Internet Information Security Research Articles

Exploration on human resource management and prediction model of data-driven information security in Internet of Things

The advent of the Internet of Things (IoT) has accelerated the pace of economic development across all sectors. However, it has also brought significant challenges to traditional human resource management, revealing an increasing number of problems and making it unable to meet the needs of contemporary enterprise management. The IoT has brought numerous conveniences to human society, but it has also led to security issues in communication networks. To ensure the security of these networks, it is necessary to integrate data-driven technologies to address this issue. In response to the current state of human resource management, this paper proposes the application of IoT technology in enterprise human resource management and combines it with radial basis function neural networks to construct a model for predicting enterprise human resource needs. The model was also experimentally analyzed. The results show that under this algorithm, the average prediction accuracy for the number of employees over five years is 90.2 %, and the average prediction accuracy for sales revenue is 93.9 %. These data indicate that the prediction accuracy of the model under this study's algorithm has significantly improved. This paper also conducted evaluation experiments on a wireless communication network security risk prediction model. The average prediction accuracy of four tests is 91.21 %, indicating that the model has high prediction accuracy. By introducing data-driven technology and IoT applications, this study provides new solutions for human resource management and communication network security, promoting technological innovation in the fields of traditional human resource management and information security management. The research not only improves the accuracy of the prediction models but also provides strong support for decision-making and risk management in related fields, demonstrating the great potential of big data and artificial intelligence technology in the future of enterprise management and security.

Visual Intrusion Detection Based On CBAM-Capsule Networks

Abstract Intrusion detection has become a research focus in internet information security, with deep learning algorithms playing a crucial role in its development. Typically, intrusion detection data are transformed into a two-dimensional matrix by segmenting, stacking and padding them with zeros for input into deep learning models. However, this method consumes computational resources and fails to consider the correlation between features. In this paper, we transform the data into images through visualization operations and propose an information entropy weighted scheme to optimize the collision element problem during the transformation process. This method enhances the correlation between pixel frame features, leading to approximately 2% improvement in accuracy of the classification model when using the generated image samples for detection in experiments. To address the issues of insensitivity to target feature locations and incomplete feature extraction in traditional neural networks, this paper introduces a new network model called CBAM-CapsNet, which combines the advantages of the lightweight Convolutional Block Attention Module and capsule networks. Experimental results on the UNSW-NB15 and IDS-2017 datasets demonstrate that the proposed model achieves accuracies of 92.94% and 99.72%, respectively. The F1 scores obtained are 91.83% and 99.56%, indicating a high level of detection.

Reliability Evaluation of Clean Energy Internet Information Security Based on Statistical Learning Methods

Reliability Evaluation of Clean Energy Internet Information Security Based on Statistical Learning Methods

A Matrix Coding-Oriented Reversible Data Hiding Scheme Using Dual Digital Images

With the development of Internet technology, information security and data protection have become particularly important. Reversible data hiding is an effective technique for data integrity and privacy protection, and secret image sharing is a distinct research field within reversible data hiding. Due to the ability of sharing secret information between two receivers and the larger embedding capacity compared to the traditional reversible data hiding scheme, dual digital images have also attracted extensive research in the past decade. In this paper, we propose a reversible data hiding scheme based on matrix coding using dual digital images. By modifying the bits in the pixels, we can conceal three bits of the secret message in two pixels. In other words, the embedding rate reaches 1.5 bits per pixel (bpp). The experimental results demonstrate that our method has a significantly larger embedding capacity of 786,432 bits compared to previous similar methods while still maintaining acceptable image quality defined by a peak signal-to-noise ratio (PSNR) greater than 30 dB. The proposed scheme is suitable for applications required to pass a large amount of data but with minor security of image quality to be visually acceptable.

Research on Internet Technology Innovation and Information Security Challenges in New Vehicle Energy Sector

With the rapid proliferation and advancement of new energy vehicles, Internet technology has garnered significant attention and application in this field. This study focuses on innovations in Internet technology in the domain of new automotive energy and the associated information security challenges. The innovations in Internet technology relevant to new energy vehicles, including Telematics, intelligent driving, and remote control, are initially explored. Subsequently, the information security challenges brought about by these innovations are analyzed, encompassing various aspects such as data privacy breaches, remote attacks, and malware infections. The significance of information security in the development of new energy vehicles is emphasized. Solutions and suggestions, including the strengthening of encryption technology, the establishment of a robust security framework, and the enhancement of user education and awareness, are put forward. In conclusion, the current state of research on Internet technology innovation and information security challenges is summarized, and it is suggested that future research should delve deeper into the trajectory of Internet technology development in the field of new energy vehicles, along with the attendant information security challenges, to provide theoretical and practical support for promoting the healthy development and secure application of the new energy vehicle industry.

Retracted: Prevention of Business Risks of Internet Information Security Platforms Based on Blockchain Technology.

[This retracts the article DOI: 10.1155/2022/7671810.].

Application of internet of things data processing based on machine learning in community sports detection

Due to the rapid development of the IoT ecosystem, a large amount of IoT data has been generated. However, in the current development process of the Internet of Things, how to ensure data security is a key issue. Traditional IoT security protection is relatively basic. With the increase of data size, these facilities need to be further improved in terms of computing, information security, storage information, and stability. However, traditional security and privacy protection methods are often insufficient for large topology structures. Blockchain is based on distributed networks, characterized by monotonous and decentralized data. Blockchain also provides a new approach to encrypting IoT security information. This article introduces blockchain technology into the Internet of Things, which can prevent reliance on centralized servers and effectively protect internet data and information security. Then this article also analyzed the motion recognition and detection of community sports, as well as the widespread application of computer vision and machine learning technologies in various fields such as computer mining and data security. Motion detection technology is very important in the field of computer vision and has applications in various real-world scenarios. This article studies new ideas for information encryption in the computer Internet of Things, and also analyzes machine learning and motion detection systems and applies them to community sports, improving the development of community sports.

International Negotiations in the Digital Age

The digital revolution has a significant impact on world politics, including the practice of international negotiations and diplomacy, which, being extremely conservative areas of human activity, still have to adapt to the new digital reality conditions. The practice of digital diplomacy, which involves using social networks to interact with a wide international audience, is becoming widespread. New diplomacy formats are emerging that focused on working with big data, machine learning and artificial intelligence technologies. This study explores the impact of the digital revolution on the practice of international negotiations. Methodologically, the analysis is based on the structural-functional approach, according to which international negotiations act as a structural element of diplomacy and foreign policy. At the same time, the authors single out the invariants of negotiations, which include the stages of international negotiations - preparation phase, discussions and implementation of the results of negotiations. The digital revolution is changing the nature of international negotiations, creating new opportunities for negotiation tactics, as well as new challenges, primarily related to information security and confidentiality. In addition, the development of digital technologies produces new subject areas of international negotiations that focus on Internet regulation, information security and other digital society problems, and contributes to the emergence and development of new international negotiations formats - multistakeholder negotiations and online remote negotiations. The authors conclude that the main negotiation invariants remain the same. However, digital technologies are transforming the available negotiating tools and tactics. Under these conditions, new knowledge and competencies are in demand among diplomats, in particular, in the field of data management and information security.

Development trend of internet technology finance and information security with perspective of web based system assurance engineering

Development trend of internet technology finance and information security with perspective of web based system assurance engineering

An enhancement of cyber security management for opportunistic systems

Customers demonstrate the ability to share partnerships and information with far-flung suppliers. These suppliers can offer varying degrees of relationship, from programming-as-a-help to organizational models as-a-help. They may provide direct information by loading or supervising assistance. This reassignment arbitrariness applies to the general view of spread calculations. Blatant people use the term exhaustively, but this record uses “scattered illustrations” while proposing a revised direction and collection, such as program and stage affiliations. Passed Ranchmen provides vitality and an open door for making clear connections. In particular, proper adoption would allow the design of wealthy devices to perform serious computations. Instead of generic conventions aimed at moving or storing critical information in the clear, these frameworks monitor information in the cloud and make it accessible elsewhere as needed. With the advent of the data age, web applications permeate people's lives and work, and electronic applications are increasingly used in various areas such as: Internet Administrator and Device Control. In the endless internet, web affiliation requires all data and information. With the proliferation of the WEB, errands and information about WEB applications have become the most unusual attack surface for network manufacturers. As related reports show, the Internet's information security requirements are a vast technology for secure development. Tasks and web applications were hacked and 75% of internet threats were related to web applications. These security opportunities created fundamental challenges for the affected regions.

Research on Machine Learning Algorithm for Internet of Things Information Security Management System Research and Implementation

To study in the Internet information security and privacy problem, a method based on IoT card monitoring technology based on machine learning, the technology can use fuzzy c -means algorithm for online business audit, using the Naive Bayes algorithm to classify Internet content and text messages, on the analysis of the comparison of the measurement method based on distance and based on the similarity. The concept of divergence in information theory is used to measure the difference between probability distributions. Finally, the feasibility of the proposed method is validated using the data from the machine learning database. The experimental results show that under the same privacy gain, the data availability relationship between the three anonymous protection methods is roughly satisfied as follows: when the privacy gain is less than 0.85, U dverity < U emonymity < U eclorenes ; when the privacy gain is greater than 0.85, U uxanaymiy < U uiversriy < U closencs . And it proves that on the premise of ensuring efficiency and accuracy, the system can find a large number of illegal IoT cards and effectively guarantee the security of IoT.

The self-assessed information security skills of the Finnish population: A regression analysis

Instead of traditional services, citizens are increasingly being offered e-services, which require information security skills. However, the majority of research on information security skills has been conducted in homogenous groups of people. The purpose of this study was to describe self-assessed information security skills of the population of Finland and factors associated with the skills. A population survey covering inhabitants aged 20 and upwards was conducted from September 2020 to February 2021. The cross-sectional dataset was weighted (n = 6023) to ensure it represented the population. Descriptive statistics were used to establish an initial understanding. Then a regression analysis was conducted to identify the variables that were associated with information security skills. The results demonstrate that 78% of the respondents assessed their information security skills as good. There was a strong positive association between Internet skills and information security skills. Other factors that demonstrated a statistically significant association were age, level of education, financial situation, e-service use, information security concerns, functional health deficits, and major depression. Even though the majority of people were confident in their information security skills in the online environment, there was evidence of a skills gap that affected people in all age groups, more often senior citizens. The findings of this study increase our understanding of information security skills at the population level. The results can be used to identify groups who are not confident in their information security skills and for designing safer e-services and education or guidelines on information security.

Prevention of Business Risks of Internet Information Security Platforms Based on Blockchain Technology.

The increasing maturity of Internet information technology has led to the rapid rise of blockchain technology. In essence, a blockchain is a shared database. In recent years, blockchain technology has attracted the attention of the public and society. With the continuous development of the market economy, many domestic enterprises have grown in size. At the same time, companies are also faced with various risks, and business risks will have a great impact on the company's production. This article aims to prevent the business risk of Internet information security platform enterprises based on blockchain technology. Through the PoS algorithm, PoW algorithm, secure hash algorithm, and the principle of direct trust, the Internet information security platform is designed. Firstly, the platform is used for a business risk test with a small company, and the platform satisfaction survey is conducted on the employees of the company. The test results show that the subplatform design reduces the business risk of the company by 5%–10%, and employee satisfaction is high. The signature simulation of this algorithm under the same conditions as the SMRA and RSAR methods is also carried out. The results show that the performance of this algorithm is better. This study opens up a new path for small and medium-sized enterprises to prevent business risks.

The Latticed-Based Path Privacy Protection Aggregation Scheme for Internet of Vehicles

With the occurrence of information leakage events of online ride-hailing, the information security of Internet of Vehicles has been highly valued by the society. Once the information of the Internet of Vehicles is exposed by the online ride-hailing platform or stolen by hackers, it will pose a fatal threat to the personal and property safety of users, and even cause a major information security accident to the whole society. Based on a post-quantum cryptography system, this paper proposes a practical privacy protection scheme for ride-hailing route information, which can present the complete statistical aggregation operation of the route and the frequency from the starting point to the destination without the visibility of the ride-hailing platform, and ensure the data privacy security of a single vehicle. Compared with representative multi-vehicle aggregation solutions, we not only guarantee message privacy, confidentiality, integrity, forward and backward security, anti-man in attack and anti-redial attack, but also achieve multi-dimensional aggregation, CCA security and anti-quantum attack. Through the analysis of the experiment, the cost of our scheme is reasonable. Therefore, the scheme is more practical in this scenario.

An Integration Hub of Exercise and Medical Care – Mobile Health Application's Service Construction and Regulations Navigation in "Health China"

Exercise mobile health application (mhAPP) is the integration hub of exercise and medical care, a new health management tool. It can facilitate the monitoring of some physiological health indicators of the human body during exercise/quiet state, collect information on exercise and diet behavior, and even medical history, and quickly generate a "health portrait" of a group or an individual, which is of great significance for China's big health services. Based on China's market service demand, data exchange theory, Internet information security law, APP industry decree and regulation, and borrowing from the U.S. APP information management system, this study constructs a theoretical model of China's big health service system with mhAPP as data source, government-regulated cloud platform as data manager, and hospitals, CDCs, shopping malls, restaurants and other organizations as third-party data users, and designed ordinances and regulations to support its operation.

Application of internet of things information security in the informationization of sports training and education

In recent years, the information technology of the Internet of Things has been developed by leaps and bounds, and the development of hardware technology has promoted the development of software technology. New concepts, new applications and new products emerge endlessly. Computer vision technology has made great progress, and industrial cameras are developing rapidly and are widely used in real life. The realization of high-definition capture and imaging functions of industrial cameras creates conditions for obtaining scientific data. This article aims to study the application of information security of the Internet of Things in the informationization of sports training and education. Correctly and objectively evaluate and understand the information security level of the Internet of Things. The guidance of computerization of sports training and education is based on the continuous and effective comparison of the implementation effect of computerization and the development strategy, and then the improvement of computerization work. Formulate the correct information strategy and provide assistance in specific implementation. On the basis of benefit, pragmatism and overall planning, formulate the correct information strategy and provide assistance in specific implementation. On the basis of benefit pragmatism and overall planning. Through experiments to master the Internet information security mechanism and use experimental questionnaire surveys and other methods to explore the application of Internet of Things information security in the informationization of sports training education, modern education must make full use of information technology, introduce physical education classroom teaching, and realize modern teaching. The experimental results of this article show that the application effect of Internet of Things information security information technology in physical education has been significantly improved. 60% of students have created better conditions for the current informationization of physical training and education, so that students can not only learn theoretical knowledge, but also deepen the understanding of sports in information teaching.

Cloud Trust-Driven Hierarchical Sharing Method of Internet of Things Information Resources

Short information sharing time is one of the problems to be solved in the traditional Internet. Therefore, this paper proposes a hierarchical simulation of the Internet of Things sharing structure framework that trusts the cloud to drive Internet information resource sharing. By setting thresholds and iterative adjustment parameters, a complementary judgment matrix is constructed to obtain the minimum nonnegative deviation value and the optimal weight vector. This paper sorts according to the value of the Internet information security model, obtains the optimal model to avoid human tampering, and designs the information resource acquisition process to ensure the reliability of the source data. We use radio frequency identification (RFID) equipment in the preprocessing of massive heterogeneous data in the Internet of Things. In a network environment where resources are limited and heterogeneous are fully considered, the trust-based adaptive detection algorithm is used to evaluate the credibility of the trust-driven algorithm for hierarchical information resource sharing services in the cloud environment of the Internet of Things. We propose a cloud trust-driven hierarchical information resource sharing Internet information resource model. Firstly, the key characteristics of hierarchical information resource sharing are analyzed. Then, a hierarchical information resource sharing model was established by using specific constraints, trust steepness function, cloud trust evaluation criteria, and trust constraint coefficient. Finally, an example of IoT system is designed to verify the effectiveness of the model. Experimental results show that, compared with the traditional model or algorithm, this model has a good hierarchical sharing effect of the underlying resource information.

Concealment of sensor network node interaction

The aim of this study is to increase the security of sensor network hosts by means of node interaction concealment. This paper outlines existing methods and approaches to information security of sensor network and internet of things systems. The authors developed a new secure data communication method based on dynamic network topology. This method allows to conceal sensor network data communication from an intruder breached an outer security perimeter. The new method secures data transfer and differs from the existing switching approaches that conceal sensor network hosts.

Human factor, a critical weak point in the information security of an organization's Internet of things

Internet of Things (IoT) presents opportunities for designing new technologies for organizations. Many organizations are beginning to accept these technologies for their daily work, where employees can be connected, both on the organization's premises and the “outside”, for business continuity. However, organizations continue to experience data breach incidents. Even though there is a plethora of researches in Information Security, there “seems” to be little or lack of interest from the research community, when it comes to human factors and its relationship to data breach incidents. The focus is usually on the technological component of Information Technology systems. Regardless of any technological solutions introduced, human factors continue to be an area that lacks the required attention. Making the assumption that people will follow expected secure behavioral patterns and therefore system security expectations will be satisfied, may not necessarily be true. Security is not something that can simply be purchased; human factors will always prove to be an important space to explore. Hence, human factors are without a doubt a critical point in Information Security. In this study, we propose an Organizational Information Security Framework For Human Factors applicable to the Internet of Things, which includes countermeasures that can help prevent or reduce data breach incidents as a result of human factors. Using linear regression on data breach incidents reported in the United States of America from 2009 to 2017, the study validates human factors as a weak-point in information security that can be extended to Internet of Things by predicting the relationship between human factors and data breach incidents, and the strength of these relationships. Our results show that five breach incidents out of the seven typified human factors to statistically and significantly predict data breach incidents. Furthermore, the results also show a positive correlation between human factors and these data breach incidents.

RETRACTED ARTICLE: Research on personal credit evaluation of internet finance based on blockchain and decision tree algorithm

With the development of Internet finance, existing financial platforms have gradually formed a large-scale, dynamic operating environment. How to ensure information security and realize personal credit evaluation is an urgent problem to be solved in the development of Internet financial platforms. The rise of blockchain technology has provided new solutions for the management of Internet financial platforms and information security. In view of the shortcomings of the current Internet financial credit evaluation, this article discusses the key standards of personal credit evaluation. With the help of blockchain, decision tree, and other technologies, this paper designs the credit evaluation process and establishes personal credit evaluation technology. Experiments and analyses show that this technology can effectively improve the transparency of personal credit information in Internet finance. This technology is used to study credit risk assessment factors and provide new solutions for the intelligent transformation and upgrading of Internet finance.