Ebook: Proceedings of CECNet 2022

After more than a decade of existence, the Conference on Electronics, Communications and Networks (CECNet) series has become established as a mature event. CECNet is held annually, and covers many interrelated groups of topics such as electronics technology, communication engineering and technology, wireless communications engineering and technology and computer engineering and technology.

Electronics, communication and networks coexist, and it is not possible to conceive of the current society without them. The next decade will probably see the consolidation of 6G-based technology, accompanied by many compatible devices. On a different topic, data centers are on the rise, and fiber-optic is now the most advanced technology, with many applications such as fiber to the home, fiber to the desktop, fiber for business and fiber to the node. As regards speed, we may soon have 100 Gb/s passive optical networks operating at a symmetrical mode. Going beyond this, 400 Gb/s may be achieved for long hauls with compact optical transceivers, and rates of 800 Gb/s for short hauls are possible. The trend is to have a hybrid coax-fiber material to take advantage of both technologies. TDSL (Terabit DSL) is not a new concept, and performance of about 2 Tb/s at a distance of 200 meters is also possible. Circular data centers are the future trend, with the idea that the heat generated by a data center could be used in, for example, a greenhouse.

This book contains the papers accepted and presented at the 12th International Conference on Electronics, Communications and Networks (CECNet 2022), held from 4–7 November 2022 as a virtual event with no face-to-face participation in Xiamen, China. All papers were carefully reviewed by program committee members, who took into consideration the breadth and depth of the research topic that fall within the scope of CECNet. CECNet 2022 was also a reference conference, and attracted many remarkable keynote speakers, such as Prof. Lyudmila Mihaylova, Department of Automatic Control and Systems Engineering, University of Sheffield, United Kingdom; Prof. Xiangjie Kong, College of Computer Science & Technology, Zhejiang University of Technology, China; and Prof. Victor Chang, Aston Business School, Aston University, United Kingdom.

CECNet 2022 received 313 submissions, and after a lively discussion stage, the committee decided to accept 79 papers, which represents an acceptance rate of about 25%.

I would like to thank all the keynote speakers and authors for their efforts in preparing a contribution for this leading international conference. Moreover, I am very grateful to all those, especially the program committee members and reviewers, who devoted their time to evaluate the papers. It is a great honour to continue with the publication of these proceedings in the prestigious series Frontiers in Artificial Intelligence and Applications (FAIA) from IOS Press.

Finally, although I hope you enjoy your virtual visit to Xiamen, I also hope we will be able to attend the conference face-to-face in the very near future.

October 2022

Antonio J. Tallón-Ballesteros

Huelva city (Spain)

University of Huelva (Spain)

Hidden Vector Encryption (HVE) is a new kind of attribute-based encryption in which a vector is hidden in the ciphertext or linked with the secret key. In ESORICS 2014, Phuong et al. proposed an HVE scheme with constant-size ciphertext which is constructed in the prime order setting. In this paper, we show that Phuong et al.’s scheme is not vector-hiding due to public parameters in their scheme leak some information about vectors. Furthermore, an improved HVE scheme is proposed in the prime order setting and its security is proven in the security model. Comparison shows our scheme has more efficient in decryption than current other HVE schemes.

In this paper, we model the cellular network consisting of aerial base stations (ABSs) which follow homogeneous Poisson Point Process (PPP) and an independent collection of random users is considered. We assume that each user communicates with the closest ABS. In particular, we deal the interference signals with Laplace transform. As a result, we can obtain a tractable expression of the coverage probability. We have found that there is a maximum coverage probability which can be reached by an optimal ABS density and with low signal-to-noise ratio (SNR), the optimal ABS density gets larger when path loss exponent (PLE) increases. Simulations under high or low SNR condition have shown that the influence of PLE on coverage probability is quite different in spite of changing signal-to-interference-plus-noise ratio (SINR) threshold or ABS density.

The access of massive terminal devices at the perception layer poses security threat to the power Internet of Things (IOT) of the State Grid Corporation. Due to lack of computing resources, the IOT perception layer terminal devices cannot embed the security chips. The lightweight authentication technologies are urgently needed to be developed to protect the authentication security of the IOT perception layer terminal devices. This paper proposes a lightweight identity authentication system based on the SM2 co-signature algorithm, which can be applied to the identity authentication of the IOT perception layer terminal devices. This system is implemented in software and characterized by low cost and strong compatibility, and most importantly, it can strengthen the identity authentication security of the power IOT which security protection capability will be improved consequently.

In this paper, we will design a set of standard communication protocols that can be used in different electric energy metering device environments by analyzing the communication protocols of the most used electric energy metering devices in the context of IoT smart laboratory construction, so that the electric energy metering devices can automatically detect the inspected equipment. It achieves the purpose of promoting the construction of a smart laboratory, enhancing the management of electric energy metering devices, and improving the efficiency of metering activities. It provides strong support for forming an automated, intelligent and industrialized testing system.

In order to ensure the security of data communication in the electricity consumption information collection system of power users, this paper proposes a security method for data exchange between the master station and the terminal data based on the key agreement mechanism. The method is mainly completed in three steps: first, the master station and the terminal A session channel is established between the two, and session key negotiation is performed to obtain the session key used in the subsequent data exchange process; then, the session key in the session key negotiation is used to perform the authentication operation of the master station to the terminal; finally, the terminal to the master station is used. station for authentication. At the same time, security policies such as encryption and signature are adopted in the process of data interaction. Through these three steps, the mutual authentication between the master station and the terminal is completed, a secure communication channel between the master station and the terminal is established, and the secure data exchange between the master station and the terminal is finally realized.

The development of big data and artificial intelligence has improved the intelligence and informatization of scientific planting. A scientific cultivation analysis method based on knowledge graphs is proposed in this paper. First, the logical representation and the ontological representation are combined to realize the access of static cultivation information and dynamic cultivation experience, as well as their representation with graphs. Second, according to the characteristics of plant cultivation information, knowledge extraction is realized via relational computing. A relationship determination method based on the first derivative and a multi-level classification retrieval method based on a tree structure are proposed to extract cultivation experience from the experimental data. Then, multimedia technology is embedded in the RDF framework and implemented, which further realizes the display of decision suggestions after scientific cultivation information analysis. Finally, taking perennial flowers as an example, the realization and application performance of cultivation knowledge graphs are demonstrated.

With the development of the supply-side reform of road transportation in China and the rapid development of public transportation, the pressure of public security management is also increasing. According to the statistics of public transport safety accidents, the number of public transport accidents and deaths accounts for about 1% of the total number of relevant road traffic accidents in China, among which 93% of bus accidents are caused by drivers’ traffic violations. And, therefore, in order to predict the dangerous driving behavior of public transportation driver, this project combines the driver factors and environmental factors such as weather, road conditions, using the gradient promotion tree algorithm to forecast the risk in the process of public transportation to drive, to achieve the advance management and intervention of public traffic safety, to avoid major public traffic safety accidents, It provides ideas and deployment direction for public security traffic management.

In this paper, an uncertain state filling method is proposed, which can not only effectively reduce the scan shifting power consumption, but also reduce the test time simultaneously for scan test. This method is based on the threshold algorithm of uncertain state filling, which can both reduce weighted transitions metric (WTM) and improve compression efficiency for test vectors. Experiments with ISCAS’89 benchmark circuits show that the proposed algorithm can make a good tradeoff between power consumption and compression efficiency.

Traffic data occupies an important position in intelligent transportation systems (ITS). However, the collected traffic data is often incomplete. We propose a generative adversarial network (GAN) model based on multi-perspective spatiotemporal learning (MST-GAN) to repair data. To achieve the effect of interpolating data from three perspectives: temporal, spatial, and spatiotemporal, we utilize chained generator with independent parameters to progressively refine the learning of temporal and spatial features. In addition, we achieve high-level fusion of multi-perspective features by adversarial between multiple generators and one discriminator. We conduct experiments on two real datasets, showing that the imputation effect of the MST-GAN model is better than other baseline models under different missing patterns. For example, the root mean square error (RMSE) is less than 7.5% and the mean absolute error (MAE) is less than 5% in the random missing scenario, which is much lower than the best performance error of other models.

With the rapid development of the Internet, the demand for high-quality nuclear data services continues to grow. As the main carrier of network traffic, data centers face huge challenges in network resource management. In order to optimize the performance indicators of network flow (such as delay, jitter and packet loss rate, etc.), it is necessary to study the core data evaluation system and modeling. Through the theoretical introduction of nuclear data evaluation system and modeling and ABC-BP hybrid algorithm, this paper analyzes from three aspects: comprehensive data evaluation, nuclear data network modeling, and data evaluation system construction. Based on the relevant theoretical research of ABC-BP hybrid algorithm Based on the analysis of the feasibility of the nuclear data evaluation system and modeling research based on the algorithm theory, the existing nuclear data evaluation system and modeling system in the relevant literature are deeply discussed and studied. Scientific and operable evaluation index system to conduct nuclear data evaluation system and modeling for the ecological development of my country’s government open data, so that it can truly understand its own system status. According to the existing problems of the system, reasonably coordinate and configure the relationship between the elements in the system, and finally realize the balanced, stable and efficient operation of the system.The final experimental results show that when the data fusion coefficients are 49.7, 31.6, 56.3, 73.9 and 60.5, the corresponding data compatibility degrees are 76.9%, 80.2%, 78.4%, 77.1% and 79.3%, respectively. And the compatibility of the nuclear data evaluation system is always maintained at the level of about 78%, indicating that the nuclear data evaluation system based on the ABC-BP hybrid algorithm has good feasibility in terms of data compatibility.

In this paper, aiming at the complex background and overlapping characteristics in X-ray images, we propose an unique spatial attention mechanism based on the feedback of high-level semantic feature to guide low-level semantic features, named Feedback Guidance Mechanism (FGM). In addition, in view of the high probability of miss of small prohibited items, a feature aggregation method based on the fusion of high and low-level features and dilated convolution is proposed, named Feature Aggregation Module (FAM). Then, we combine FGM and FAM into a lightweight model SSD and get a new Prohibited Items Detector (PIXDet). Our experiments indicate that PIXDet is more lightweight, but it can achieve 90.36% mAP on PIXray dataset, exceeding SSD by 1.0% mAP, outperforming some state-of-the-art methods, implying its potential applications in prohibited items detection field.

Bloom’s taxonomy of educational goals divides the educational goals in the cognitive field into different levels from low-level to high-level, and the highest level is innovation. Our country is stepping into the era of knowledge economy step by step, cultivating students’ innovative thinking is the need of The Times development, the key to maintain the prosperity of national culture, and the development of national science and technology needs the promotion of education innovation. But the vast majority of middle school students lack of thinking in the learning process in our country, the lack of space imagination ability and logical thinking ability in the process of teaching, and teachers failing to cultivate students’ various mathematical ability, based on this the paper in bloom education target on the basis of how to improve the students’ mathematics creative thinking put forward the following Suggestions: Teachers should attach importance to preview before class and introduction, and students’ learning methods should be reformed: skillfully use “flipped classroom”, “group cooperative learning”, attach importance to the cultivation of students’ observation and analysis ability, attach importance to classroom summary and form knowledge system. And under the guidance of the classification of educational objectives, the teaching design of the sum of the first n terms of geometric progression is carried out.

Due to the exposed nature of wireless links, the communication of wireless networks is vulnerable to jammers. And because the jammer models are usually unknown to communication users, particularly in military confrontation applications, how to ensure maintain communication under different jamming is an active research topic. In this paper, we take the anti-jamming task of cognitive radio as a Markov decision process and propose an anti-jamming method based on Q-learning. The method aim to learn an efficient policy for users to maximize the total channel transmission capacity in different typical jamming scenarios. The simulation results indicate that compared with the traditional anti-jamming methods, the anti-jamming method based on Q-learning can obtain better performance, and more effective against several kinds of typical jamming models.

Detention places, as an important part of police’s safe of law enforcement, are receiving more and more research attention. We are aiming to apply advanced information technology to the field of detention places and build an early warning prediction model that can improve the security of detention places. This research can accumulate some experience for follow-up technological development in the field of detention places’ supervision.

In this design, dimension of the proposed antenna is 20 × 25 × 1.6 mm³ with FR4 substrate having circular patch fed with co-planar waveguide (CPW) that operates at numerous resonance frequencies between 5 and 10 GHz. The proposed antenna can be used well for low range communication transceivers in the C and X bands, according to simulation results. The optimal parameters for UWB antenna are the fractional bandwidth, which should be greater than 85%, and VSWR, which is another parameter. For the best and most efficient technique of using printed monopole antenna, the range of Ultra wideband (UWB) bandwidth should be lower than 2. Simulate data suggest that the proposed antenna has outstanding impedance matching capabilities, achieving a peak gain of 8 dBi. Results indicate that the ground plane’s dimensions of 15.9 mm and 11.4 mm are the most suitable for UWB due to its return loss of -41.86 dB, fractional bandwidth of about 89%, and Voltage standing wave ratio(VSWR) of less than 2 within the frequency spectrum. This modified prototype antenna has a decent, omnidirectional radiation pattern.

For the past years, the Internet of Things (IoT) supported by 5G technology, has been expanding rapidly across a wide range of services, enabling inter-object connectivity for the automotive industry, consumer electronics, transportation, logistics sectors, and manufacturing. With the increasing ubiquitous usage of various small-sized sensors, manufacturing cost of each element taken remains a critical aspect. Relatively low price of individual elements is the key for enabling tightly connected environment, but may severely affect RF chains quality as well as overall performance. With 5G expansion to the sub-THz bands, power amplifier nonlinearity may significantly limit system performance even in high- grade devices, due to power amplifier design limitations. Multiple studies were done to mitigate nonlinearity impact, both at the transmitter (TX) and receiver (RX) sides. Many solutions propose for evaluation and further compensation of the PA nonlinearity effects, via decision-directed feedback, training or even statistical processing of the received signal. However, with knowledge of the PA nonlinearity function at the receiver side, the processing may be simplified by the application of the reverse function to the equivalent signal in the time domain. In this paper we propose a method for PA nonlinear distortion compensation at the RX side, which can be adjusted for several signal waveforms adopted in 5G NR (New Radio) standard, such as CP-OFDM, DFT-S-OFDM, and others. The simulation results presented demonstrate performance improvement both for the sub-THz PA models and models for the 30–70 GHz band.

In recent years, the public security department has insisted on technology to promote the high-quality development of public security work in the new era. It not only builds a three-dimensional patrol and defence system, but improve the level of patrol, defence and control management vigorously. At present, an intelligence-aided patrol system has been initially formed, and video patrols and law enforcement duty supervision have been carried out. However, the application of new technologies and the innovation of policing mechanisms in public security departments still have some problems. For example, unbalanced regional development, insufficient deepening of intelligent applications and insufficient systematization of applications, which greatly restrict the effectiveness of public security patrol and defence in practice. Based on this, our study identifies the crime hotspots in the city through EXCEL data analysis, and identifies them as patrol points. By applying the shortest route algorithm in the genetic algorithm, a precise patrol route is formed. Based on this, the precise patrol route is displayed on a map using a visualization tool and then fed back to the police terminal equipment. This project enables police patrols to be more accurate and patrol routes to be optimized. It improves the police patrol system and provides the basis for the construction of an intelligent patrol system.

Since INCOSE first proposed the Model-based System Engineering (MBSE) road map in 2007, the concept of MBSE has been well known, but the application results of MBSE in many companies have not been satisfactory. The implementation of MBSE is a considerable investment, including learning the top-level MBSE processes and the three pillars of MBSE, including the language, tool and methodology. The lack of understanding of MBSE’s advantages makes it difficult for many complex equipment development enterprises to invest enormous time and economic costs to implement MBSE. In this paper, the advantages of MBSE are discussed in three developing trends, including written ideograms, human-machine communication language and human thinking. This is the first time to discuss the progressiveness of MBSE from these different views, which can help enterprises dispel the concerns about MBSE implementation and strengthen their confidence in MBSE’s full implementation.

Model-based System Engineering (MBSE) is proved an effective way to develop complex systems, and lots of MBSE methods/tools have been developed in recent years. Lack of deep analysis of mainstream MBSE methods/tools and guidance in performing MBSE under the general SE process leads to a rough patch for design staff to transform from document-based system engineering to model-based system engineering. In this paper, step-by-step modelling practice following the official tutorials is performed to analyze MagicGrid (MagicDraw), ARCADIA (Capella), and HarmonySE (Rhapsody). This is the first time to analyse the mainstream MBSE methodolgies from the uniform INCOSE SE practice view and compare the method and modeling tool differences. These will provide a detailed guide for the engineers to transform from document-based system engineering to model-based system engineering.

Quantitative inversion techniques have been widely used in many fields where the electric or magnetic fields are sampled in a wide range of viewing angles. In this paper, the quantitative inversion imaging scheme has been proposed for remote sensing radar systems with multiview-multistatic sensing configuration. The cross correlated contrast source inversion method is used in witch the cross-correlated term has been used as a regularization technique for, to some extent, overcoming the ill-posedness. Preliminary simulation results demonstrate that quantitative inversion radar imaging shows physical resolving ability for remote sensing imaging. To the best of our knowledge, it is verified for the first time that physical imaging is feasible with limited range of viewing angles (less than 65° in this paper). Therefore, we remark that in remote sensing applications, the quantitative inversion radar imaging scheme shows potential of identifying radar targets not only with finer geometric resolutions but also in an additional physical dimension of the electromagnetic characteristics. Extension of this inversion scheme to the multibistatic sensing configuration will be more impressive in the field of remote sensing radar imaging.

A lowpass-bandpass (LP-BP) diplexer with one lowpass channel (LPC) and one bandpass channel (BPC) is presented. The lumped-element dual-resonance resonator as common resonator is proposed to connect inductors, capacitors and LC resonator to constitute the desired channels. The LPC design is combined with parameters optimization and the lowpass transformation method, and the BPC design can be developed using the classical design theory of coupled-resonator filter. As an example, a 0.9 / 1.8 GHz LP-BP diplexer is designed and fabricated, which exhibits high return loss (RL), low insertion loss (IL), wide bandwidth (BW), high isolation and extremely compact size.

Based on plaintext information, a dynamic chaotic color image encryption algorithm is proposed as a solution for the security problem in image data transmission, Comparatively, the existing one has the characteristics of high key acquisition complexity and low encryption speed. Firstly, normalize the RGB components of the images so as to obtain the dynamic key associated with the plaintext, which encrypts images with any shape by rearranging and combining pixels from the original image. Secondly, the parameter offset key is introduced as the initial parameter of the logistic map to generate a high-precision chaotic encryption sequence. The chaotic value sequence is stored for disordered pixels according to the image size, and enlarged and rounded to enhance the pixel value diffusion of the original image. Finally, RGB components are fully fused and uniformly distributed to form a completely encrypted image. According to the experimental results and security analysis, the proposed algorithm is effective against differential attacks, with low complexity, high efficiency, and faster encryption speed.

Digital transformation will promote the rapid progress of power digital space construction led by power data. Through the use of new digital information technology, we will give full play to the function of data integration and effectively support the construction of new power system. Data interconnection is the key link to release the value of data, but at present, there are still many urgent problems to be solved in the power digital spatial data sharing, such as the mismatch between data demand and data supply, weak security guarantee and so on. In order to study the security protection of power digital spatial information data sharing, according to the concept of privacy computing, a power digital spatial data security sharing model system based on privacy computing is designed. This model system has strong research and practical significance for realizing the secure circulation and sharing of new power system data.

Chicken and egg food traceability system based on NFC and QR code technology was designed. The traceability system registers and uploads the information of raised chickens through the chicken foot ring embedded with NFC tag. The system generates egg QR code according to the registered information and prints it on the eggs corresponding to the raised chickens. It is used for consumer users to scan and query the relevant information of the eggs and the raised chickens, including the breeding address, breeder and breeding record of the raised chickens. The system is designed based on the classic three-layer mode of the Internet of things and the B / S architecture. The system mainly realizes the traceability of chickens through NFC tags and eggs through QR codes. It has high stability and great application and promotion value.