查看更多>>摘要：In this paper,we numerically demon-strated the possibility of using wurtzite boron gallium ni-tride(W-BGaN)as active layers(quantum well and quantum barriers)along with aluminum gallium nitride(AlGaN)to achieve lasing at a deep ultraviolet range at 263 nm for edge emitting laser diode.The laser diode struc-ture simulations were conducted by using the Crosslight-LASTIP software with a self-consistency model for varies quantity calculations.Moreover,multiple designed struc-tures such as full and half have been achieved as well as the study of the effect of grading engineering/techniques at the electron blocking layer for linearly-graded-down and linearly-graded-up grading techniques were also em-phasized.As a result,a maximum emitted power of 26 W,a minimum threshold current of 308 mA,a slope effi-ciency of 2.82 W/A,and a minimum p-type resistivity of 0.228 Ω cm from the different doping concentrations and geometrical distances were thoroughly observed and jot-ted down.
查看更多>>摘要：This paper presents a high-precision,suc-cessive approximation register(SAR)analog-to-digital converter(ADC)with resistive analog front-end for low-voltage and wide input range applications.To suppress the serious nonlinearity brought by the voltage coeffi-cients of analog front-end without deteriorating differen-tial nonlinearity performance,a mixed-signal calibration scheme based on piecewise-linear method with calibration digital-to-analog converter is proposed.A compensation current is designed to sink or source from the reference to keep it independent of input signal,which greatly im-proves the linearity performance.Fabricated in a 0.5-μm CMOS process,the proposed ADC achieves 88-dB signal-to-noise-and-distortion ratio and 103-dB spurious free dy-namic range with 5-V supply voltage and 2.5-V reference voltage,and the total power consumption is 37.5 mW.
查看更多>>摘要：Many cryptanalytic techniques for sym-metric-key primitives rely on specific statistical analysis to extract some secrete key information from a large num-ber of known or chosen plaintext-ciphertext pairs.For ex-ample,there is a standard statistical model for differen-tial cryptanalysis that determines the success probability and complexity of the attack given some predefined con-figurations of the attack.In this work,we investigate the differential attack proposed by Guo et al.at Fast Soft-ware Encryption Conference 2020 and find that in this at-tack,the statistical behavior of the counters for key can-didates deviate from standard scenarios,where both the correctkey and the correct key xor specific difference are expected to receive the largest number of votes.Based on this bimodal behavior,we give three different statistical models for truncated differential distinguisher on CRAFT(a cryptographic algorithm name)for bimodal phenom-ena.Then,we provide the formulas about the success probability and data complexity for different models un-der the condition of a fixed threshold value.Also,we veri-fy the validity of our models for bimodal phenomena by experiments on round-reduced of the versions distinguish-ers on CRAFT.We find that the success probability of theory and experiment are close when we fix the data complexity and threshold value.Finally,we compare the three models using the mathematical tool Matlab and conclude that Model 3 has better performance.
查看更多>>摘要：Type-Ⅰ generalized Feistel networks(GFN)are widely used frameworks in symmetric-key primitive designs such as CAST-256 and Lesamnta.Dif-ferent from the extensive studies focusing on specific block cipher instances,the analysis against Type-Ⅰ GFN structures gives generic security evaluation of the basic frameworks and concentrates more on the effect of linear transformation.Currently,works in this field mainly eval-uate the security against impossible differential attack,zero-correlation linear attack,meet-in-the-middle attack and yoyo game attack,while its security evaluation against rectangle attack is still missing.In this paper,we filled this gap and gave the first structural analytical res-ults of Type-Ⅰ GFN against rectangle attack.By exploit-ing its structural properties,we proved there exists a boomerang switch for Type-Ⅰ GFN for the first time,which is independent of the round functions.Then we turned the boomerang switch into chosen plaintext set-ting and proposed a new rectangle attack model.By ap-pending 1 more round in the beginning of the boomerang switch,we constructed a rectangle distinguisher and a key recovery attack could be performed.
查看更多>>摘要：Edge-cloud collaborative application scenario is more complex,it involves collaborative opera-tions among different security domains,frequently access-ing and exiting application system of mobile terminals.A cross-domain identity authentication protocol based on privacy protection is proposed.The main advantages of the protocol are as follows.1)Self-certified key genera-tion algorithm:the public/private key pair of the mobile terminal is generated by the terminal members them-selves.It avoids security risks caused by third-party key distribution and key escrow;2)Cross-domain identity au-thentication:the alliance keys are calculated among edge servers through blockchain technology.Cross-domain identity authentication is realized through the signature authentication of the alliance domain.The cross-domain authentication process is simple and efficient;3)Revocab-ility of identity authentication:When the mobile termin-al has logged off or exited the system,the legal identity of the terminal in the system will also become invalid imme-diately,so as to ensure the forward and backward secur-ity of accessing system resources.Under the hardness as-sumption of discrete logarithm problem and computation-al Diffie-Hellman problem,the security of the protocol is proven,and the efficiency of the protocol is verified.
查看更多>>摘要：Data recovery from flash memory in the mobile device can effectively reduce the loss caused by data corruption.Type recognition of data fragment is an essential prerequisite to the low-level data recovery.Pre-vious works in this field classify data fragment based on its file type.Still,the classification efficiency is low,espe-cially when the data fragment is a part of a composite file.We propose a fine-grained approach to classifying data fragment from the low-level flash memory to improve the classification accuracy and efficiency.The proposed meth-od redefines flash-memory-page data recognition problem based on the encoding format of the data segment,and applies a hybrid machine learning algorithm to detect the data type of the flash page.The hybrid algorithm can sig-nificantly decompose the given data space and reduce the cost of training.The experimental results show that our method achieves better classification accuracy and higher time performance than the existing methods.
查看更多>>摘要：With the popularization and develop-ment of social software,more and more people join the social network,which produces a lot of valuable informa-tion,but also contains plenty of sensitive privacy informa-tion.To achieve the personalized privacy protection of masssive social network relational data,a privacy enhance-ment method for social networks relational data based on personalized differential privacy is proposed.And a di-mensionality reduction segmentation sampling(DRS-S)algorithm is proposed to implement this method.First,in order to solve the problem of inefficiency caused by the excessive amount of data in social networks,dimension re-duction and segmentation are carried out to divide the data into groups.According to the privacy protection re-quirements of different users,we adopt sampling method to protect users with different privacy requirements at different levels,so as to realize personalized different pri-vacy.After that,the noise is added to the protected data to satisfy the privacy budget.Then publish the social net-work data.Finally,the proposed algorithm is compared with the traditional personalized differential privacy(PDP)algorithm and privacy preserving approach based on clustering and noise(PBCN)in real data set,the ex-perimental results demonstrate that the quality of pri-vacy protection and data availability of DRS-S are better than that of PDP algorithm and PBCN algorithm.
查看更多>>摘要：Residual computation is an effective method for gray-scale image steganalysis.For binary im-ages,the residual computation calculated by the XOR op-eration is also employed in the local residual patterns(LRP)model for steganalysis.A binary image steganalyt-ic scheme based on symmetrical local residual patterns(SLRP)is proposed.The symmetrical relationships among residual patterns are introduced that make the features more compact while reducing the dimensionality of the features set.Multi-scale windows are utilized to construct three SLRP submodels which are further merged to con-struct the final features set instead of a single model.SLRPs with higher probability to be modified after em-bedding are emphasized and selected to construct the fea-ture sets for training the support vector machine classifi-er.The experimental results show that the proposed steganalytic scheme is effective for detecting binary im-age steganography.
查看更多>>摘要：By allowing intermediate nodes to com-bine multiple packets before forwarding them,the concept of network coding in multi-cast networks can provide maximum possible information flow.However,this also means traditional encryption methods are less applicable,since the different public-keys of receivers imply different ciphertexts which cannot be easily combined by network coding.While network coding itself may provide confiden-tiality,its effectiveness heavily depends on the underly-ing network topology and ability of the eavesdroppers.Fi-nally,broadcast encryption and group key agreement techniques both allow a sender to broadcast the same ciphertext to all the receivers,although they rely on the assumptions of trusted key servers or secure channels.In this paper,we propose a novel public-key encryption concept with a single public-key for encryption and mul-tiple secret keys for decryption(MSK-PK),which has limited ciphertext expansion and does not require trusted key servers or secure channels.To demonstrate the feas-ibility of this concept,we construct a concrete scheme based on a class of lattice-based multi-trapdoor functions.We prove that those functions satisfy the one-wayness property and can resist the nearest plane algorithm.
查看更多>>摘要：The dynamic code loading mechanism of the Android system allows an application to load execut-able files externally at runtime.This mechanism makes the development of applications more convenient,but it also brings security issues.Applications that hide mali-cious behavior in the external file by dynamic code load-ing are becoming a new challenge for Android malware detection.To overcome this challenge,based on dynamic code loading mechanisms,three types of threat models,i.e.Model Ⅰ,Model Ⅱ,and Model Ⅲ are defined.For the Model Ⅰ type malware,its malicious behavior occurs in DexCode,so the application programming interface(API)classes were used to characterize the behavior of the Dex-Code file.For the Model Ⅱ type and Model Ⅲ type mal-wares whose malicious behaviors occur in an external file,the permission complement is defined to characterize the behaviors of the external file.Based on permission com-plement and API calls,an Android malicious application detection method is proposed,of which feature sets are constructed by improving a feature selection method.Five datasets containing 15,581 samples are used to evaluate the performance of the proposed method.The experi-mental results show that our detection method achieves accuracy of 99.885％on general dataset,and performes the best on all evaluation metrics on all datasets in all com-parison methods.
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