Current Issue : October-December Volume : 2022 Issue Number : 4 Articles : 5 Articles
With the rapid development of modern society, the administrative information content rapid growth of e-government information resource sharing becomes the key of the government departments for effective social management. The cloud technology Internet big data are widely used and popular, which enable information resources to be shared among government data and are both an opportunity and challenge for effective e-government information resource sharing. It is of great significance to enhance government credibility. Information security risk assessment is a comprehensive evaluation of the potential risk of an uncertain stochastic process, traditional evaluation methods are deterministic models, and it is difficult to measure the security risk of uncertainty. On the other hand, with the opening and complexity of information system business functions, the nonlinearity and complexity of evaluation calculation also increase. By studying the relatively mature assessment criteria and methods in the field of information security, this study analyzes the information security status of small Internet of Things system based on the characteristics of Internet of Things information security. Combining the latest research results of information entropy neural network and other fields with the original risk assessment methods, the improved AHP information security risk assessment model is verified by simulation examples....
Information security can ensure an efficient application of classified computers. At present, in some classified computers, there exist problems and deficiencies in the field of information security management. It is not conducive to the control of information security. A network parallel computing system is a network-based system that has a high potential to resolve these issues. In recent years, with the development of cost-effective CPU and high-speed network technology, this system has gradually attracted the attention of people. Based on the research on distributed parallel computing, this paper abstractly analyzes the network parallel computing environment. It also discusses how a security protection system solution based on a distributed enterprise network environment helps rectify this problem. After research and analysis of classified computer information systems, this paper uses distributed parallel computing for building an advanced security system. Experimental results show that this method can improve the security status of the system to a much higher extent compared to the existing network security technologies. It has strong practicality and good social and economic value. The purpose of this paper is to provide information management tools for enterprises to improve the secrecy of management-level enterprises....
The Internet of Things (IoT) has disrupted the IT landscape drastically, and Long Range Wide Area Network (LoRaWAN) is one specification that enables these IoT devices to have access to the Internet. Former security analyses have suggested that the gateways in LoRaWAN in their current state are susceptible to a wide variety of malicious attacks, which can be notoriously difficult to mitigate since gateways are seen as obedient relays by design. These attacks, if not addressed, can cause malfunctions and loss of efficiency in the network traffic. As a solution to this unique problem, this paper presents a novel certificate authentication technique that enhances the cyber security of gateways in the LoRaWAN network. The proposed technique considers a public key infrastructure (PKI) solution that considers a two-tier certificate authority (CA) setup, such as a root-CA and intermediate-CA. This solution is promising, as the simulation results validate that about 66.67% of the packets that are arriving from an illegitimate gateway (GW) are discarded in our implemented secure and reliable solution....
In the era of global social media, Internet users’ privacy rights have been weakened, and the insight and alertness of individuals for privacy disclosure are decreasing. The security and flexibility of the system are usually the two ends of the measurement standard. While more and more users pursue the intelligence and convenience of using social media applications, letting big data technology and AI algorithms learn and use our privacy data cannot be avoided. On the basis of literature review, this paper summarized four categories of social media user behavior, which were divided into privacy concern behavior, privacy protection behavior, active disclosure behavior, and passive participation behavior. Using analytic hierarchy process, this paper explored their relationship with five different types of privacy: defensive privacy, identity authentication privacy, interactive privacy, psychological privacy, and integration information privacy. We finally formulated the most common twelve kinds of sub-internet user behavior on the degree of personal privacy disclosure, and provide users countermeasures to prevent privacy disclosure according to the different influence weights....
Whitelisting is a widely used method in the security field. However, due to the rapid development of the Internet, the traditional whitelisting method cannot promote the security of increasing Internet access. In recent years, with the success of machine learning in different areas, many researchers focus on the security of Internet access through machine learning methods. The most common form of machine learning is supervised learning. Supervised learning requires a large number of labeled samples, but it is difficult to obtain labeled samples in practical applications. This paper introduced an unsupervised deep learning algorithm based on seq2seq, which combined with the recurrent neural network and the autoencoder structure to realize an intelligent boundary security control mechanism. The main methods proposed in this paper are divided into two parts: data processing and modeling. In the phase of data processing, the access text table was coded with dicts, and all sequences were padded to the maximum. In the modeling phase, the network was optimized according to the principle of minimizing the reconstruction error. From the comparative experiments, the proposed method’s AUC on the public data set reached 0.99, and its performance is better than several classical supervised learning algorithms, proving that the proposed method has an efficient defense against abnormal network access....
Loading....