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ENHANCING SECURITY IN IOT DEVICES: A LIGHTWEIGHT HYBRID CRYPTOGRAPHIC SYSTEM
(LCS) APPROACH
Amita Shah1, Sanjay Shah2, Dhaval Parikh3, Namit Shah4
!Ph.D Scholar, Computer/IT Engineering, Gujarat Technological University, Gujarat, India
amitashah@ldce .ac.in
2Professor & Head, Computer Engineering Dept., Government Engineering College, Rajkot,
Gujarat, India. sanjay_shah_r@yahoo.com 3Professor & Head, Computer Engineering Dept., Government Engineering College, G'nagar,
Gujarat, India. daparikh@gecg28.ac.in "Student, Computer Engineering Dept., L D College of Engineering, Ahmedabad, Gujarat,
India. namitvshah@gmail.com
Abstract
The escalating connectivity of devices in the Internet of Things (IoT) era necessitates robust security measures while accommodating resource constraints. Lightweight cryptography addresses this need, focusing on algorithm development for devices with limited resources. This research proposes the Lightweight Crypto System (LCS) as a hybrid cryptosystem, integrating the Lightweight Symmetric Algorithm (LSA) and the Lightweight Hash Algorithm (LHA). LSA is a modified AES-128 variant, enhancing data confidentiality, while LHA, derived from SHA-256, verifies data integrity. The study evaluates the proposed LCS on criteria such as execution time, memory usage, avalanche effect, collision resistance, and entropy, emphasizing the optimal balance between performance and security achieved by LSA and LHA. The findings position LCS as a compelling solution for securing IoT devices without compromising on stringent security requirements.
Keywords: Internet of Things (IoT), Lightweight Cryptography, Hybrid Cryptosystems, LSA, LHA, Security.
1. Introduction
The Internet of Things (IoT) integration poses security challenges [1]. With threats like unauthorized access and data breaches, secure communication is vital. Our research introduces Lightweight Crypto System (LCS) as an adaptable solution [2], enhancing IoT security. It safeguards user privacy and ensures data integrity in the interconnected IoT landscape [3, 4].
The Lightweight Crypto System (LCS) is a breakthrough in IoT security, tailored for resource-constrained devices [5, 6, 7]. Comprising three key elements, it forms a comprehensive security framework. The Lightweight Symmetric Algorithm (LSA), a modified AES-128, ensures efficient symmetric encryption for data confidentiality [8]. Elliptic Curve Cryptography (ECC) facilitates secure key exchange and authentication [9]. Additionally, the Lightweight Hash
Algorithm (LHA) enhances data integrity verification in the LCS system. Together, these components provide robust solutions for confidentiality, authenticity, access control, and data integrity in IoT communication. LCS's effectiveness stems from the collaboration of its three components: LSA ensures data confidentiality with a tailored version of AES-128 for IoT constraints, ECC facilitates secure key exchange, and the proposed LHA enhances data integrity verification. This integration positions LCS as a versatile solution addressing the complex security demands of the evolving IoT landscape.
1.1. Motivation and Contribution
This research is driven by the growing IoT landscape and the security challenges it poses. With the surge in connected devices, addressing security concerns becomes crucial. The motivation stems from the need to enhance IoT security infrastructure due to escalating concerns about data privacy and integrity. This research aims to provide innovative cryptographic solutions tailored for resource-constrained IoT devices, bridging the gap between security and performance. The major contribution is the exploration of a LCS ensuring efficient and secure communication in the interconnected IoT landscape.
• Lightweight Crypto System (LCS): Introduction of a specialized hybrid cryptosystem tailored for IoT environments, providing a comprehensive security solution for resource- constrained devices [11].
• Lightweight Symmetric Algorithm (LSA): Development and implementation of LSA, a modified AES-128 algorithm optimized for IoT devices, ensuring efficient and secure data confidentiality [8].
• Lightweight Hash Algorithm (LHA): Proposal and implementation of LHA, a novel lightweight hash algorithm designed for data integrity verification in resource-constrained IoT devices, striking a balance between security and performance [12].
• Performance and Security Parameter Analysis: Rigorous evaluation of LCS through performance metrics and key security parameters, including execution time, memory usage, avalanche effect, collision resistance, and entropy, offering insights into the system's robust- ness and efficiency.
• Real-world Testbed Implementation: Practical validation of LCS on an IoT testbed using ESP32 hardware, demonstrating its effectiveness in real-world IoT scenarios and providing a foundation for further optimization of cryptographic processes in IoT environments.
2. Related Work
IoT security literature investigates cryptographic methods due to the growing impact of IoT in daily life, especially in critical areas like smart homes and healthcare. The resource constraints of IoT devices necessitate lightweight and energy-efficient security solutions, posing a challenge to widespread adoption. Recent research explores the potential benefits of integrating lightweight blockchain technology, emphasizing the role of hashing in constructing a robust blockchain structure for enhanced IoT security [13]. This study evaluates various hash techniques on a Raspberry Pi device, providing quantitative insights into the performance of hash functions for lightweight blockchain-based IoT applications [13].
The IoT's growth introduces security challenges for embedded devices [14]. A solution proposes using MD5, a hashing algorithm, to enhance IoT security, fortifying embedded devices against internet-based attacks [14]. This approach seamlessly integrates with the IoT framework and is endorsed for securing embedded systems in IoT [14].
The study in [15] tackles the lack of reliable hybrid cryptosystems for securing critical IoT
devices. It explores lightweight encryption algorithms such as TEA, XTEA, XXTEA, RSA, and ECC, aiming for optimal security in constrained environments. The proposed hybrid cryptosystem, incorporating chaotic theory for key generation, outperforms RSA and XXTEA by 40%, showcasing enhanced security and superior performance for safeguarding IoT devices [15].
In [16], the paper underscores the crucial role of cryptography in data security, introducing the Secure Hash Algorithm-3 (SHA-3) for data verification. Implementing a low-power technique, latch-based clock gating, enhances power efficiency in SHA-3 algorithm designs [16].
In [17], the paper recognizes the pivotal role of wireless sensor networks (WSNs) in collecting and transmitting sensitive information. It addresses challenges in WSN infrastructure design due to resource limitations and emphasizes the need for efficient authentication solutions. The proposed 2AMD-160, a Secure Hash Algorithm, outperforms MD5 and SHA1 in both execution time and security in comparative analysis [17].
The IoT's global connectivity introduces security challenges, requiring energy-efficient solutions. Existing methods compromise between security and energy consumption [18] proposes a BLAKE2b-based authentication with modified ECDSA, demonstrating improved signature times on Raspberry Pi-3. The scheme exhibits resistance to attacks, suitable for resource-constrained IoT devices.
In [23], the paper shows how message-level security instead of transport level security is used to provide end-to-end secure communication between IoT devices and Gateway. Various symmetric and asymmetric security algorithms along with different data formats such as XML, JSON and EXI are executed and compared. Used Blowfish encryption algorithm for IoTSyS framework[23].
3. Proposed Methodology
In addressing the escalating security concerns associated with the ever-expanding Internet of Things (IoT) ecosystem, we introduce a comprehensive Lightweight Crypto System (LCS) that harmoniously integrates three key cryptographic components: "MyLightSymAlgo" (LSA), Elliptic Curve Cryptography (ECC), and the novel "MyLightHashAlgo" (LHA). This section gives detail description for each of the components. The architecture for proposed hybrid model (LCS) sender side and receiver side execution approach is presented in Figure 1 and 2, respectively.
Figure 1: Proposed Hybrid Model (LCS) (Sender Side Execution)
Amita Shah, Sanjay Shah, Dhaval Parikh, Namit Shah RT&A, No 2 (78) A LIGHTWEIGHT HYBRID CRYPTOGRAPHIC SYSTEM (LCS)_Volume 19, June, 2024
The sequential execution flow of the proposed approach is illustrated in Figure 3. The detail explanation for each component for proposed hybrid model (LCS) is presented below.
3.1 MyLightSymAlgo (LSA): Lightweight Symmetric Encryption
LSA, a key element of the proposed LCS, is a tailored variant of AES-128, designed to address security requirements in resource-constrained IoT devices by introducing efficiency-enhancing modifications and replacements [8].
• Algorithmic Modifications: LSA undergoes meticulous changes within AES-128 to create a lightweight encryption process for IoT devices, considering constraints like limited processing power and memory.
• Enhanced Encryption/Decryption: The final LSA version shows notable improvements over AES-128, excelling in both encryption and decryption for faster data transformation, crucial for realtime processing in IoT.
Figure 2: Proposed Hybrid Model (LCS) (Receiver Side Execution)
Figure 3: Sequence of Execution
• Security and Sensitivity: LSA aims for a highly secure encryption system with sensitivity to small input changes, enhancing overall security by producing significant output variations [8].
• IoT Data Security: LSA is designed to secure data from IoT sensors, suitable for resource-constrained devices where traditional cryptographic methods may be impractical.
As part of LCS, LSA ensures data confidentiality in IoT, protecting sensitive information while addressing IoT device limitations. The LSA diagram is depicted in Figure 4. The step-by-step operations of the LSA employed for secure data encryption is presented in Algorithm 1 [8].
128-bit plaintext
Round Key 1 (128 bits)
Pre-round
transformation Ko E -C
1 1-
Round 1 o 00
K <
1 o
Round 2 ro
K2 ! 1 1 1 QJ c
1 1 1 1 QJ ID CD
Round 7 1/1
(slightly different) K7
Secret Key (128 bits)
128-bit ciphertext
Figure 4: LSA General Diagram
Algorithm 1 Lightweight Symmetric Algorithm (LSA)
1: procedure LSA (Data Block, Round Keys)
2: XOR Data Block with corresponding Pre Round Key
3: Apply Parity Transformation
4: for each byte in Data Block do
5: Substitute byte using innovative SubBytes table
6: Rearrange bytes using Junction Jumping strategy
7: XOR with corresponding Round Key byte
8: end for
9: Substitute byte using innovative SubBytes table
10: XOR Data Block with corresponding Round Key byte
11: Output: Encrypted Data Block 12: end procedure
3.2 Elliptic Curve Cryptography (ECC): Asymmetric Encryption and Key Generation
Compared with other traditional public key encryption algorithm such as RSA algorithm, ECC algorithm can provide the same security with short key length. ECC operates on elliptic curves over finite fields so provide complexity [19]. The advantages of elliptic curves are: Encryption, Decryption and Signature Verification speed up, due to shorter key lengths, High safety performance, Small storage space, Fast processing speed, and Low bandwidth requirements [20, 21].
3.3 MyLightHashAlgo (LHA): Lightweight Hash Algorithm for Integrity
MyLightHashAlgo (LHA), a crucial element of Lightweight Crypto System (LCS) for resource-constrained IoT devices, improves data integrity using the optimal SHA256 variant, SHA256SUBPT. Proposed as the Lightweight Hash Algorithm (LHA), SHA256SUBPT achieves a balance between performance and security, with its architecture illustrated in Figure 5. • LHA Architecture Block Wise: LHA processes data in 512-bit blocks, employing a block-wise approach for efficient handling, contributing to a 256-bit message digest. The block-wise architecture is illustrated in Figure 6.
Figure 5: LHA Architecture
Figure 6: LHA Architecture Block Wise
• Hash Function of LHA: LHA's hash function, grounded in Merkle-damgard construction, executes multiple rounds of operations to generate a 256-bit message digest, ensuring data integrity. The graphical representation is illustrated in Figure 7.
• Each Round of Hash Function of LHA: In each round of the LHA hash function, crypto- graphic
operations like bitwise transformations and XOR summations are applied to input data, enhancing algorithm complexity. The iterative process ensures intricate manipulations, leading to the generation of a secure 256-bit hash digest, as depicted in Figure 8. LHA's hash function's round operation integrates key operations like Majority and Choose selections, XOR summations, and optimizations such as round reduction, Rijndael substitution, and Parity transformation which replace all state variables-64 bit, except A and E, with the 1's complements of their present values if their present values happen to be odd to enhance efficiency and security.
Figure 7: Hash Function of LHA
Figure 8: Each Round of Hash function of LHA
- Ma: Majority selects the next output in a bit-wise manner based on the majority bit for the three input bytes.
- Ch: Choose selects the next output in a bit-wise manner based on the values in the 'x' variable; if x[i] = 0, y[i] is selected, else z[i] is selected.
- E0: Sigma A: XOR Summation on A.
- E1: Sigma E: XOR Summation on E.
• LHA - SECURITY PARAMETERS: To evaluate the security of the LHA algorithm, we consider Collision Resistance and Shannon Entropy as crucial security parameters. Collision Resistance: This property in cryptographic hash functions ensures that it is challenging to find two inputs (a and b) such that they produce the same output (H(a) = H(b)), where a /= b.
Shannon Entropy: This parameter is employed to gauge Confusion, specifically the obfus-cation of the Input-Output Relationship.
4. Experimental Result Analysis
The evaluation and results analysis were conducted to compare the performance of the Lightweight Symmetric Algorithm (LSA) against the Advanced Encryption Standard (AES) in terms of execution time and memory consumption. Security parameters such as avalanche effect, Hamming distance, and entropy were considered.
4.1 LSA vs AES Execution Time Comparison
We conducted a thorough evaluation of the execution time for the LSA compared to the Advanced Encryption Standard (AES). This analysis provides insights into the relative efficiency of LSA and AES in handling cryptographic operations, with implications for real-world applications and system performance. Figure 9 represents the LSA vs AES in terms of execution time.
Figure 9: LSA vs AES in term of Execution Time
4.2 LSA vs AES Memory Consumption Comparison
Our study assessed the memory consumption of Lightweight Symmetric Algorithm (LSA) compared to Advanced Encryption Standard (AES), providing insights into their resource requirements for optimizing cryptographic algorithm performance. Figure 10 visually represents the LSA vs AES memory consumption dynamics.
4.3 Security Parameters Evaluation
The algorithm's security assessment centered on the avalanche effect, hamming distance, and entropy, evaluating diffusion, confusion, and bit changes. Parameters were derived from 10,000 randomly generated blocks to conduct a thorough security analysis.
Figure 10: LSA vs AES in term of Memory Consumption
4.3.1 LSA Avalanche Criterion Evaluation
Our assessment of the Lightweight Symmetric Algorithm (LSA) scrutinizes its performance using the Avalanche Criterion (AC), considering first, second, and third-order criteria along with the average. This comprehensive analysis sheds light on LSA's efficacy in diffusing changes in input data, reflecting in output data, essential for robust cryptographic applications.
Table 1: Performance of LSA in term of Avalanche Criterion
1st Order AC 2nd Order AC 3rd Order AC Average AC
AES 49.00% 49.00% 49.00% 49.00%
LSA 49.00% 42.00% 49.00% 46.66%
Table 1 displays LSA's performance in Avalanche Criterion (AC) at various orders and the average AC, contrasting with AES's constant 49.00%. LSA shows variations, notably a 2nd Order AC drop to 42.00%, resulting in an average AC of 46.66%, indicating different levels of change propagation compared to AES. Figure 11 visually compares LSA and AES in terms of Avalanche Effect, offering insights into their respective responses to modifications in input data and highlighting their unique diffusion characteristics.
4.3.2 LSA Entropy Criteria
Table 2 reveals the performance of LSA and AES based on Entropy criteria, indicating a 50.00%
Hamming Distance for both and very close Shannon's Entropy values. LSA slightly edges higher at 3.612 compared to AES's 3.611, showcasing comparable security aspects related to confusion and the number of flipped bits after conversion.
Table 2: Performance of LSA in term of Avalanche Criterion
Hamming Distance Shannon's Entropy (Log2)
AES LSA
50.00% 50.00%
3.611
3.612
Figure 11: LSA vs AES in Term of Avalanche Effect
Figure 12 illustrates the evaluation of LSA versus AES based on Hamming Distance, showing an equivalent and favorable 50.00% for both algorithms. Hamming Distance, measuring bit differences between original and encrypted data, underscores their similar and consistent performance in this security parameter.
Figure 12: LSA vs AES in Term of Hamming Distance
Figure 13: LSA vs AES in term of Shannon Entropy
In Figure 13, LSA and AES exhibit identical Shannon Entropy values of 3.612, emphasizing their equivalent performance in providing a high degree of confusion and obfuscation in the input-output relationship. These similar Shannon Entropy values highlight a strong level of security for both algorithms in this parameter.
4.1. Performance Analysis for SHA256 and LHA
4.4.1 Memory Consumption of SHA256 and LHA
Figure 14 presents the results of experiments evaluating the memory consumption of SHA256 and LHA, offering a comparison of their respective requirements under specified conditions. The analysis provides insights into the efficiency and resource utilization of SHA256 and LHA, highlighting their impacts on memory consumption in cryptographic operations.
Figure 14: Performance of SHA256 and LHA in Term of Memory Consumption
4.4.2 Performance of SHA256 and LHA in Term of Execution time
Figure 15 illustrates the experimentally evaluated execution time performance of SHA256 and LHA, offering insights into the time efficiency of both algorithms, including processing time and overall execution speed.
4.4.3 Collision Count Analysis
The collision count analysis for SHA256 and LHA, considering different sizes of strings per hash, is presented in the Table 3. The collision count is an important metric to assess the robustness and security of hash functions.
Figure 15: Performance of SHA256 and LHA in Term of Execution time
Table 3: Collision Count Analysis for SHA256 and LHA
Size of String per Hash
SHA256 Collision Count
LHA Collision Count
04 Hex 08 Hex 16 Hex 32 Hex
64 Hex (Full Hash code)
6.10621 5.2e-05
0 0 0
6.10645 3.25e-05
0 0 0
4.4.4 Shannon Entropy Analysis
The Shannon Entropy analysis for SHA256 and LHA, considering different sizes of strings per hash, is presented in the Table 4. Shannon Entropy is a measure of uncertainty or information content in a system.
Table 4: Shannon Entropy Analysis for SHA256 and LHA
Size of String per Hash SHA256 Shannon Entropy LHA Shannon Entropy
04 Hex 1.81759 1.81727
08 Hex 2.59429 2.59478
16 Hex 3.2089 3.20719
32 Hex 3.61134 3.61357
64 Hex (Full Hash code) 3.8196 3.82103
4.4.5 Performance Analysis of AES vs LSA and SHA vs LHA on ESP32 Platform
In this configuration, the ESP32-CAM acts as an access point with a WebSocket server and DHT11 sensor, transmitting encrypted data. The M5Stack ESP32 serves as a client, connecting to ESP32-CAM, triggering operations with three buttons, ensuring secure communication and decoding of encrypted data for display.
Table 5: Comparison of LSA and AES Encryption/Decryption Performance for Text-Based Data
Parameter LSA (microseconds) AES (microseconds)
Encryption Time 268 1680
Encryption Time per Block 48 384
Decryption Time 267 2060
Decryption Time per Block 48 464
Data Length 69 bytes 69 bytes
Table 6: Comparison of LSA and AES Encryption/Decryption Performance for Image-Based Data
Parameter LSA (microseconds) AES (microseconds)
Encryption Time 7205 61438
Encryption Time per Block 32 320
Decryption Time 3090 73251
Decryption Time per Block 32 368
Data Length 3056 bytes 3056 bytes
Table 7: Comparison between the Performance of the LSA and AES For Image-based
Data
Algorithm Operation Time Time per Block (N Data Length (bytes) Hash Function Hash Time (N Hash Time per Block (|js)
AES with sha Encrypt 69226 320 3440 SHA256 2037 9
AES with sha Decrypt 82459 368 3440 SHA256 2037 9
LSA with lha Encrypt 8108 32 3440 LHA256 1259 5
LSA with lha Decrypt 8059 32 3440 LHA256 1259 5
Figure 16: Performance analysis of AES vs LSA on text/image based data on IoT Set up
Figure 17: Performance analysis of AES/SHA vs LSA/LHA on text/image based data on
IoT Set up
Tables 5 and 6 compare LSA and AES encryption/decryption performance for text-based and image-based data. Figure 16 illustrates the experimentally evaluated execution time performance of AES and LSA on IoT set up. Tables 7 and 8 compare performance of combination of LSA-LHA and AES-SHA encryption/decryption for text-based and image-based data. Figure 17 illustrates the experimentally evaluated execution time performance of AES-SHA and LSA-LHA on IoT setup.
Table 8: Comparison between the Performance of the LSA and AES for Text based data
Algorithm Operation Time Time per Block (N Data Length (bytes) Hash Function Hash Time (N Hash Time per Block (|js)
AES with sha Encrypt 1755 400 69 SHA256 146 36
AES with sha Decrypt 2016 464 69 SHA256 146 36
LSA with lha Encrypt 311 64 69 LHA256 81 20
LSA with lha Decrypt 281 64 69 LHA256 81 20
Table 9 and 10 detail the throughput of AES and LSA for text-based and image-based data, respectively. Furthermore, Table 11 illustrates the throughput of AES and SHA for image data, while Table 12 showcases the throughput of LSA and LHA for image data.
Table 9: Text-Based Data Throughput of LSA and AES
Parameter LSA Throughput (Mb/s) AES Throughput (Mb/s)
Encryption Throughput 2.06 0.33
Decryption Throughput 2.07 0.27
Data Length 69 bytes 69 bytes
Table 10: Image-Based Data Throughput LSA and AES
Parameter LSA Throughput (Mb/s) AES Throughput (Mb/s)
Encryption Throughput 3.39 0.40
Decryption Throughput 3.41 0.33
Data Length 3056 bytes 3056 bytes
Table 11: AES with SHA Throughput with Image Data
Operation Throughput (Mb/s)
AES Encryption 0.40
AES Decryption 0.33
SHA Hashing 13.51
Table 12: LSA with LHA Throughput with Image Data
Operation Throughput (Mb/s)
LSA Encryption 3.39
LSA Decryption 3.415
LHA Hashing 21.86
The comparison tables show that LSA consistently outperforms AES in encryption and decryption performance for both text-based and image-based data, with lower times per block and higher throughput. When combined with LHA, LSA demonstrates remarkable efficiency, especially for image data, surpassing AES with SHA. These findings highlight LSA's potential for secure and efficient data transmission, particularly in applications like IoT and image processing.
5. Conclusion
Our Hybrid Lightweight Cryptographic System (LCS) is a significant advancement in IoT data security, employing LSA for encryption, ECC for key management, and LHA for integrity verification. Our LHA algorithm outperforms SHA-256, showcasing similar collision resistance in practical scenarios, ensuring enhanced performance without compromising security.Additionally, LSA with LHA exhibits notable performance improvements in comparison with AES128 with SHA256, particularly in real-time image-based data transmission on ESP32. When working with text data, there's an observed approximately 79.5% improvement in performance, and when
working with image data, the improvement is approximately 86.8%. Such improvements have potential implications for real-time applications, particularly where latency is a concern. This study paves the way for future cryptographic optimizations in IoT. Identifying and addressing potential security vulnerabilities in these areas will be a key focus of our future research.
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