摘要：
In recent years, the combination of deep learning and side-channel analysis has received extensive attention. Previous research has shown that the key recovery problem can be transformed into a classification problem. The performance of these models strongly depends on the size of the dataset and the number of instances in each target class. The training time is very long. In this paper, the key recovery problem is transformed into a similarity measurement problem in Siamese neural networks. We use simulated power traces and true power traces to form power pairs to augment data and simplify key recovery steps. The trace pairs are selected based on labels and added to the training to improve model performance. The model adopts a Siamese, CNN-based architecture, and it can evaluate the similarity between the inputs. The correct key is revealed by the similarity of different trace pairs. In experiments, three datasets are used to evaluate our method. The results show that the proposed method can be successfully trained with 1000 power traces and has excellent attack efficiency and training speed.
通讯机构：
[Lang Li] C;College of Computer Science and Technology, Hengyang Normal University, Hengyang, China<&wdkj&>Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, China
关键词：
internet of things;5G;dynamic S-box;bit-slice technology;lightweight block cipher
通讯机构：
[Li, L ] H;Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.
关键词：
area-optimized;high throughput;Internet of Things;lightweight;LILLIPUT block cipher
摘要：
The relationship between encryption algorithm and key scheduling algorithm is utilized to achieve optimal sharing among components, which significantly reduces hardware area. The number of XOR gates and S‐boxes required for low area optimization is reduced by 52 and 8, respectively. Summary The widespread use of Internet of Things devices has increased the demand for lower cost and more efficient lightweight ciphers. However, there is a difficult trade‐off between cost and efficiency for lightweight block ciphers. The optimizations of area and throughput are important for some constrained environments. This paper proposes two novel hardware architectures for the LILLIPUT cipher. In the novel low area structure, a new permutation layer is provided for LILLIPUT. The relationship between encryption algorithm and key scheduling algorithm is utilized to achieve optimal sharing among components, which significantly reduces hardware area. The experimental results show that the number of XOR gates and S‐boxes required for low area optimization is reduced by 52 and 8, respectively. The total area is reduced by about 18%. For high throughput structure, this paper provides 2‐round, 5‐round, and 15‐round loop unrolling designs for LILLIPUT to improve throughput. The experimental results show that the throughput of the 5‐round loop unrolling structure reaches a good level, which is relatively the most cost‐effective. In practical application, ciphers can be unrolled implementations according to the needs of devices to improve the execution speed, which can greatly reduce the execution time and complexity of the algorithm.
期刊：
Fuzzy Sets and Systems,2022年426:27-45 ISSN：0165-0114
通讯作者：
Li, Long
作者机构：
[Li, Long] Hengyang Normal Univ, Coll Math & Stat, Hengyang, Hunan, Peoples R China.;[Long, Zuqiang] Hengyang Normal Univ, Coll Phys & Elect Engn, Hengyang, Hunan, Peoples R China.;[Ying, Hao] Wayne State Univ, Dept Elect & Comp Engn, Detroit, MI 48202 USA.;[Qiao, Zhijun] Univ Texas Rio Grande Valley, Dept Math, Edinburg, TX 78539 USA.
通讯机构：
[Li, Long] H;Hengyang Normal Univ, Coll Math & Stat, Hengyang, Hunan, Peoples R China.
通讯机构：
[Li, L ] H;Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.;Hengyang Normal Univ, Hunan Prov Key Lab Intelligent Informat Proc & Ap, Hengyang 421002, Peoples R China.
关键词：
Differential power analysis;Hamming weight;Ghost peaks;AES
摘要：
Differential power analysis (DPA) is disturbed by ghost peaks. There is a phenomenon that the mean absolute difference (MAD) value of the wrong key is higher than the correct key. We propose a compressed key guessing space (CKGS) scheme to solve this problem and analyze the AES algorithm. The DPA based on this scheme is named CKGS-DPA. Unlike traditional DPA, the CKGS-DPA uses two power leakage points for a combined attack. The first power leakage point is used to determine the key candidate interval, and the second is used for the final attack. First, we study the law of MAD values distribution when the attack point is AddRoundKey and explain why this point is not suitable for DPA. According to this law, we modify the selection function to change the distribution of MAD values. Then a key-related value screening algorithm is proposed to obtain key information. Finally, we construct two key candidate intervals of size 16 and reduce the key guessing space of the SubBytes attack from 256 to 32. Simulation experimental results show that CKGS-DPA reduces the power traces demand by 25% compared with DPA. Experiments performed on the ASCAD dataset show that CKGS-DPA reduces the power traces demand by at least 41% compared with DPA.
通讯机构：
[Lang Li] C;College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, China<&wdkj&>Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, 421002, China
通讯机构：
[Lang Li] C;College of Computer Science and Technology, Hengyang Normal University, Hengyang, China<&wdkj&>Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang Normal University, Hengyang, China
关键词：
Side channel analysis;Deep learning;Signal processing;Random convolution kernel
期刊：
Cognitive Systems Research,2021年68:62-72 ISSN：1389-0417
通讯作者：
Gao, T.;Wang, J.
作者机构：
[Li, Long] Hengyang Normal Univ, Coll Math & Stat, Henyang 421001, Peoples R China.;[Xie, Xuetao] Sichuan Univ, Coll Comp Sci, Chengdu 610065, Peoples R China.;[Gao, Tao] Beihang Univ, Sch Comp Sci & Engn, Beijing 100191, Peoples R China.;[Wang, Jian] China Univ Petr, Coll Sci, Qingdao 266580, Peoples R China.
通讯机构：
[Gao, T.] S;[Wang, J.] C;School of Computer Science and Engineering, Beihang University, Beijing 100191, China
关键词：
Armijo;Conjugate gradient;Convergence;Elman
摘要：
Elman recurrent network is a representative model with feedback mechanism. Although gradient descent method has been widely used to train Elman network, it frequently leads to slow convergence. According to optimization theory, conjugate gradient method is an alternative strategy in searching the descent direction during training. In this paper, an efficient conjugate gradient method has been presented to reach the optimal solution in two ways: (1) constructing a more effective conjugate coefficient, (2) determining adaptive learning rates in terms of the generalized Armijo search method. Experiments show that the performance of the new algorithm is superior to traditional algorithms, such as gradient descent method and conjugate gradient method. In particular, the new algorithm has better performance than the evolutionary algorithm. Finally, we prove the weak and strong convergence of the presented algorithm, i.e., the gradient norm of the error function with respect to the weight vectors converges to zero and the weight sequence approaches a fixed optimal point. (C) 2021 Elsevier B.V. All rights reserved.
作者机构：
[Li, Long; Long, Zuqiang] Hengyang Normal Univ, Coll Math & Stat, Hengyang 421008, Hunan, Peoples R China.;[Qiao, Zhijun] Univ Texas Rio Grande Valley, Dept Math, Edinburg, TX 78539 USA.
通讯机构：
[Li, Long] H;Hengyang Normal Univ, Coll Math & Stat, Hengyang 421008, Hunan, Peoples R China.
摘要：
In this paper, a smoothing algorithm with constant learning rate is presented for training two kinds of fuzzy neural networks (FNNs): max-product and max-min FNNs. Some weak and strong convergence results for the algorithm are provided with the error function monotonically decreasing, its gradient going to zero, and weight sequence tending to a fixed value during the iteration. Furthermore, conditions for the constant learning rate are specified to guarantee the convergence. Finally, three numerical examples are given to illustrate the feasibility and efficiency of the algorithm and to support the theoretical findings.
期刊：
JOURNAL OF EXPERIMENTAL BOTANY,2019年70(15):3969-3979 ISSN：0022-0957
通讯作者：
Tang, Kexuan;Chen, Wansheng;Zhang, Lei
作者机构：
[Ma, Yanan; Li, Ling; Fu, Xueqing; Shen, Qian; Zhang, Fangyuan; Hao, Xiaolong; Zhang, Lida; Lv, Zongyou; Shi, Pu; Chen, Minghui; Tang, Kexuan; Yan, Tingxiang] Shanghai Jiao Tong Univ, Joint Int Res Lab Metab & Dev Sci, Key Lab Urban Agr South, Minist Agr,Plant Biotechnol Res Ctr,Fudan SJTU No, Shanghai 200240, Peoples R China.;[Chen, Wansheng; Lv, Zongyou] Second Mil Med Univ, Changzheng Hosp, Dept Pharm, Shanghai 200003, Peoples R China.;[Chen, Wansheng; Lv, Zongyou] Shanghai Univ Tradit Chinese Med, Res & Dev Ctr Chinese Med Resources & Biotechnol, Shanghai 201203, Peoples R China.;[Zhang, Lei; Guo, Zhiying] Second Mil Med Univ, Sch Pharm, Dept Pharmaceut Bot, Shanghai 200433, Peoples R China.;[Jiang, Weimin] Hengyang Normal Univ, Coll Life Sci & Environm, Hengyang 421008, Hunan, Peoples R China.
通讯机构：
[Tang, Kexuan; Chen, Wansheng; Zhang, Lei] S;[Zhang, Lei] Z;Shanghai Jiao Tong Univ, Joint Int Res Lab Metab & Dev Sci, Key Lab Urban Agr South, Minist Agr,Plant Biotechnol Res Ctr,Fudan SJTU No, Shanghai 200240, Peoples R China.;Second Mil Med Univ, Changzheng Hosp, Dept Pharm, Shanghai 200003, Peoples R China.;Shanghai Univ Tradit Chinese Med, Res & Dev Ctr Chinese Med Resources & Biotechnol, Shanghai 201203, Peoples R China.
摘要：
Artemisinin is a sesquiterpene lactone produced by the Chinese traditional herb Artemisia annua and is used for the treatment of malaria. It is known that salicylic acid (SA) can enhance artemisinin content but the mechanism by which it does so is not known. In this study, we systematically investigated a basic leucine zipper family transcription factor, AaTGA6, involved in SA signaling to regulate artemisinin biosynthesis. We found specific in vivo and in vitro binding of the AaTGA6 protein to a 'TGACG' element in the AaERF1 promoter. Moreover, we demonstrated that AaNPR1 can interact with AaTGA6 and enhance its DNA-binding activity to its cognate promoter element 'TGACG' in the promoter of AaERF1, thus enhancing artemisinin biosynthesis. The artemisinin contents in AaTGA6-overexpressing and RNAi transgenic plants were increased by 90-120% and decreased by 20-60%, respectively, indicating that AaTGA6 plays a positive role in artemisinin biosynthesis. Importantly, heterodimerization with AaTGA3 significantly inhibits the DNA-binding activity of AaTGA6 and plays a negative role in target gene activation. In conclusion, we demonstrate that binding of AaTGA6 to the promoter of the artemisinin-regulatory gene AaERF1 is enhanced by AaNPR1 and inhibited by AaTGA3. Based on these findings, AaTGA6 has potential value in the genetic engineering of artemisinin production.
通讯机构：
[Li, Lang] H;Hengyang Normal Univ, Hunan Prov Key Lab Intelligent Informat Proc & Ap, Hengyang 421002, Peoples R China.;Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.
关键词：
Block cipher;Internet of Things;Involution;Lightweight cryptography;SPN structure
摘要：
In past few years, as security ciphers in the Internet of Things (IoT), the research of lightweight block cipher has attracted tremendous attention in cryptography. The SPN structure has been widely used in the design of block cipher. However, the encryption and decryption processes of ciphers based on the SPN structure are different. We design a new SPN structure, which is perfect for lightweight block cipher. The new SPN structure makes that the encryption process is the same as decryption. Moreover, input and output data directions are the same for encryption and decryption processes. Thus, the same process can absolutely be shared in decryption and encryption both for software and hardware implementation. Further, we propose a family of involutional lightweight block cipher, called Loong, based on the proposed SPN structure and components. Rigorous analysis indicates that Loong is of high security against cryptanalysis, especially the differential attack and linear attack. As shown by our experiments and comparisons, Loong is compact in hardware environment and is suitable for the IoT.
期刊：
BULLETIN OF THE AUSTRALIAN MATHEMATICAL SOCIETY,2019年99(3):421-431 ISSN：0004-9727
通讯作者：
Ponnusamy, Saminathan
作者机构：
[Li, Liulan] Henyang Normal Univ, Hunan Prov Key Lab Intelligent Informat Proc & Ap, Hengyang 421002, Hunan, Peoples R China.;[Ponnusamy, Saminathan] Indian Inst Technol Madras, Dept Math, Chennai 600036, Tamil Nadu, India.
通讯机构：
[Ponnusamy, Saminathan] I;Indian Inst Technol Madras, Dept Math, Chennai 600036, Tamil Nadu, India.
关键词：
convex in a direction;convex mapping;convolution;harmonic;slanted half-plane mapping;univalent
摘要：
Dorff et al. \cite{DN} formulated an open problem concerning the convolution of two right half-plane mappings, where the normalization of the harmonic mappings has been considered incorrectly. Without realizing the error, the present authors considered the open problem (see \cite[Theorem 2.2]{LiPo1} and \cite[Theorem 1.3]{LiPo2}). In this paper, we have reformulated the open problem in correct form and provided solution to it in a more general form. In addition, we also obtain two new results which correct and improve some other results.
摘要：
In order to broaden the study of the most popular and general Takagi-Sugeno (TS) system, we propose a complex-valued neuro-fuzzy inference system which realises the zero-order TS system in the complex-valued network architecture and develop it. In the complex domain, boundedness and analyticity cannot be achieved together. The splitting strategy is given by computing the gradients of the real-valued error function with respect to the real and the imaginary parts of the weight parameters independently. Specifically, this system has four layers: in the Gaussian layer, the L-dimensional complex-valued input features are mapped to a Q-dimensional real-valued space, and in the output layer, complex-valued weights are employed to project it back to the complex domain. Hence, split-complex valued gradients of the real-valued error function are obtained, forming the split-complex valued neuro-fuzzy (split-CVNF) learning algorithm based on gradient descent. Another contribution of this paper is that the deterministic convergence of the split-CVNF algorithm is analysed. It is proved that the error function is monotone during the training iteration process, and the sum of gradient norms tends to zero. By adding a moderate condition, the weight sequence itself is also proved to be convergent.
摘要：
<jats:p>While the existence of conformal mappings between doubly connected domains is characterized by their conformal moduli, no such characterization is available for harmonic diffeomorphisms. Intuitively, one expects their existence if the domain is not too thick compared to the codomain. We make this intuition precise by showing that for a Dini-smooth doubly connected domain <jats:italic>Ω*</jats:italic> there exists a <jats:italic>ε ></jats:italic> 0 such that for every doubly connected domain <jats:italic>Ω</jats:italic> with Mod<jats:italic>Ω* <</jats:italic> Mod<jats:italic>Ω <</jats:italic> Mod<jats:italic>Ω*</jats:italic> + <jats:italic>ε</jats:italic> there exists a harmonic diffeomorphism from <jats:italic>Ω</jats:italic> onto <jats:italic>Ω*</jats:italic>.</jats:p>
