encompasses a myriad of interconnected devices tasked with the automated collection of sensitive data. A paramount challenge within this realm is the establishment of stringent security protocols to safeguard sensitive information and thwart unauthorized access. Although various strategies have been conceived and implemented to fortify data protection in IoT environments, the unique resource limitations intrinsic to IoT devices necessitate further exploration. The criticality of efficient time and memory management for the optimization of IoT application performance cannot be overstated. This paper elucidates the efficacy of employing lightweight blockchain technology as a bulwark to secure numerous IoT applications. It introduces a symmetric cryptographic algorithm, known as Blowfish, tailored for the secure transmission of data within IoT networks. A novel key generation phase has been developed, demonstrating an adept utilization of time and memory resources on IoT devices for the encryption of transaction data. Furthermore, these transactions are recorded within a blockchain database, capitalizing on its inherent immutability. Comparative analysis reveals that the proposed scheme surpasses contemporary algorithms, including AES and 3DES, with regard to encryption time and memory overhead for key generation. This advancement heralds a significant stride in the quest to bolster IoT security.

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“…The sixth pertains to Man-in-The-Middle attacks, where attackers can intercept and potentially modify or steal data [18]. Numerous studies have proposed security mechanisms for IoT to address these vulnerabilities [19][20][21][22][23], but comprehensive solutions that tackle all these challenges remain elusive, with each approach having its strengths and weaknesses.…”

Section: Introductionmentioning

confidence: 99%

Secure IoT Routing through Manifold Criterion Trust Evaluation using Ant Colony Optimization

Sharmin,

Olanrewaju,

Khan

et al. 2023

IJACSA

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The paper presents a simplified yet innovative computational framework to enable secure routing for sensors within a vast and dynamic Internet of Things (IoT) environment. In the proposed design methodology, a unique trust evaluation scheme utilizing a modified version of Ant Colony Optimization (ACO) is introduced. This scheme formulates a manifold criterion for secure data transmission, optimizing the sensor's residual energy and trust score. A distinctive pheromone management is devised using trust score and residual energy. Concurrently, several attributes are employed for constraint modeling to determine a secure data transmission path among the IoT sensors. Moreover, the trust model introduces a dualtiered system of primary and secondary trust evaluations, enhancing reliability towards securing trusted nodes and alleviating trust-based discrepancies. The comprehensive implementation of the proposed integrates mathematical modeling, leveraging a streamlined bioinspired approach of the revised ACO using crowding distance. Quantitative results demonstrate that our approach yields a 35% improvement in throughput, an 89% reduction in delay, a 54% decrease in energy consumption, and a 73% enhancement in processing speed compared to prevailing secure routing protocols. Additionally, the model introduces an efficient asynchronous updating rule for local and global pheromones, ensuring greater trust in secure data propagation in IoT.

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Enabling secure data transmission for wireless sensor networks based IoT applications

Cited by 32 publications

References 31 publications

An Application of the Khumbelo Function on the Camellia Algorithm to Prevent Attacks in IoT Devices

An Application of the Khumbelo Function on the Camellia Algorithm to Prevent Attacks in IoT Devices

A Lightweight Blockchain to Secure Data Communication in IoT Network on Healthcare System

Secure IoT Routing through Manifold Criterion Trust Evaluation using Ant Colony Optimization

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