DNA-based cryptographic techniques have attracted significant interest due to their intrinsic parallelism, high algorithmic complexity, and bio-inspired randomness. However, their practical applicability in resource-constrained Internet of Things (IoT) environments remains insufficiently explored. This study presents a comprehensive performance evaluation of six representative DNA-based encryption schemes—DNA-XOR-Mutation, DNA-Substitution-Shift, Hybrid DNA-Logical Encoding, DNA-Crossover-Encode, DNA-Logical-Shift, and DNA-Hybrid-Crypt—implemented and experimentally measured on embedded platforms typical of IoT devices. These schemes were benchmarked against established lightweight cryptographic algorithms, including PRESENT-80, ASCON-128, SPECK-64, TWINE-80, HIGHT, SIMON-64/128, and LED-64, using an experimental measurement environment configured to reflect the specifications of widely deployed microcontrollers such as ATmega328P, STM32F0, ESP32, nRF52840, PIC24FJ64GA, and MSP430. Performance metrics encompassed execution time, ROM/RAM memory footprint, and energy consumption. The results indicate that while DNA-based algorithms generally demand greater memory resources and exhibit higher latency than hardware-optimized lightweight ciphers, they demonstrate superior diffusion properties and enhanced resistance against classical differential cryptanalysis. These findings highlight the promise of DNA-inspired cryptography as a complementary security mechanism for next-generation IoT systems, particularly in scenarios requiring polymorphic or non-deterministic encryption approaches. Finally, we discuss optimization strategies and hardware integration considerations, offering a performance-driven foundation for further research into DNA-based cryptographic primitives within IoT security frameworks.