Differential cryptanalysis of new Qamal encryption algorithm

Currently, the Republic of Kazakhstan is developing a new standard for symmetric data encryption. One of the candidates for the role of the standard is the Qamal encryption algorithm developed by the Institute of Information and Computer Technologies (Almaty, Republic of Kazakhstan). The article describes the algorithm. Differential properties of the main operations that make up the Qamal cypher are considered in the questions of stability. We have shown that for a version with a 128-bit data block and the same secret key size for three rounds of encryption it is difficult to find the right pairs of texts with a probability of 2–120, which makes differential cryptanalysis not applicable to the Qamal cyphe

Maximums of the Additive Differential Probability of Exclusive-Or

At FSE 2004, Lipmaa et al. studied the additive differential probability adp⊕(α,β → γ) of exclusive-or where differences α,β,γ ∈ Fn2 are expressed using addition modulo 2n. This probability is used in the analysis of symmetric-key primitives that combine XOR and modular addition, such as the increasingly popular Addition-Rotation-XOR (ARX) constructions. The focus of this paper is on maximal differentials, which are helpful when constructing differential trails. We provide the missing proof for Theorem 3 of the FSE 2004 paper, which states that maxα,βadp⊕(α,β → γ) = adp⊕(0,γ → γ) for all γ. Furthermore, we prove that there always exist either two or eight distinct pairs α,β such that adp⊕( α,β → γ) = adp⊕(0,γ → γ), and we obtain recurrence formulas for calculating adp⊕. To gain insight into the range of possible differential probabilities, we also study other properties such as the minimum value of adp⊕(0,γ → γ), and we find all γ that satisfy this minimum value

Trusted Operation of Cyber-Physical Processes Based on Assessment of the System’s State and Operating Mode

We consider the trusted operation of cyber-physical processes based on an assessment of the system’s state and operating mode and present a method for detecting anomalies in the behavior of a cyber-physical system (CPS) based on the analysis of the data transmitted by its sensory subsystem. Probability theory and mathematical statistics are used to process and normalize the data in order to determine whether or not the system is in the correct operating mode and control process state. To describe the mode-specific control processes of a CPS, the paradigm of using cyber-physical parameters is taken as a basis, as it is the feature that most clearly reflects the system’s interaction with physical processes. In this study, two metrics were taken as a sign of an anomaly: the probability of falling into the sensor values’ confidence interval and parameter change monitoring. These two metrics, as well as the current mode evaluation, produce a final probability function for our trust in the CPS’s currently executing control process, which is, in turn, determined by the operating mode of the system. Based on the results of this trust assessment, it is possible to draw a conclusion about the processing state in which the system is operating. If the score is higher than 0.6, it means the system is in a trusted state. If the score is equal to 0.6, it means the system is in an uncertain state. If the trust score tends towards zero, then the system can be interpreted as unstable or under stress due to a system failure or deliberate attack. Through a case study using cyber-attack data for an unmanned aerial vehicle (UAV), it was found that the method works well. When we were evaluating the normal flight mode, there were no false positive anomaly estimates. When we were evaluating the UAV’s state during an attack, a deviation and an untrusted state were detected. This method can be used to implement software solutions aimed at detecting system faults and cyber-attacks, and thus make decisions about the presence of malfunctions in the operation of a CPS, thereby minimizing the amount of knowledge and initial data about the system

Maximums of the Additive Differential Probability of Exclusive-Or

At FSE 2004, Lipmaa et al. studied the additive differential probability adp⊕(α,β → γ) of exclusive-or where differences α,β,γ ∈ Fn2 are expressed using addition modulo 2n. This probability is used in the analysis of symmetric-key primitives that combine XOR and modular addition, such as the increasingly popular Addition-Rotation-XOR (ARX) constructions. The focus of this paper is on maximal differentials, which are helpful when constructing differential trails. We provide the missing proof for Theorem 3 of the FSE 2004 paper, which states that maxα,βadp⊕(α,β → γ) = adp⊕(0,γ → γ) for all γ. Furthermore, we prove that there always exist either two or eight distinct pairs α,β such that adp⊕( α,β → γ) = adp⊕(0,γ → γ), and we obtain recurrence formulas for calculating adp⊕. To gain insight into the range of possible differential probabilities, we also study other properties such as the minimum value of adp⊕(0,γ → γ), and we find all γ that satisfy this minimum value