Number Of Bytes Research Articles

Three Rounds Cryptography to Protect Secret Message

A simple three rounds method of message cryptography will be introduced, the message will be encrypted-decrypted by apply XORing operation of the message with the secret KEY1 in the first round, in the second round the message will be shuffled using the secret key KEY2, while in the third round the message binary matrix will be rotated left to a number of selected digits. The introduced method will be very secure it will use a secret kept digital color image as an image_key, this image will be used to generate KEY1 and KEY2. KEY1 will be extracted from the image from a selected position, while KEY2 will be an indices key obtained by sorting a number of bytes extracted from the image from another position determined by the user. In addition to the image_key the method will use the values of POS1, POS2, and NORLD to determine the starting position of key1, the starting position of key2 and the number of rotate left digits. The produced decrypted message will be very sensitive to the selected image_key, POS1, POS2 and NORTD. The encryption function will be simplified and it will be implemented using three simple tasks: XORing, shuffling and rotating left, while the decryption function will be implemented by applying rotate left, shuffling back and XORing operations. The proposed method will be implemented and tested using various messages, the results will be studied and analyzed to prove the achievements provided by the method in: quality, speed, security and sensitivity.

Decentralize transaction records of digital payment gateway using Ethereum Blockchain and Interplanetary File System

This research proposes a system to store transaction records from a payment gateway based on digital payments by utilizing blockchain technology and Interplanetary File System (IPFS) as distributed storage. In digital payments, the possibility of online fraud or theft of customer data is a problem that needs to be solved. Although the solution is to use a Payment Gateway with security standards to prevent these problems, the system is still centralized and vulnerable to the possibility of system failure or data changes by irresponsible people. Blockchain furnishes a secure and unalterable record for documenting payment transactions. Conversely, IPFS presents a decentralized and immune-to-censorship approach for storing and accessing data. The usage of these technologies guarantees the secure storage of payment transaction data and related documents (such as invoices and receipts) while effectively thwarting data manipulation or censorship attempts. Therefore, this research aims to build a blockchain technology system to increase security and maintain the integrity of the data generated from the Payment Gateway. This research using distributed data storage using IPFS to save transaction from the payment gateway data. Based on the evaluation and security analysis results, implementing a blockchain technology system to store transaction records from digital-based payment gateways can improve data security and integrity. In the gas fee increase analysis, the gas fee will increase according to the total number of bytes generated when the transaction is made, where each byte will cost 12 gwei to pay the gas fee.

Firmware Updates over the Air via LoRa: Unicast and Broadcast Combination for Boosting Update Speed.

The capacity to update firmware is a vital component in the lifecycle of Internet of Things (IoT) devices, even those with restricted hardware resources. This paper explores the best way to wirelessly (Over The Air, OTA) update low-end IoT nodes with difficult access, combining the use of unicast and broadcast communications. The devices under consideration correspond to a recent industrial IoT project that focuses on the installation of intelligent lighting systems within ATEX (potentially explosive atmospheres) zones, connected via LoRa to a gateway. As energy consumption is not limited in this use case, the main figure of merit is the total time required for updating a project. Therefore, the objective is to deliver all the fragments of the firmware to each and all the nodes in a safe way, in the least amount of time. Three different methods, combining unicast and broadcast transmissions in different ways, are explored analytically, with the aim of obtaining the expected update time. The methods are also tested via extensive simulations, modifying different parameters such as the size of the scenario, the number of bytes of each firmware chunk, the number of nodes, and the number of initial broadcast rounds. The simulations show that the update time of a project can be significant, considering the limitations posed by regulations, in terms of the percentage of airtime consumption. However, significant time reductions can be achieved by using the proper method: in some cases, when the number of nodes is high, the update time can be reduced by two orders of magnitude if the correct method is chosen. Moreover, one of the proposed methods is implemented using actual hardware. This real implementation is used to perform firmware update experiments in a lab environment. Overall, the article illustrates the advantage of broadcast approaches in this kind of technology, in which the transmission rate is constant despite the distance between the gateway and the node. However, the advantage of these broadcast methods with respect to the unicast one could be mitigated if the nodes do not run exactly the same firmware version, since the control of the broadcast update would be more difficult and the total update time would increase.

Performance analysis of React v. 18.1.0 and Angular v. 11.0.2 development frameworks

This paper presents the results of the comparative analysis of the two JavaScript frameworks. The research was carried out using test applications with the same functionalities, implemented in both environments. The number of bytes occupied by both projects, the number of lines of code, the average RAM consumption and the time efficiency were used as criteria for comparison. Automatic load tests and technical analysis of both environments were performed. The results showed that React is able to better handle a large amount of data (around 100 000 records), while for small data sets oscillating around 1000 records, no significant differences in both application performance were demonstrated. For a medium number of records (10000), React proved to be more efficient.

CYBERSECURITY: RESEARCH ON METHODS FOR DETECTING DDOS ATTACKS

This article describes the problem of DDoS attacks, analyzing their nature and consequences. The paper covers common DDoS attack types, such as SYN flood, ICMP flood, UDP flood. Existing methods for detecting attacks from literature are reviewed, including machine learning approaches, including artificial neural networks, support vector machines and decision trees. The paper introduces a decision tree-based machine learning model for the detection of DDoS attacks. The model is trained and tested on a publicly available dataset. The dataset consists of 1,04,345 rows of data, where every row includes 23 features, such as source IP, destination IP, port number, number of bytes transferred from the switch port, etc. A similar set of characteristics can be obtained on a real network hardware using simple calculations, which makes it possible to approximate the model evaluation to real operating conditions. SYN flood, ICMP flood and UDP flood attack types are present in the data, as well as legitimate traffic. To avoid overfitting, only some columns were used, and columns such as IP addresses were discarded. The field “label” in each row of the dataset contains either 0 or 1 where 0 corresponds to legitimate traffic and 1 to malicious one. The problem of DDoS attack detection is therefore formally reduced to the task of binary classification of each row from the dataset. The constructed model achieves an average classification accuracy of 0.94 with a standard deviation at the level of 0.06 in detecting the above mentioned types of attacks. To objectively assess the effectiveness of the model and avoid distortion of the results, stratified 5-fold cross-validation was used. The developed model can be applied in the real world network hardware to filter malicious packets or as a tool for warning the administrator about an attack. This research advances cybersecurity by enhancing DDoS attack detection.

Video File Allocation for Wear-Leveling in Distributed Storage Systems With Heterogeneous Solid-State-Disks (SSDs)

With the advent of new large-capacity solid-state disks (SSDs) such as quad-level-cells (QLC), SSD arrays can be effectively used in video storage systems that require large-capacity storage space. Typically, SSD manufacturers specify a drive-writes-per-day (DWPD) metric, which is the ratio of bytes written per day to the total capacity in bytes, to ensure an SSD’s specified lifetime; it is important to limit the number of write operations by considering the DWPD for each SSD. We propose a new video file allocation technique to effectively manage the heterogeneous DWPD characteristics of SSDs in distributed storage systems. To express the degree of wear-leveling for heterogeneous SSDs, we first introduce the concept of ADWD, which is the actual number of bytes written per day compared to DWPD. We then propose two algorithms for file placement and migration. The file placement algorithm places files greedily based on the bandwidth-to-space ratio (BSR) of each file and SSD to balance the bandwidth usage and storage of the SSD. The file migration algorithm moves files from overloaded to underloaded SSDs to meet bandwidth limit requirements while minimizing the overall ADWD as a result of migration, and then migrates additional popular files to improve SSD bandwidth utilization. To use these algorithms in actual distributed file systems, we implemented a suite of tools for file placement and migration in the Hadoop distributed file system (HDFS). Experimental results show that the proposed algorithm reduces the mean of ADWD by 35.44% and its standard deviation by 69.78% compared to the benchmark methods on average.

The strategic analysis and operation of the multiservice model used for synchronous transmission in communication networks

The core idea of asynchronous transfer mode (ATM) technology was revealed a long time ago. The main technology under development at the time was time-division multiplexing (TDM) technology, which consisted of synchronous switching based on the sequence number of bytes in the integrated frame. The main disadvantage of TDM technology, also known as synchronous transport module (STM) synchronous transmission technology, is the inability to reallocate the bandwidth of the integrated channel between subchannels. During those periods when no user data is sent on the subchannel, the aggregated channel still sends the bytes of this subchannel filled with zeros. Efforts to load sub channels’ idle periods necessitate the introduction of a header for each subchannel’s data. In intermediate statistical time-division multiplexing (STDM) technology, which allows idle periods to be filled by transmitting bursts of traffic from other sub channels, headers that actually have a subchannel number are introduced. In this paper, the strategic analysis and operation of technologies used in multiservice networks were discussed. Simultaneously, the structure of data sets is drawn into sets resembling computer networks. The fact that each packet has an address allows it to be transmitted asynchronously since its location relative to data on other subchannels is not its address. Asynchronous packets from one subchannel are inserted into the free time slots of another subchannel, but they are not mixed with the data of this subchannel because they have their own address.

IoT-Based Medical Image Monitoring System Using HL7 in a Hospital Database.

In recent years, the healthcare system, along with the technology that surrounds it, has become a sector in much need of development. It has already improved in a wide range of areas thanks to significant and continuous research into the practical implications of biomedical and telemedicine studies. To ensure the continuing technological improvement of hospitals, physicians now also must properly maintain and manage large volumes of patient data. Transferring large amounts of data such as images to IoT servers based on machine-to-machine communication is difficult and time consuming over MQTT and MLLP protocols, and since IoT brokers only handle a limited number of bytes of data, such protocols can only transfer patient information and other text data. It is more difficult to handle the monitoring of ultrasound, MRI, or CT image data via IoT. To address this problem, this study proposes a model in which the system displays images as well as patient data on an IoT dashboard. A Raspberry Pi processes HL7 messages received from medical devices like an ultrasound machine (ULSM) and extracts only the image data for transfer to an FTP server. The Raspberry Pi 3 (RSPI3) forwards the patient information along with a unique encrypted image data link from the FTP server to the IoT server. We have implemented an authentic and NS3-based simulation environment to monitor real-time ultrasound image data on the IoT server and have analyzed the system performance, which has been impressive. This method will enrich the telemedicine facilities both for patients and physicians by assisting with overall monitoring of data.

(Invited) Progressive Involvement of Thin Film Technologies in Connected Objects to Meet New Societal Challenges

This presentation is part of a context of galloping evolution of digitalization of all societal areas. These concern the administrative and financial management of economic activities, the management of the production of all kinds of objects and systems in an industry 4.0 vision, or the control of the functioning of communication, transport, health, energy or security equipment, mainly.This invasion of digital systems and communication may appear as a progress in many societal applications, but this unprecedented development creates new limitations that must be quickly overcome. If from the users' point of view, the implemented technologies appear more and more simple thanks to their software, ergonomic and user-friendly aspects, the physical support of digital objects constitutes the foundation of all these sophisticated tools. It can be noted that the great majority of user-friendly devices in direct link with the users employ flat panel displays and many other microsystems. Any evolution or improvement of these “Physical Cyber Systems” tools is based on the innovation of microelectronic circuits and systems whether they are integrated, large area or hybrid.Limitations appear in different forms, whether they are of a scientific, technical and technological origin, or also of a human origin, particularly with regard to the nature and the pool of skills, know-how, and innovation capabilities.This talk highlights the future challenges related to the exponential development of connected objects, sensors, the Internet of Things and the exploitation of transmitted and stored data. Indeed, globally, the total number of sensors and actuators grows by a factor of 2 in less than 2 years, the number of connected objects by a factor of 2 every 4 years, and the number of bytes transferred annually by a factor of 2 every 2 years, having reached the Zettabytes in 2018 and expected to reach the Yottabytes in 2030 (1024). Knowing that in a complete chain of data transfer about 50% of the equivalent consumption is spent by data centers, 30% by transmissions at all levels and 20% by industrial, professional or individual users, the effective power consumption is also growing exponentially, in practice by a factor of 2 every 4 years, despite the current permanent improvement of microelectronic technologies. In 2030, the world electricity consumption due to digital technologies should reach the world electricity consumption of 2018, i.e. about 27,000 TWh without any major intervention on the hardware level! It is necessary to review the entire chain of integrated functions that are physically realized on the basis of microelectronic components, circuits and systems. It is therefore the field of microelectronics that will have to bring innovation to face the challenges.At the level of microelectronics, the fields of intervention will therefore be multiple. The first area concerns the elementary components, which must be even more integrated but which must above all consume less. For example, major efforts are currently being made on memories that could consume up to 1000 times less than silicon-based memories thanks to the use of thin metal and insulator films. The stacking of integrated components using thin-film processes also provides solutions for integration and low consumption. The second area aims at a more intensive use of hybrid technologies in sensors and actuators involving thin films and multidisciplinary approaches. The third area is related to the reduction of energy consumption by modifying circuit architectures, by controlling the switch-off of inactive functions (a ratio of 1000 is expected), by using new materials such as organics for displays, or by involving large-gap semiconductors for high-power devices allowing to significantly reduce their leakage currents and their on-resistances. The fourth area is more complex and concerns the reduction of the use of rare elements in technologies that very often involve very high consumption in connection with their extraction, purification and transport. Their use in very thin layers such as those transferred onto insulating substrates in SOI technologies could be a solution. The last area concerns the human factor. The level of knowledge and know-how must be increasingly high with more and more players. Currently, many companies worldwide complain about the lack of candidates for job offers and point out the jobs in shortage. The challenge in this case is transferred to the international scientific and educational community.After presenting the different challenges in this context, this talk highlights the different approaches to meet the challenges, emphasizing the potential interest of thin film technologies. It concludes with the human challenge, which is becoming a key point for the success of the digital extension at the global level.

Transformation of C Programming Language Memory Model into Object-Oriented Representation of EO Language

The paper analyzes the possibilities of transforming C programming language constructs into objects of EO programming language. The key challenge of the method is the transpilation from a system programming language into a language of a higher level of abstraction, which doesn’t allow direct manipulations with computer memory. Almost all application and domain-oriented programming languages disable such direct access to memory. Operations that need to be supported in this case include the use of dereferenced pointers, the imposition of data of different types in the same memory area, and different interpretation of the same data which is located in the same memory address space. A decision was made to create additional EO-objects that directly simulate the interaction with computer memory as in C language. These objects encapsulate unreliable data operations which use pointers. An abstract memory object was proposed for simulating the capabilities of C language to provide interaction with computer memory. The memory object is essentially an array of bytes. It is possible to write into memory and read from memory at a given index. The number of bytes read or written depends on which object is being used. The transformation of various C language constructs into EO code is considered at the level of the compilation unit. To study the variants and analyze the results a transpiler was developed that provides necessary transformations. It is implemented on the basis of Clang, which forms an abstract syntax tree. This tree is processed using LibTooling and LibASTMatchers libraries. As a result of compiling a C program, code in EO language is generated. The considered approach turns out to be appropriate for solving different problems. One of such problems is static code analysis. Such solutions make it possible to isolate low-level code fragments into separate program objects, focusing on their study and possible transformations into more reliable code.

MQTT-MFA: A Message Filter Aggregator to Support Massive IoT Traffic Over Satellite

One of the main application scenario that the upcoming 5G systems are expected to support is Internet of Things (IoT) traffic backhauling. With the exponential increase of devices, it follows the critical challenge of handling the huge data volume that they produce. Terrestrial networks may not be sufficient for that, or not always available. Satellites then come into play, and they can provide the ubiquitous coverage targeted by 5G. On the other side, aggregation can be an efficient strategy to reduce the amount of traffic, and use network resources in an efficient manner. Building on that, in this work, we consider a hybrid IoT-satellite network architecture for collecting message queuing telemetry transport (MQTT) traffic. We design an advanced filter, namely, MQTT message filter aggregator (MQTT-MFA), that performs MQTT topics aggregation in close proximity of MQTT Publishers before data are sent over the satellite link. The developed MQTT-MFA implementation leverages on MQTT bridge, and it is compliant with Mosquitto, an open-source MQTT broker. Extensive simulation results have demonstrated that MQTT-MFA requires only 10% of the TCP/IP overhead generated in a baseline architecture (where the bridge is not set up) and 1/4 number of bytes to transmit the same amount of information, when compression of the data payload is also enabled.

Machine Learning for Android Scareware Detection

With the steady rise in the use of smartphones, specifically android smartphones, there is an ongoing need to build strong Intrusion Detection Systems to protect ourselves from malicious software attacks, especially on Android smartphones. This work focuses on a sub-group of android malware, scareware. The novelty of this work lies in being able to detect the various scareware families individually using a small number of network attributes, determined by a recursive feature elimination process based on information gain. No work has yet been done on analyzing the scareware families individually. Results of this work show that the number of bytes initially sent back and forth, packet size, amount of time between flows and flow duration are the most important attributes that would be needed to classify a scareware attack. Three classifiers, Decision Tree, Naïve Bayes and OneR, were used for classification. The highest average classification accuracy (79.5%) was achieved by the Decision Tree classifier with a minimum of 44 attributes.

Implementation and Comparison of File Security Using AES, DES and RSA and Anomaly Detection in Videos Using Convolutional Auto Encoder

Security is the vital part which helps in trying to exchange huge amount of data in the form of valid data from source to destination. Nowadays technology is modifying very fast based on the view on secure information. Every individual who are interacting with social network wishes their communication to be confidential and secured from the access of the unauthenticated users over the internet. Symmetric and Asymmetric Cryptography Techniques play a vital role as the arms of security. Cryptography is the skill of properly modifying the readable plain text data into a not readable cipher form. There are many individual symmetric and asymmetric algorithms that are implemented to secure the files but have their own disadvantages. Proposed technique in this paper is to use a combination of symmetric and asymmetric encryption algorithms and compare the performance with the existing systems. The file is divided into n-parts depending on the size then each part of the file is encrypted with any of the AES, DES, and RSA algorithms. Results of this Hybrid technique provides a stronger security. The comparison is made on the basis of time taken by the proposed and existing systems in milliseconds to encrypt different numbers of bytes of text and image data.

Design and Implementation of a Lightweight and Fast Tiny Advanced Encryption Standard Algorithm

Cryptographic algorithms are gaining importance due to their relevance and importance in the areas of privacy and security experienced by the Internet of Things (IoT) devices. They improve data privacy and confidentiality by limiting who can decrypt the data to the person who has the key. Advanced encryption standard (AES) is one of the most important encryption algorithms in use. This algorithm uses 10 rounds for each encryption and decryption process and encrypts data starting with 16 bytes, which increases the time needed for encryption and decryption. In order to speed up encryption and decryption while maintaining security levels more than or equal to those offered by the AES algorithm, this paper proposes an algorithm called tiny advanced encryption standard (TAES) with two different scenarios. As the encryption process starts with 4 bytes and goes up to an unlimited number of bytes, TAES features are less complex and more flexible than those of AES and can be quickly implemented, and are characterized by high encryption of images, texts, and sounds. The proposed TAES algorithm is tested on text and images using the MATLAB software. The result is completely distorted images and text. The test results also unveil that the encryption and decryption speeds as well as the throughput of the proposed TAES is much better than those of the original AES algorithm. Moreover, a low signal-to-noise ratio (SNR) values are obtained, indicating a greater degree of image distortion as a consequence of utilizing the proposed TAES algorithm.

A Streaming Media Recompression Transmission Scheme for Agricultural Machinery Monitoring

Place a camera on the agricultural machinery, the video collected by the camera is transmitted by means of a wireless network to enable the operator to monitor the operation of the machinery and provide decisions accordingly when necessary. As video data contains large capacity, and the farmlands are distributed widely and remotely, it is difficult to ensure the stability of the transmission network. In this research, a binary recompression method was proposed to perform a secondary compression on the video sequence compressed by the encoder, which solved the problem of video transmission in dynamic network by reducing the number of bytes of data on the communication channel. The core idea is to change the distribution of the original sequence of "0" and "1" symbols in binary by designing mapping rules and compression rules through the idea of binary rearrangement, so that the same symbols can be gathered together as much as possible, thereby increasing the probability of compression. In the end, a test system was set up to verify that the recompressed transmission scheme proposed in this paper was able to effectively improve the quality of video transmission in farmlands.

Log File Data Extraction or Mining

Log records contain data generally Client Title, IP Address, Time Stamp, Get to Ask, number of Bytes Exchanged, Result Status, URL that Intimated, and Client Chairman. The log records are kept up by the internet servers. By analysing these log records gives a flawless thought to the client. The wide Web may be a solid store of web pages that gives the Net clients piles of information. With the change in the number and complexity of Websites, the degree of the net has gotten to be massively wide. Web Utilization Mining may be a division of web mining that consolidates the application of mining strategies to web server logs in coordination to expel the behaviour of clients. Log records contain basic data around the execution of a framework. This data is frequently utilized for investigating, operational profiling, finding quirks, recognizing security dangers, measuring execution,

A Standard-Based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring

The environment consists of the interaction between the physical, biotic, and anthropic means. As this interaction is dynamic, environmental characteristics tend to change naturally over time, requiring continuous monitoring. In this scenario, the internet of things (IoT), together with traditional sensor networks, allows for the monitoring of various environmental aspects such as air, water, atmospheric, and soil conditions, and sending data to different users and remote applications. This paper proposes a Standard-based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring. The platform consists of an IoT network based on the IEEE 1451 standard which has the network capable application processor (NCAP) node (coordinator) and multiple wireless transducers interface module (WTIM) nodes. A WTIM node consists of one or more transducers, a data transfer interface and a processing unit. Thus, with the developed network, it is possible to collect environmental data at different points within a city landscape, to perform analysis of the communication distance between the WTIM nodes, and monitor the number of bytes transferred according to each network node. In addition, a dynamic model of data flow is proposed where the performance of the NCAP and WTIM nodes are described through state variables, relating directly to the information exchange dynamics between the communicating nodes in the mesh network. The modeling results showed stability in the network. Such stability means that the network has capacity of preserve its flow of information, for a long period of time, without loss frames or packets due to congestion.

Obfuscated Tor Traffic Identification Based on Sliding Window

Tor is an anonymous communication network used to hide the identities of both parties in communication. Apart from those who want to browse the web anonymously using Tor for a benign purpose, criminals can use Tor for criminal activities. It is recognized that Tor is easily intercepted by the censorship mechanism, so it uses a series of obfuscation mechanisms to avoid censorship, such as Meek, Format-Transforming Encryption (FTE), and Obfs4. In order to detect Tor traffic, we collect three kinds of obfuscated Tor traffic and then use a sliding window to extract 12 features from the stream according to the five-tuple, including the packet length, packet arrival time interval, and the proportion of the number of bytes sent and received. And finally, we use XGBoost, Random Forest, and other machine learning algorithms to identify obfuscated Tor traffic and its types. Our work provides a feasible method for countering obfuscated Tor network, which can identify the three kinds of obfuscated Tor traffic and achieve about 99% precision rate and recall rate.

A hybrid method of genetic algorithm and support vector machine for DNS tunneling detection

With the expansion of the business over the internet, corporations nowadays are investing numerous amounts of money in the web applications. However, there are different threats could make the corporations vulnerable for potential attacks. One of these threats is harnessing the domain name protocol for passing harmful information, this kind of threats is known as DNS tunneling. As a result, confidential information would be exposed and violated. Several studies have investigated the machine learning in order to propose a detection approach. In their approaches, authors have used different and numerous types of features such as domain length, number of bytes, content, volume of DNS traffic, number of hostnames per domain, geographic location and domain history. Apparently, there is a vital demand to accommodate feature selection task in order to identify the best features. This paper proposes a hybrid method of genetic algorithm feature selection approach with the support vector machine classifier for the sake of identifying the best features that have the ability to optimize the detection of DNS tunneling. To evaluate the proposed method, a benchmark dataset of DNS tunneling has been used. Results showed that the proposed method has outperformed the conventional SVM by achieving 0.946 of f-measure

Network Security Technology of Intelligent Information Terminal Based on Mobile Internet of Things

In the process of implementing the Internet of Things, the object itself has identity information and identification equipment and encounters difficulties in communication security during the process of entering the network communication. Just like the Internet and wireless sensor networks, there are security issues in information transmission. Therefore, it is of great significance to study the mobile Internet of Things network security technology depression to protect the communication information in the mobile Internet of Things. This paper mainly studies the network security technology of intelligent information terminal based on mobile Internet of Things. This article will analyze and compare the mainstream encryption algorithms of the current mobile Internet and choose a safer and more secure HASH algorithm. We study the flow of key management, key generation, key distribution, verification key distribution, key update, key storage, key backup, and key validity time setting for mobile Internet of Things, using an existing identity cryptosystem. Based on encryption, the design technology of key management and authentication in this paper is improved. Compared with other methods, the storage consumption of this method on GWN is relatively medium. In the initial stage, the storage is 32 bytes, then in registration stage 1, it reaches 84 bytes, in registration stage 2, it is 82 bytes, and then, in the login authentication phase, the number of bytes rose and reached 356 bytes in authentication phase 3. Experimental results show that this protocol has certain advantages in ensuring safety performance.