# Design Trends and Comparative Analysis of Lightweight Block Ciphers for IoTs
## 4 Related Work
### Hybrid
The primary limitation of ECLBC is its lack of dynamic responsiveness, meaning it cannot adapt in real time to changing security threats or environmental conditions. This constraint stems from its design focus on ultra-low resource environments such as IoMT, where dynamic adaptability would require extra computation, memory, and communication resources that such devices typically cannot afford. As a result, while ECLBC achieves a strong balance between security and reliability, it may require additional external mechanisms to handle evolving threat landscapes or perform real-time adjustments. SFN [61] is an LWBC that integrates both the SP network structure and the Feistel network structure to enhance encryption efficiency and security. By using a 96-bit key and a 64-bit block size, SFN employs a novel encryption method that leverages both network structures for key expansion and encryption or decryption. The control signal from a 32-bit key allows for 232 different operation modes, improving the cipher's resistance to attacks such as differential, linear, meet-in-the-middle, impossible differential, and integral attacks. SFN's round function includes components such as AddRoundKey, S-box layers, MixColumns, MixRows, and MixXors, which collectively improve the security and efficiency of the cipher. It is shown to be compact in hardware (1876.04 GE) and efficient in software, making it suitable for constrained environments such as IoT. One limitation of SFN is the complexity introduced by using both SP and Feistel network structures, which, while enhancing security, could lead to higher resource usage in certain hardware environments compared to simpler designs. Although SFN performs well in terms of security against multiple types of cryptographic attacks, its performance might suffer in highly resource-constrained settings that require faster encryption or lower power consumption. The hybrid nature of SFN also increases the implementation complexity, which could make it harder to optimize for specific applications or adapt to evolving security requirements without significant modifications. GFRX [62] is an LWBC designed for resource-constrained IoTs devices, combining a generalized Feistel structure with ARX (addition or AND, rotation, XOR) operations to enhance diffusion and hardware efficiency. Unlike traditional Feistel structures, which process only half the data per round, GFRX uses four branches and alternates between two ARX-based functions (FAN and FAD) to achieve strong diffusion in fewer rounds. It supports various block/key size combinations (e.g., 64/128 bits) and achieves the avalanche effect within 6 rounds, indicating fast diffusion. GFRX reuses its encryption structure for decryption and key expansion, reducing hardware cost. Hardware evaluations show excellent performance, requiring as little as 886 GE in fully serialized ASIC implementations and outperforming many existing lightweight ciphers such as PRESENT and SIMON in both area and efficiency. Its security is validated up to 19-round differential and 13-round linear attacks, offering a good balance of security, performance, and flexibility for IoTs environments. Despite its efficiency and strong diffusion, the GFRX algorithm has a few notable limitations. Its use of ARX-based round functions introduces lower throughput due to the serial generation of round keys, which can slow down performance in high-speed environments. Additionally, while the design simplifies hardware implementation, its security margin is relatively narrow, with effective differential and linear attacks reaching up to 19 and 13 rounds, respectively, leaving less buffer against future cryptanalytic advances. Furthermore, the structure is highly hardware-oriented, potentially reducing performance and flexibility in software or mixed platforms. These factors may limit GFRX's applicability in use cases demanding high-speed, scalability, or long-term cryptographic strength.