An Efficient and Provably Secure SM2 Key-Insulated Signature Scheme for Industrial Internet of Things

With the continuous expansion of the Industrial Internet of Things(IIoT),more andmore organisations are placing large amounts of data in the cloud to reduce overheads.However,the channel between cloud servers and smart equipment is not trustworthy,so the issue of data authenticity needs to be addressed.The SM2 digital signature algorithm can provide an authentication mechanism for data to solve such problems.Unfortunately,it still suffers from the problem of key exposure.In order to address this concern,this study first introduces a key-insulated scheme,SM2-KI-SIGN,based on the SM2 algorithm.This scheme boasts strong key insulation and secure keyupdates.Our scheme uses the elliptic curve algorithm,which is not only more efficient but also more suitable for IIoT-cloud environments.Finally,the security proof of SM2-KI-SIGN is given under the Elliptic Curve Discrete Logarithm(ECDL)assumption in the random oracle.

Exploration and Practice of Postgraduate Training Mode Based on Medical Imaging Information Security

In the process of continuous maturity and development of medical imaging diagnosis,it is common to transmit images through public networks.How to ensure the security of transmission,cultivate talents who combine medical imaging and information security,and explore and cultivate new discipline growth points are difficult problems and challenges for schools and educators.In order to cope with industrial changes,a new round of scientific and technological revolution,and the challenges of the further development of artificial intelligence in medicine,this article will analyze the existing problems in the training of postgraduates in medical imaging information security by combining the actual conditions and characteristics of universities,and put forward countermeasures and suggestions to promote the progress of technology in universities.

Research and Exploration on the Construction of Double Qualified Teachers in Software Engineering

In order to solve the problem of insufficient integration of school-enterprise supervisors in the current school-enterprise cooperation model,this article introduces the ideas and results of the construction of a team with double-qualified instructors majored in software engineering.Specifically,the integration of production and education are carried out in three stages,i.e.,enterprise cooperation courses,enterprise internship,and graduation design(internship),by taking the software engineering major of the School of Information and Software Engineering of the University of Electronic Science and Technology of China as a case study.

Teaching and Practice of Database Course for Software Engineering Ability Training

In view of the fact that the relevant courses of undergraduate database are not systematic,this paper discusses the relevant requirements of database courses from the perspective of the ability training of software engineering.It gives the problem-oriented classroom and experimental design of the course content module,designs and develops the course learning platform,analyzes the data of the teaching effect,and explains the effectiveness of course teaching.

Consideration of Postgraduate Training under the Cross Field of Medical Information and Engineering

The slogan of“Combination of medicine and engineering”proposed in“Made in China 2025”has aroused great attention to higher engineering education.However,it is a difficult problem and challenge for schools and educators to effectively adapt to the economic and social development,train new medical and engineering talents,and explore and cultivate new subject growth points.In order to deal with engineering change and a new round of scientific and technological revolution,facing the challenge of new engineering construction.This paper will combine the reality and characteristics of colleges and universities,analyze the problems existing in the current medical engineering cross-graduate training,and put forward countermeasures and suggestions to promote the progress and development of science and technology in colleges and universities.

Reform and Practice of Software Engineering Teaching under the Background of Emerging Engineering Education

This paper analyzes the new demands of software engineering talent training under the background of emerging engineering education,in order to clarify the direction of software engineering teaching reform,and discusses the issue of how to build core competencies of software engineering talent.This paper takes“consolidating professional foundation,training practical ability and improving innovation ability”as the goal of software engineering talent training,puts forward the conception of software engineering teaching reform with“reconstructing the core course platform,improving the practice teaching system,and creating an innovation training environment”,and expounds the teaching reform practice activities based on this conception.Finally,the paper summarizes the achievements of teaching reform.

Design of multilayer cellular neural network based on memristor crossbar and its application to edge detection

Memristor with memory properties can be applied to connection points(synapses)between cells in a cellular neural network(CNN).This paper highlights memristor crossbar-based multilayer CNN(MCM-CNN)and its application to edge detection.An MCM-CNN is designed by adopting a memristor crossbar composed of a pair of memristors.MCM-CNN based on the memristor crossbar with changeable weight is suitable for edge detection of a binary image and a color image considering its characteristics of programmablization and compactation.Figure of merit(FOM)is introduced to evaluate the proposed structure and several traditional edge detection operators for edge detection results.Experiment results show that the FOM of MCM-CNN is three times more than that of the traditional edge detection operators.

Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017,it was first used for machine translation tasks and achieved the state of the art at that time.Although the current neural machine translation model can generate high quality translation results,there are still mistranslations and omissions in the translation of key information of long sentences.On the other hand,the most important part in traditional translation tasks is the translation of key information.In the translation results,as long as the key information is translated accurately and completely,even if other parts of the results are translated incorrect,the final translation results’quality can still be guaranteed.In order to solve the problem of mistranslation and missed translation effectively,and improve the accuracy and completeness of long sentence translation in machine translation,this paper proposes a key information fused neural machine translation model based on Transformer.The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder.After the same encoding as the source language text,it is fused with the output of the source language text encoded by the encoder,then the key information is processed and input into the decoder.With incorporating keyword information from the source language sentence,the model’s performance in the task of translating long sentences is very reliable.In order to verify the effectiveness of the method of fusion of key information proposed in this paper,a series of experiments were carried out on the verification set.The experimental results show that the Bilingual Evaluation Understudy(BLEU)score of the model proposed in this paper on theWorkshop on Machine Translation(WMT)2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset.The experimental results show the advantages of the model proposed in this paper.

Exploration of the Training Mode of School-enterprise Collaborative AI Innovative Talents Based on PaddlePaddle

This paper takes the school-enterprise cooperation between the University of Electronic Science and Technology of China(UESTC)and Baidu(China)Co.,Ltd.as an example to build the Paddle Paddle(Sichuan)AI Education Innovation Center by enjoying the best of both UESTC and Baidu(China),and cooperating with 16 universities in Sichuan Province.With the support of this center,both the school and the enterprise successfully built a school-enterprise collaborative AI innovative talent training model,which mainly serves the universities,industries,and districts.Furthermore,this training model is able to facilitate the update of the industrial intelligence and the regional economic development in southwest China,and also provide a reference for deep integration of school-enterprise collaboration and the cultivation of innovative talents in electronic information fields.

The Exploration of Talent Cultivation in Software Engineering“ Internet Plus Finance”

With the rapid development of the Internet finance industry,society has put forward urgent needs for“Internet Plus finance”composite talents,and also put forward challenges to talent cultivation in colleges and universities.To cultivate the talents in the“Internet Plus finance”,the School of Information and Software Engineering of the University of Electronic Science and Technology of China(hereinafter“the School”)begins the 10 major measures,such as the construction of training programs,the construction of the curriculum system,the construction of the faculty team,and the construction of the practice base.Meanwhile,the School works together with banks,which have cooperated for a long time,to establish the talent cultivation system in the direction of“Internet Plus finance”in the software engineering major,solving the problem of interdisciplinary talent training in the field of software engineering and finance.

Research on the Ideological and Political Construction of Mathematics Foundations of Information Security

Mathematics foundations of information security is a core course in the subject of information security.In view of the current national ideological and political conference in universities,finding a way to integrate this course with ideological and political education attracts a lot of attention from the education community.This paper makes an assay of the significance of the combination of mathematics foundations of information security course and ideological and political education,and introduces the teaching practice of mathematics foundations of information security course combined with ideological and political education.Through the combination of ideological and political education and curriculum content,cultivating all-round development of talents who study information security.

Multiple mode cooperation based software engineering talents training

The main problems of the traditional software talent training are that the knowledge learned is out of touch of the industry,weak ability to solve complex engineering problems and the comprehensive quality cannot meet the requirements of enterprises.Taking the course of digital image processing as an example,this paper analyzes the key steps in the training process in details,and proposes a multiple mode collaborative based software engineering talent training mechanism,which brings the key subjects of teaching materials,teachers,students,enterprises,subjects into a unified training mechanism,so as to provide a new ideas for software talent teaching.

School-Enterprise Cooperation in Excellent Engineer Education and Training Program at UESTC

School of Information and Software Engineering at University of Electronic Science and Technology of China(abbreviated hereafter as "SISE") joined Excellent Engineer Education and Training Program launched by Ministry of Education of China in 2011. This paper discussed nine models of school-enterprise cooperation practiced at SISE since 2011. The school-enterprise cooperation model effectively broadens the students' horizons and improves the students' practical ability and has been recognized by academic circles.

Improved Prediction and Understanding of Glass-Forming Ability Based on Random Forest Algorithm

As an ideal material,bulk metallic glass(MG)has a wide range of applications because of its unique properties such as structural,functional and biomedical materials.However,it is difficult to predict the glass-forming ability(GFA)even given the criteria in theory and this problem greatly limits the application of bulk MG in industrial field.In this work,the proposed model uses the random forest classification method which is one of machine learning methods to solve the GFA prediction for binary metallic alloys.Compared with the previous SVM algorithm models of all features combinations,this new model is successfully constructed based on the random forest classification method with a new combination of features and it obtains better prediction results.Simultaneously,it further shows the degree of feature parameters influence on GFA.Finally,a normalized evaluation indicator of binary alloy for machine learning model performance is put forward for the first time.The result shows that the application of machine learning in MGs is valuable.

Intention Estimation of Adversarial Spatial Target Based on Fuzzy Inference

Estimating the intention of space objects plays an important role in air-craft design,aviation safety,military and otherfields,and is an important refer-ence basis for air situation analysis and command decision-making.This paper studies an intention estimation method based on fuzzy theory,combining prob-ability to calculate the intention between two objects.This method takes a space object as the origin of coordinates,observes the target’s distance,speed,relative heading angle,altitude difference,steering trend and etc.,then introduces the spe-cific calculation methods of these parameters.Through calculation,values are input into the fuzzy inference model,andfinally the action intention of the target is obtained through the fuzzy rule table and historical weighted probability.Ver-ified by simulation experiment,the target intention inferred by this method is roughly the same as the actual behavior of the target,which proves that the meth-od for identifying the target intention is effective.

Electronic Auction Scheme Based on Smart Contract and IPFS

Sealed-bid auctions are a vital transaction tool in the e-commerce field.Traditional centralized auction schemes typically result in severe threats to data integrity,information transparency,and traceability owing to their excessive reliance on third parties,and blockchain-based auction schemes generally suffer from high storage costs and are deficient in functional and architectural design.To solve these problems,this study presents a sealed-bid auction scheme that removes the third-party based on an Ethereum smart contract,ensuring data integrity,openness,and transparency in the execution process.The commitment mechanism and distributed storage system help to significantly reduce the user’s storage cost and protect the privacy of user bids.For the functional design,this study introduces a fulltext-retrieval and dispute-processing module for commodities,which reduces the defects existing in the functional module design of existing auction systems.Furthermore,a prototype auction system on the Ethereum test chain is built to validate the proposed scheme.Experiments show that compared with traditional storage methods,indirect storage based on a distributed storage system of texts and images can reduce the storage cost by at least 50%while ensuring data integrity.Finally,the gas cost at each stage of the auction scheme and the time required for the full-text retrieval of products are recorded to evaluate the scheme performance and analyze the test results.

Device-Free Through-the-Wall Activity Recognition Using Bi-Directional Long Short-Term Memory and WiFi Channel State Information

Activity recognition plays a key role in health management and security.Traditional approaches are based on vision or wearables,which only work under the line of sight(LOS)or require the targets to carry dedicated devices.As human bodies and their movements have influences on WiFi propagation,this paper proposes the recognition of human activities by analyzing the channel state information(CSI)from the WiFi physical layer.The method requires only the commodity:WiFi transmitters and receivers that can operate through a wall,under LOS and non-line of sight(NLOS),while the targets are not required to carry dedicated devices.After collecting CSI,the discrete wavelet transform is applied to reduce the noise,followed by outlier detection based on the local outlier factor to extract the activity segment.Activity recognition is fulfilled by using the bi-directional long short-term memory that takes the sequential features into consideration.Experiments in through-the-wall environments achieve recognition accuracy>95%for six common activities,such as standing up,squatting down,walking,running,jumping,and falling,outperforming existing work in this field.

The Controllability of Quantum Correlation under Geometry and Entropy Discords

Quantum correlation plays a critical role in the maintenance of quantum information processing and nanometer device design.In the past two decades,several quantitative methods had been proposed to study the quantum correlation of certain open quantum systems,including the geometry and entropy style discord methods.However,there are differences among these quantification methods,which promote a deep understanding of the quantum correlation.In this paper,a novel time-dependent three environmental open system model is established to study the quantum correlation.This system model interacts with two independent spin-environments(two spin-environments are connected to the other spin-environment)respectively.We have calculated and compared the changing properties of the quantum correlation under three kinds of geometry and two entropy discords,especially for the freezing phenomenon.At the same time,some original and novel changing behaviors of the quantum correlation under different timedependent parameters are studied,which is helpful to achieve the optimal revival of the quantum discord and the similar serrated form of the freezing phenomenon.Finally,it shows the controllability of the freezing correlation and the robustness of these methods by adjusting time-dependent parameters.This work provides a new way to control the quantum correlation and design nanospintronic devices.

Teaching Reform of Mathematics Foundations of Information Security with Algorithm as the Core

In view of the problems existing in the teaching of Mathematics Foundations of Information Security,such as emphasizing theory but neglecting practice,combined with the concept of engineering education certification and emerging engineering education teaching reform,this paper combs the knowledge points and learning context of Mathematics Foundations of Information Security,puts forward a new teaching mode of Mathematics Foundations of Information Security with algorithm as the core,and gives the teaching content,organization form and assessment method.Thus,it improves the students’learning interest and practical ability,and improves the achievement of graduation requirements.

How to Integrate Abstract Algebra and Number Theory in the Teaching of Public Key Cryptography Elegantly

Different from traditional symmetric cryptography, public key cryptography allows each user to own a pair of public/private key pair. Given the public key of one user and the data to be encrypted, a ciphertext can be generated such that only the intended user is able to recover the data using his/her private key associated with public key involved in the encryption process. To really understand the philosophy behind the public key cryptography is not an easy task and sometimes it seems somewhat difficult, if not impossible, for the beginners without the knowledge of the abstract algebra and number theory. In this paper, we introduce briefly the basic definition of public key cryptography as well as the corresponding mathematical hard problems. Besides, we explain why the mathematical backgrounds, especially abstract algebra and number theory, matter in the study of public key cryptography.