# A Survey on Recent Advanced Research of CPS Security
## 3 Reviews
### Lightweight Cryptography  
Lightweight cryptography is an encryption method that features low computational complexity. It aims at expanding the applications of cryptography to embedded devices. Recently, researchers have proposed or improved lightweight cryptography algorithms for different scenarios. Given the limitations of processing power, energy, and memory, a light and quick cryptography algorithm is needed in an IoT system to provide high-level security. [PERSON] et al. [103] chose a family of lightweight elliptic curves in an IoT scenario that extracts the advantages of the emerging Montgomery and twisted Edwards curves. To solve the problem of resource limitation, the authors proposed two different versions of this algorithm: high-speed and memory-efficient versions; both versions are robust against timings and SPA attacks. In their work, they developed a new approach for energy consumption evaluation depending on the performance and communication costs between objects, which could be useful for further research. LEDs are AES-like lightweight ciphers of two key sizes that are widely used in IoT devices. [PERSON] et al. [102] proposed a ciphertext-only fault analysis method with six distinguishers (SEI, GF, GF-SEI, ML, HW, and MAP) on LEDs in the random nibble-oriented fault model. The simulation experiments proved that the analysis could restore64-bit and 128-bit secret keys of LEDs with over 99 percent probability by injecting fault locations into the deeper round. [PERSON] et al. [101] proposed an ultralightweight encryption scheme to protect resource-limited embedded devices. In an untrusted environment, this encryption algorithm is robust against white-box attacks without requiring massive memory use. It requires a small amount of static data, ranging from 48 to 92 KB for 10-32 rounds. After being theoretically analyzed, both the security and efficiency of this scheme were proven to be very good. Given that many developers improperly encapsulate crypto functions into IoT devices, CRYPTOREX [100] is implemented to analyze the problem of crypto misuses on a large scale. CRYPTOREX utilizes stack layout recovery and dynamically updates the API list to tackle function arguments during static taint analysis across multiple architectures. When it was executed on 521 firmware images with 165 predefined crypto APIs, CRYPTOREX successfully found 679 crypto misuse issues in total, which shows that 24.2% of firmware images disobey at least one misuse rule. [PERSON] and [PERSON] [104] proposed unique elliptic curves, namely, nothing upon my sleeves (NUMS) curves, and implemented the NUMS256, NUMS379, and NUMS384 curves on two kinds of embedded devices. The authors combined the individual computational strengths of the twisted Edward and Montgomery curves and the efficient pseudo-Mersenne primes. Their experimental results also showed that NUMS requires fewer memory resources than the widely used Curve25519 and executing NUMS in constant time can prevent an embedded device from timing and simple-side channel attacks. [PERSON] et al. [20] proposed an efficient image encryption algorithm based on the architecture of diffusion and confusion. First, the initial conditions of the hyperchaotic Chen system were determined by plain imaging, which guarantees changes in chaotic sequences. Then, the plain images were encrypted by the chaotic sequence with pixel scrambling, image encryption, and cyclic shift. The XOR operation was also constructed to improve the correlation between pixels, thus resisting plaintext attacks. The simulation results and theoretical analysis proved that this scheme is efficient in key sensitivity, correlation, information entropy, and computation time and can defend against differential and chosen-plaintext attacks. Compressed sensing is simple lightweight cryptography, but its security is not perfect. [PERSON] et al. [105] adapted an encoder to the statistical features of an acquired signal.