Biblio

With the continuous development of the Internet, artificial intelligence, 5G and other technologies, various issues have started to receive attention, among which the network security issue is now one of the key research directions for relevant research scholars at home and abroad. This paper researches on the basis of traditional Internet technology to establish a security identification system on top of the network physical layer of the Internet, which can effectively identify some security problems on top of the network infrastructure equipment and solve the identified security problems on the physical layer. This experiment is to develop a security identification system, research and development in the network physical level of the Internet, compared with the traditional development of the relevant security identification system in the network layer, the development in the physical layer, can be based on the physical origin of the protection, from the root to solve part of the network security problems, can effectively carry out the identification and solution of network security problems. The experimental results show that the security identification system can identify some basic network security problems very effectively, and the system is developed based on the physical layer of the Internet network, and the protection is carried out from the physical device, and the retransmission symbol error rates of CQ-PNC algorithm and ML algorithm in the experiment are 110 and 102, respectively. The latter has a lower error rate and better protection.

With the rapid development of Internet technology, the era of big data is coming. SQL injection attack is the most common and the most dangerous threat to database. This paper studies the working mode and workflow of the GreenSQL database firewall. Based on the analysis of the characteristics and patterns of SQL injection attack command, the input model of GreenSQL learning is optimized by constructing the patterned input and optimized whitelist. The research method can improve the learning efficiency of GreenSQL and intercept samples in IPS mode, so as to effectively maintain the security of background database.

With the development of Internet technology, the attacker gets more and more complex background knowledge, which makes the anonymous model susceptible to background attack. Although the differential privacy model can resist the background attack, it reduces the versatility of the data. In this paper, this paper proposes a differential privacy information publishing algorithm based on clustering anonymity. The algorithm uses the cluster anonymous algorithm based on KD tree to cluster the original data sets and gets anonymous tables by anonymous operation. Finally, the algorithm adds noise to the anonymous table to satisfy the definition of differential privacy. The algorithm is compared with the DCMDP (Density-Based Clustering Mechanism with Differential Privacy, DCMDP) algorithm under different privacy budgets. The experiments show that as the privacy budget increases, the algorithm reduces the information loss by about 80% of the published data.

With the proposal of the national industrial 4.0 strategy, the integration of industrial control network and Internet technology is getting higher and higher. At the same time, the closeness of industrial control networks has been broken to a certain extent, making the problem of industrial control network security increasingly serious. S7 protocol is a private protocol of Siemens Company in Germany, which is widely used in the communication process of industrial control network. In this paper, an industrial control intrusion detection model based on S7 protocol is proposed. Traditional protocol parsing technology cannot resolve private industrial control protocols, so, this model uses deep analysis algorithm to realize the analysis of S7 data packets. At the same time, in order to overcome the complexity and portability of static white list configuration, this model dynamically builds a white list through white list self-learning algorithm. Finally, a composite intrusion detection method combining white list detection and abnormal behavior detection is used to detect anomalies. The experiment proves that the method can effectively detect the abnormal S7 protocol packet in the industrial control network.

Energy is the material basis for human society to survive and has a very important strategic position in the national economy. With the advancement of Internet technology and the extensive use of clean energy, the energy industry has demonstrated a new development trend. Based on blockchain technology, this paper analyzes energy data security and multi-source synergy mechanism, processes and classifies a large amount of energy data in energy system, and builds a blockchain-based energy data supervision and transaction model. A summary tree of energy data is proposed; a consensus mechanism based on multi-source collaboration is proposed to ensure efficient negotiation; and finally, blockchain is verified in the energy scenario. This provides reference for the application of blockchain technology in the energy industry.

As trust becomes increasingly important in the software domain. Due to its complex composite concept, people face great challenges, especially in today's dynamic and constantly changing internet technology. In addition, measuring the software trustworthiness correctly and effectively plays a significant role in gaining users trust in choosing different software. In the context of security, trust is previously measured based on the vulnerability time occurrence to predict the total number of vulnerabilities or their future occurrence time. In this study, we proposed a new unified index called "loss speed index" that integrates the most important variables of software security such as vulnerability occurrence time, number and severity loss, which are used to evaluate the overall software trust measurement. Based on this new definition, a new model called software trustworthy security growth model (STSGM) has been proposed. This paper also aims at filling the gap by addressing the severity of vulnerabilities and proposed a vulnerability severity prediction model, the results are further evaluated by STSGM to estimate the future loss speed index. Our work has several features such as: (1) It is used to predict the vulnerability severity/type in future, (2) Unlike traditional evaluation methods like expert scoring, our model uses historical data to predict the future loss speed of software, (3) The loss metric value is used to evaluate the risk associated with different software, which has a direct impact on software trustworthiness. Experiments performed on real software vulnerability datasets and its results are analyzed to check the correctness and effectiveness of the proposed model.

There has been a growing expansion in the use of steganography, due to the evolution in using internet technology and multimedia technology. Hence, nowadays, the information is not secured sufficiently while transmitting it over the network. Therefore, information security has taken an important role to provide security against unauthorized individuals. This paper proposes steganography and cryptography technique to secure image based on hybrid edge detector. Cryptography technique is used to encrypt a secret image by using Vernam cipher algorithm. The robust of this algorithm is depending on pseudorandom key. Therefore, pseudo-random key is generated from a nonlinear feedback shift register (Geffe Generator). While in steganography, Hybrid Sobel and Kirch edge detector have been applied on the cover image to locate edge pixels. The least significant bit (LSB) steganography technique is used to embed secret image bits in the cover image in which 3 bits are embedded in edge pixel and 2 bits in smooth pixel. The proposed method can be used in multi field such as military, medical, communication, banking, Electronic governance, and so on. This method gives an average payload ratio of 1.96 with 41.5 PSNR on average. Besides, the maximum size of secret image that can be hidden in the cover image of size 512*512 is 262*261. Also, when hiding 64800 bits in baboon cover image of size 512*512, it gives PSNR of 50.42 and MSE of 0.59.