A Complexity-Reduced Block Encryption Algorithm Suitable for Internet of Things

Guo, Xiaxia; Hua, Jingyu; Zhang, Yu; Wang, Dongming

doi:10.1109/access.2019.2912929

Cited by 14 publications

(18 citation statements)

References 36 publications

(52 reference statements)

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“…Most of these works are investigating the use of simplified version of the original AES algorithm by modifying some of the encryption/decryption steps that make it a lightweight block symmetric standard. In [16], the secure and fast encryption routine (SAFER++) is presented for securing IoT applications. It is a low-complexity, secure, and fast block cipher, accomplished by modifying the original SAFER standard with a 64-key length resulting in an algorithm that is equally secure but simpler.…”

Section: Introductionmentioning

confidence: 99%

Analysis and evaluation of symmetrical key ciphers for internet of things smart home

Abdulla

Mahmood

Salih³

et al. 2021

IJEECS

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A large number of sensors and intelligent devices are interconnected via the internet to collect data as part of the internet of things (IoT) applications. Data security is one of the important challenges for these applications due to vulnerability of the internet. IoT devices limiting factors, such as delay-sensitivity, restricted memory, and low computing capability, make choosing the appropriate data encryption standard extremely important. The current research focuses on evaluating four data security, block cipher standards for the IoT smart home application. Considering the encryption/decryption speed, DES, TDES, AES, and SAFER+ standards are evaluated by implementing the algorithms with MATLAB to determine the best security solution. The simulation of the four standards shows the superiority of SAFER+ standard in term of encryption speed compared to others added to its capabilities on security, and software implementation opportunity. The use of classical symmetric key standards for real time data security in the IoT application can be validated through the selection of SAFER+.

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Section: Introductionmentioning

confidence: 99%

Analysis and evaluation of symmetrical key ciphers for internet of things smart home

Abdulla

Mahmood

Salih³

et al. 2021

IJEECS

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“…Ironically, with increase in high-pace IoT demands, the events of security breaches too have increased severely. The security breaches in IoT can be at the different level, i.e., device level, infrastructure level, network level (say, channel) and data level [3][4] [6] [38]. Such security breaches can cause detrimental impacts in terms of financial loss, data-loss, tack-manipulation and procedural destruction [2].…”

Section: Introductionmentioning

confidence: 99%

“…Recalling the typical architecture of the IoT systems that encompasses Low-power Lossy (sensor) Networks (LLNs), gateways, transmission channel and data-warehouses or storage possessing undeniably security related vulnerabilities. Typically, the poorly interfaced nature of IoT devices and their inferior connection, especially operating online can undergo 377 | P a g e www.ijacsa.thesai.org security breaches and resulting losses [5][6][7]. On the other hand, attack probability gets increased manifolds over channel where different man-in-the middle attack (MITM), linear and differential attacks, impersonation, etc.…”

Section: Introductionmentioning

confidence: 99%

Feistel Network Assisted Dynamic Keying based SPN Lightweight Encryption for IoT Security

Gurumanapalli¹,

Muthuluru²

2021

IJACSA

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In the last few years Internet-of-Things (IoT) technology has emerged significantly to serve varied purposes including healthcare, surveillance and control, business communication, civic administration and even varied financial activities. Despite of such broadened applications, being distributed, wireless based systems, IoTs are often considered vulnerable towards intrusion or malicious attacks, where exploiting the benefits of loosely connected peers, the attackers intend to gain device access or data access un authentically. However, being resource constrained in nature while demanding time-efficient computation, the majority of the classical cryptosystems are either computationally exhaustive or limited to avoid attacks like Brute-Force, Smart Card Loss Attack, Impersonation, Linear and Differential attacks, etc. The assumptions hypothesizing that increasing key-size with higher encryption round can achieve augmented security often fail in IoT due to increased complexity, overhead and eventual resource exhaustion. Considering it as limitation, in this paper we proposed a state-of-art Generalized Feistel Network assisted Shannon-Conditioned and Dynamic Keying based SSPN (GFS-SSPN) Lightweight Encryption System for IoT Security. Unlike classical cryptosystems or even substitution and permutation (SPN) based methods, we designed Shannon-criteria bounded SPN model with Generalized Feistel Network (SPN-GFS) modelthat employs 64-bit dynamic key with five rounds of encryption to enable highly attack-resilient IoT security. The proposed model was designed in such manner that it could be suitable towards both data-level security as well as device level accesscredential security to enable a "Fit-To-All" security solution for IoTs. Simulation results revealed that the proposed GFS-SSPN model exhibits very small encryption time with optimal NPCR and UACI. Additionally, correlation output too was found encouragingly fair, indicating higher attack-resilience.

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“…For example, no successful attack on the full-round Simon or the full-round Speck, which is a family of lightweight block ciphers, is known [8][9][10]. ird, we need an automated and generalized test tool for checking the safety of various lightweight block ciphers for Internet of ings [11]. ere are various automated techniques that can be used to build distinguishers against block ciphers [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Cryptanalysis of Lightweight Block Ciphers

2020

Security and Communication Networks

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Most of the traditional cryptanalytic technologies often require a great amount of time, known plaintexts, and memory. This paper proposes a generic cryptanalysis model based on deep learning (DL), where the model tries to find the key of block ciphers from known plaintext-ciphertext pairs. We show the feasibility of the DL-based cryptanalysis by attacking on lightweight block ciphers such as simplified DES, Simon, and Speck. The results show that the DL-based cryptanalysis can successfully recover the key bits when the keyspace is restricted to 64 ASCII characters. The traditional cryptanalysis is generally performed without the keyspace restriction, but only reduced-round variants of Simon and Speck are successfully attacked. Although a text-based key is applied, the proposed DL-based cryptanalysis can successfully break the full rounds of Simon32/64 and Speck32/64. The results indicate that the DL technology can be a useful tool for the cryptanalysis of block ciphers when the keyspace is restricted.

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A Complexity-Reduced Block Encryption Algorithm Suitable for Internet of Things

Cited by 14 publications

References 36 publications

Analysis and evaluation of symmetrical key ciphers for internet of things smart home

Analysis and evaluation of symmetrical key ciphers for internet of things smart home

Feistel Network Assisted Dynamic Keying based SPN Lightweight Encryption for IoT Security

Deep Learning-Based Cryptanalysis of Lightweight Block Ciphers

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