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Security Challenges and Solutions in IoT Networks for the Smart Cities
Published in Mohammad Ayoub Khan, Internet of Things, 2022
When dynamic permutation is used, the order of the collected data from the sensor is changed. In that way, an adversary cannot execute a hardware Trojan with a predefined condition while the processor is processing a dynamically permuted message. The larger the number of permutation patterns allowed, the longer it takes for the attacker to succeed in obtaining the unit design details or even executing an attack. Furthermore, even if the adversary processes any information regarding the processing unit design, the dynamic nature of the permutation method still makes it harder for them to execute an attack or obtain the cryptokey. The cryptographic module of the processor validates the permutation pattern and requests a new one in case it is weak. Hence, the authors used permutation randomness of a 5-bit counter which resulted in a nearly flat accumulated partial guessing entropy with a subkey byte obtaining 2 for 7000 power traces.
Network Reliability and Security
Published in Partha Pratim Sahu, Advances in Optical Networks and Components, 2020
Using the transformation, the eight 4-bit blocks Sj(Bj) are then concatenated and the resulting 32-bit block is transposed by the permutation pattern P shown in Table 9.4. This permutation pattern P is used 16 times for every input block.
Cross-Layer Design in WirelessMAN
Published in Yan Zhang, Hsiao-Hwa Chen, Mobile Wimax, 2007
IEEE 802.16 OFDMA systems support two main modes for subcarrier permutation: distributed and adjacent. Distributed subcarrier permutation can employ frequency diversity effectively by distributing the allocated subcarriers to subchannels using such permutation mechanisms as FUSC, PUSC, OFUSC, and OPUSC (these subchannels are called diversity subchannels). This frequency diversity effect reduces performance degradation due to the fast fading characteristics of mobile environments. In addition, these permutation mechanisms minimize the probability that the same physical subcarriers will be used in adjacent cells and sectors, so this operation results in averaging intercell/sector interference. Adjacent subcarrier permutation can maximize throughput by adaptively allocating adjacent subcarriers according to the characteristics of users’ frequency-selective fading (the sets of these adjacent subcarriers are called band AMC subchannels). Table 9.3 summarizes and compares the characteristics of diversity subchannels and band AMC subchannels [16]. Diversity subchannels have average intercell interference because each cell or sector has a different subcarrier permutation pattern, so one-cell frequency reuse can be implemented. However, cell or sector boundary users using band AMC subchannels may experience severe intercell interference if adjacent cells or sectors use the same sub-carriers, so resources need to be allocated carefully, according to the level of interference. Band AMC mode achieves an improvement in capacity of up to 30% over diversity mode [17,18], but requires more overhead and is more complex than diversity mode because it is necessary to estimate channel quality correctly and a lot of feedback is required in order to report the channel quality for each band. Therefore the use of band AMC mode requires careful cross-layer design, and it is expected that system performance can be improved if diversity mode and band AMC mode are utilized appropriately according to such conditions of MSs as SINR, mobility, and QoS.
Combinatorial diversity metrics for declarative processes: an application to policy process analysis
Published in International Journal of General Systems, 2021
In order to introduce the notion of a (permutation) pattern, we must assume some total order (≼) on Σ. Let be a sequence where and there are no duplicate entries, i.e. all entries of x are unique. A subsequence of x is an occurrence of the pattern if they are order isomorphic: i.e. the smallest (with respect to the order ≼) entry of is in the same position as the smallest (with respect to the order ≤) entry of p, the second smallest entry of is in the same position as the second smallest entry of p, and so on.
Data complexity based hybrid approach to select a model for wind speed forecasting
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2021
Anil Kumar Kushwah, Rajesh Wadhvani
(Acharya, Fujita, and Sudarshan et al. 2015) used the Permutation Entropy (PE), which is developed based on embedding vectors considering specific advantages of time-saving, robustness, and consistency concerning nonlinear monotonous transformations. Specifically, by producing the embedding vectors, sorting each vector’s values in non-decreasing order, and constructing permute patterns considering the offset of permuted values. The PE transforms the time series data, and it is calculated in relation to the probability distribution of all the permute patterns. (Zunino et al. 2017) have suggested using a modified PE, where, unlike the original PE, the identical values in the embedding vector are named in the corresponding permutation pattern in the same order, which assigns them to various orders based on the time of their occurrence.