Network Security Data Research Articles

Review of Cyber Attack Detection: Honeypot System

The number of connected devices in the network is growing day by day, and as the number of linked devices grows, so will the number of cyberattacks. All devices connected to the Internet has become a target of cyberattacks as network attack methods have developed. As a result, the security of network data cannot be neglected. To handle the future threats in this way, we employ honeypots, which are conceptual framework traps designed to block unauthorized access to both PCs and data. Every day, a large number of people access the internet throughout the world. Honeypot, also known as Intrusion Detection Technology, is a type of security technology that screens devices to prevent unwanted activities. This article will provide an overview of cyber security as well as a discussion of machine learning, cyber threats, and honeypot system-based techniques. This review paper was the result of a lot of research, and in assessing honeypots, the researchers found that they are becoming more of a concern for experts as an important security tool that can halt or limit system attacks and provide analysts with insights into the origins and behaviours of such attacks.

Edge-Oriented Computing: A Survey on Research and Use Cases

Edge computing is a distributed computing paradigm such that client data are processed at the periphery of the network, as close as possible to the originating source. Since the 21st century has come to be known as the century of data due to the rapid increase in the quantity of exchanged data worldwide (especially in smart city applications such as autonomous vehicles), collecting and processing such data from sensors and Internet of Things devices operating in real time from remote locations and inhospitable operating environments almost anywhere in the world is a relevant emerging need. Indeed, edge computing is reshaping information technology and business computing. In this respect, the paper is aimed at providing a comprehensive overview of what edge computing is as well as the most relevant edge use cases, tradeoffs, and implementation considerations. In particular, this review article is focused on highlighting (i) the most recent trends relative to edge computing emerging in the research field and (ii) the main businesses that are taking operations at the edge as well as the most used edge computing platforms (both proprietary and open source). First, the paper summarizes the concept of edge computing and compares it with cloud computing. After that, we discuss the challenges of optimal server placement, data security in edge networks, hybrid edge-cloud computing, simulation platforms for edge computing, and state-of-the-art improved edge networks. Finally, we explain the edge computing applications to 5G/6G networks and industrial internet of things. Several studies review a set of attractive edge features, system architectures, and edge application platforms that impact different industry sectors. The experimental results achieved in the cited works are reported in order to prove how edge computing improves the efficiency of Internet of Things networks. On the other hand, the work highlights possible vulnerabilities and open issues emerging in the context of edge computing architectures, thus proposing future directions to be investigated.

Analysis of Encryption Algorithms Proposed for Data Security in 4G and 5G Generations

This paper intended to investigate and analyze encryption algorithms that can be proposed to perform data security in 4G and 5G networks. The research explores different standards, services, and features presented via 4G and 5G networks. Also, the basic components of encryption algorithms (e.g., ZUC, SNOW 3G, and AES) are investigated. For instance, initialization keys have been identified and analyzed due to their vital roles in determining the security of the encryption algorithms. Moreover, the researchers analyzed the effective elements of these algorithms (i.e., LFSR registers, substitution boxes, NLF functions like finite state machines, Math transformations, secret encryption keys, and non-secret IV keys). Cryptanalysis methods play important roles in determining the security of these algorithms. Thus, some cryptanalysis methods have been explored and investigated. Various weak points have been identified in initialization process of these algorithms. Therefore, different recommendations are presented that enhance the security of these ciphers, and can be reflected in data security in 4G and 5G networks.

THE ADVANCED METHOD OF PROTECTION OF PERSONAL DATA FROM ATTACKS USING SOCIAL ENGINEERING ALGORITHMS

Social interaction of subjects in the modern world, in addition to positive forms, also has negative ones. In modern society it is impossible to do without social networks and in the modern world the Internet - technologies prevail. Currently, everyone connected to a computer is registered in at least one social network. Social networks attract people, because in today's world all people communicate, exchange information, and get acquainted, some people come up with a virtual world in which they can be fearless, and popular and thus abandon reality. The problem related to the security of personal data in social networks is the most relevant and interesting in modern society. Analysis of methods of protection of personal data from attacks using social engineering algorithms showed that it is impossible to prefer any one method of protection of personal information. All methods of personal data protection purposefully affect the protection of information, but protection in full can not be provided by only one method. Based on the analysis of methods of personal data protection, we have proposed an improved method of protecting personal data from attacks using social engineering algorithms. Improvement is a combination of two existing methods aimed at improving the effectiveness of user training. Using the features of the proposed method formulated by us, it is the increase of user training that will provide better protection of personal data. The main advantage of the proposed method is that it uses the synergy of existing methods, which are aimed at educating users and learning to protect their personal information. The direction of further research: analysis and improvement of methods of attacks not only with the help of phishing social engineering but also with the help of other methods of social engineering of other types. Creating a mathematical model to protect personal information from attacks using social engineering methods.

OTP-Based Software-Defined Cloud Architecture for Secure Dynamic Routing

In the current era, anyone can freely access the Internet thanks to the development of information and communication technology. The cloud is attracting attention due to its ability to meet continuous user demands for resources. Additionally, Cloud is effective for systems with large data flow such as the Internet of Things (IoT) systems and Smart Cities. Nonetheless, the use of traditional networking technology in the cloud causes network traffic overload and network security problems. Therefore, the cloud requires efficient networking technology to solve the existing challenges. In this paper, we propose one-time password-based software-defined cloud architecture for secure dynamic routing to mitigating the above-mention issues. The proposed cloud architecture provides a secure data path through dynamic routing using One-Time Internet Protocol (OTIP) algorithm between each layer. On the network side, we use software-defined technology to provide efficient network management and data security. We introduce a software-defined cloud architecture that applies OTIP algorithms for secure dynamic routing. We conduct a comparative analysis between general IP communication and proposed OTIP communication architecture. It evaluates the performance of OTIP algorithms. Finally, we examine the proposed software-defined cloud architecture, including how to apply OTIP in secure dynamic routing according to the results of the comparative analysis.

Integration of Fog Computing for Health Record Management Using Blockchain Technology

Internet of Medical Things (IoMT) is a breakthrough technology in the transfer of medical data via a communication system. Wearable sensor devices collect patient data and transfer them through mobile internet, that is, the IoMT. Recently, the shift in paradigm from manual data storage to electronic health recording on fog, edge, and cloud computing has been noted. These advanced computing technologies have facilitated medical services with minimum cost and available conditions. However, the IoMT raises a high concern on network security and patient data privacy in the health care system. The main issue is the transmission of health data with high security in the fog computing model. In today's market, the best solution is blockchain technology. This technology provides high-end security and authentication in storing and transferring data. In this research, a blockchain-based fog computing model is proposed for the IoMT. The proposed technique embeds a block chain with the yet another consensus (YAC) protocol building security infrastructure into fog computing for storing and transferring IoMT data in the network. YAC is a consensus protocol that authenticates the input data in the block chain. In this scenario, the patients and their family members are allowed to access the data. The empirical outcome of the proposed technique indicates high reliability and security against dangerous threats. The major advantages of using the blockchain model are high transparency, good traceability, and high processing speed. The technique also exhibits high reliability and efficiency in accessing data with secure transmission. The proposed technique achieves 95% reliability in transferring a large number of files up to 10,000.

Digital twins to fight against COVID-19 pandemic

This study is aimed to explore the anti-epidemic effect of artificial intelligence (AI) algorithms such as digital twins on the COVID-2019 (novel coronavirus disease 2019), so that the information security and prediction accuracy of epidemic prevention and control (P & C) in smart cities can be further improved. It addresses the problems in the current public affairs governance strategy for the outbreak of the COVID-2019 epidemic, and uses digital twins technology to map the epidemic P & C situation in the real space to the virtual space. Then, the blockchain technology and deep learning algorithms are introduced to construct a digital twins model of the COVID-2019 epidemic (the COVID-DT model) based on blockchain combined with BiLSTM (Bi-directional Long Short-Term Memory). In addition, performance of the constructed COVID-DT model is analyzed through simulation. Analysis of network data security transmission performance reveals that the constructed COVID-DT model shows a lower average delay, its data message delivery rate (DMDR) is basically stable at 80%, and the data message disclosure rate (DMDCR) is basically stable at about 10%. The analysis on network communication cost suggests that the cost of this study does not exceed 700 bytes, and the prediction error does not exceed 10%. Therefore, the COVID-DT model constructed shows high network security performance while ensuring low latency performance, enabling more efficient and accurate interaction of information, which can provide experimental basis for information security and development trends of epidemic P & C in smart cities.

SECURING DATA NETWORK FOR GROWING BUSINESS VPN ARCHITECTURES CELLULAR NETWORK CONNECTIVITY

Private networks allow organizations to leverage, customize and dedicate LTE network capabilities to their own service needs. These networks are controlled and managed locally and can be optimized for specific network services and applications. Often they are used because there may be gaps in coverage where there is no cellular connectivity. Enterprises and businesses running on light application systems, using small bandwidth and requiring fast deployment such as ATMs, vending machines, digital signage kiosks and small store branches We propose a method and concept and implementation, in the form of a Data Network Security Configuration For Business Growth VPN architecture Mobile Network Connectivity for various businesses. By implementing products and services by developing the configuration and model of VPN Tunneling Protocol rules, using the EOIP Protocol and SSTP Protocol methods and virtualization schemes using the VLAN Bridging method on Wide Area Network (WAN) network connectivity. This method takes advantage of the LTE features found on the RB751U-2hnd and then integrates Huawei Mobile Broadband LTE. We also present a general Service Level Agreement (SLA) and an open source tools-based SLA network system Zabbix. Then configure the VPN Tunneling Protocol and its features on the RB751U-2hnd using Paramiko Network Automation. The focus of the results of this research is that by utilizing the available tools we will build a VPN with system monitoring facilities with the results achieved are network performance and availability and show that the design we build can be used for private connections for growing businesses. the results obtained from testing for 1 month for the 3 providers used, for the average throughput value with VPN tunneling applied TSEL 14.2 Mbps, ISAT 13.9 Mbps and XL 13.5 Mbps. The SLA value obtained is based on acceptable criteria, TSEL 91.5%, ISAT 91.8% and XL 90.6%.

A quantitative assessment method of network information security vulnerability detection risk based on the meta feature system of network security data

A quantitative assessment method of network information security vulnerability detection risk based on the meta feature system of network security data

Securing Data Network For Growing Business VPN architectures Cellular Network Connectivity

Private networks allow organizations to leverage, customize and dedicate LTE network capabilities to their own service needs. These networks are controlled and managed locally and can be optimized for specific network services and applications. Often they are used because there may be gaps in coverage where there is no cellular connectivity. Enterprises and businesses running on light application systems, using small bandwidth and requiring fast deployment such as ATMs, vending machines, digital signage kiosks and small store branches We propose a method and concept and implementation, in the form of a Data Network Security Configuration For Business Growth VPN architecture Mobile Network Connectivity for various businesses. By implementing products and services by developing the configuration and model of VPN Tunneling Protocol rules, using the EOIP Protocol and SSTP Protocol methods and virtualization schemes using the VLAN Bridging method on Wide Area Network (WAN) network connectivity. This method takes advantage of the LTE features found on the RB751U-2hnd and then integrates Huawei Mobile Broadband LTE. We also present a general Service Level Agreement (SLA) and an open source tools-based SLA network system Zabbix. Then configure the VPN Tunneling Protocol and its features on the RB751U-2hnd using Paramiko Network Automation. The focus of the results of this research is that by utilizing the available tools we will build a VPN with system monitoring facilities with the results achieved are network performance and availability and show that the design we build can be used for private connections for growing businesses. the results obtained from testing for 1 month for the 3 providers used, for the average throughput value with VPN tunneling applied TSEL 14.2 Mbps, ISAT 13.9 Mbps and XL 13.5 Mbps. The SLA value obtained is based on acceptable criteria, TSEL 91.5%, ISAT 91.8% and XL 90.6%.

Research on internal network data security monitoring method based on NB-IoT

In order to overcome the problems of poor data classification accuracy and effectiveness of traditional data monitoring methods, this paper designs a data security monitoring method based on narrow-band Internet of things. Firstly, the model of network data acquisition and sensor node’s optimal configuration is established to collect intranet data. Based on the analysis of data characteristics, dynamic intranet data analysis indexes are designed from three aspects: establishing security incident quantity index, establishing address entropy index and data diversion. According to the above-mentioned narrow-band data aggregation rate, the security index of the Internet of things is calculated to realize the security of monitoring data. The experimental results show that: whether the network attack exists or not, the accuracy rate of the method is always higher than 90%, the classification time is less than 4 s, and the energy consumption of monitoring process is always less than 150 J, which fully proves that the method achieves the design expectation.

Application of cloud computing in banking and e-commerce and related security threats

Cloud computing is one of the most powerful inventions that has grabbed the curiosity of technologists all around the world. Cloud computing has many advantages, but it also has a slew of security risks that no organization can afford to ignore. For a successful Cloud Computing adoption in a corporation, proper planning and awareness of emerging risks, threats, vulnerabilities, and potential solutions are necessary. As a result, determining the most effective solution instructions to increase cloud security has become important for all cloud operations. In this research, we are investigating and assessing the most noteworthy network security and data security risks on cloud systems based on a literature review. Because many businesses have promoted and marketed virtual environments as the solution to current security concerns, a deeper look finds that virtualization adds extra software to the network system, which may have a negative influence on security if built and deployed poorly. Furthermore, data center hubs link their servers through software, which means that if something goes wrong, the final effect might be damaging to security. Consumers must rely on trust mechanisms since they have no control over the cloud's resources. This article examines several cloud computing applications in banking and e-commerce, as well as the security issues associated with them.

Protection of Network Devices and Data security using Firewall A literature Survey

Protection of Network Devices and Data security using Firewall A literature Survey

The Application of Computer Technology in Electronic Information Engineering

With the continuous progress and development of our country’s economy, computer network technology has also been continuously improved and upgraded, and the level of EI technology has matured day by day, and the requirements on enterprises have become more and more stringent. In order to more fully expand the scope of EI computing and ensure that the technology is in a normal state of development, it is necessary to conduct applied research and exploration of EI engineering based on computer technology in order to use it for people to provide better services and create More value. This article is based on the research on the actual application of computer technology applied in our country’s EI technology engineering. First, it uses the literature research method to summarize the characteristics of our country’s EI technology engineering and the actual application of computer technology in EI engineering. In this paper, the investigation and research method is used to investigate some of the problems and suggestions faced by the actual application of computer technology in our country’s EI technology engineering. Through the analysis of the results, the in-depth study of the development trend of our country’s EI engineering is predicted. Survey results: Among the problems faced by the application of computer technology in EI engineering, local area network instability problems occur more frequently, accounting for about 45%, and then data and information security problems, accounting for about 30%. In the proposal for the development of the application of computer technology in EI engineering, the introduction of advanced local area networks will account for about 40% of the equipment, and about 35% for the strengthening of data security technology. It can be seen from this that the main research direction of computer technology application in EI engineering is local area network stability and data security.

Highly accurate and efficient two phase-intrusion detection system (TP-IDS) using distributed processing of HADOOP and machine learning techniques

Network security and data security are the biggest concerns now a days. Every organization decides their future business process based on the past and day to day transactional data. This data may consist of consumer’s confidential data, which needs to be kept secure. Also, the network connections when established with the external communication devices or entities, a care should be taken to authenticate these and block the unwanted access. This consists of identification of the malicious connection nodes and identification of normal connection nodes. For that, we use a continuous monitoring of the network input traffic to recognize the malicious connection request called as intrusion and this type of monitoring system is called as an Intrusion detection system (IDS). IDS helps us to protect our network and data from insecure and malicious network connections. Many such systems exists in the real time scenario, but they have critical issues of performance like accuracy and efficiency. These issues are addressed as a part of this research work of IDS using machine learning techniques and HDFS. The TP-IDS is designed in two phases for increasing accuracy. In phase I of TP-IDS, Support Vector Machine (SVM) and k Nearest Neighbor (kNN) are used. In phase II of TP-IDS, Decision Tree (DT) and Naïve Bayes (NB) are used, where phase II is the validation phase of the system for increasing accuracy. Also, both the phases are having Hadoop distributed file system underlying data storage and processing architecture, which allows parallel processing to increase the speed of the system and hence achieve the efficiency in TP-IDS.

Secure Data Sequence Recognition of All-Optical High-Speed Network Using Semiconductor Optical Amplifier

Semiconductor optical amplifier (SOA) has nonlinear optical effect and integration advantages, and is widely used in all-optical logic gates. Hence, it is used in the identification of all-optical high-speed network security data sequences. First, the SOA model is established and then simplified based on the existing model. On this basis, the identification model of all-optical high-speed network security data sequence is established, and the concept of integrated turbo-switch is introduced. The structure of the turbo-switch is analyzed. Then, an integrated turbo-switch architecture based on SOA-Mach Zehnder interferometer (MZI) is proposed, and its performance is verified by simulation. A data sequence recognition method for all-optical high-speed network security is proposed based on the integrated acceleration switch, and the difficulty of result recognition is analyzed. The simulation results of integrated turbo-switch show that when 1550 nm light passes through MZI, the interference can be almost completely cancelled, and the corresponding phase difference of 1538 nm light is less than 3 radians, that is, some light can pass through MZI. After the bias current of SOA of upper and lower arms of SOA-MZI is properly adjusted, MZI can play the function of tunable filter. Adjusting the bias current of SOA1 and SOA2 in the turbo-switch can control the “overshoot” program in the gain recovery curve, make SOA2 in a saturated working state, optimize the gain recovery curve, and improve the SOArelated mode effect, so that the turbo-switch can also output a more stable waveform under continuous “1” input. The recognition difficulty test shows that the target sequence after the cycle and the data sequence to be recognized are used for the “Exclusive NOR” operation, and the “AND gate” is added to realize the data sequence recognition and reduce the recognition difficulty.

Build Encrypted Interconnection Networks by application of IP Security and Mac Address Filtering Authentication Methods

To improve the security in data networks we use of IP Security and MAC Address Filtering authentication methods on network devices is very useful to be able to protect, verify and filter company data especially if data contain sensitive information like credit cards while using public data network. IP Security authentication provides integrity between connections, then Filtering MAC Address can help the router task to be able recognize users on the network, So that expected the combination between IP Security and Mac Address Filtering will provide security for every transfer and receive data from Headquarter to branch office, then the company doesn't have to worry about data package being robbed or manipulated by the unauthorized parties.

A decentralized framework for device authentication and data security in the next generation internet of medical things

Internet of Things (IoT) applications have gained a huge momentum and have spanned across all domains adding innovations to the prevailing solutions. The IoT networks generate enormous data comprising meteorological information, patient critical body parameters, finance, logistics, location of a tracking object, etc. Security for sensitive data,such as patient body critical parameters from an attached monitoring device, streaming over IoT networks is vital and is a need of the hour. Data integrity and user (or device) authentication are crucial for building a trust-worthy communication network among the peers in IoT networks. Most networks still employ specific software encryption algorithms that provide considerable data security. But quantum computing has proved the vulnerability of computationally vigorous cryptographic algorithms. A decentralized and scalable framework for device authentication and data security is proposed in this paper based on blockchain platform and Physical Unclonable Functions (PUFs). An authentication protocol is developed using PUF-based cryptographic primitives. The PUF-based keys are hard to replicate and almost impossible to predict because of the randomness in the physical design and complex mathematical modeling of the system. Lightweight Smart contracts are used to facilitate role-based access control. Data privacy is preserved by storing the sensitive data off-chain. As a proof of concept, an IoT-based healthcare system based on Ethereum permissioned blockchain is developed using the proposed framework. The​ designed PUF exhibits 48.46% uniqueness and 2.38% reliability. A comparative analysis with existing similar models shows that the proposed approach is feasible and provides a scalable solution for device authentication and data security in resource-limited medical IoT networks.

A Multi-Source Big Data Security System of Power Monitoring Network Based on Adaptive Combined Public Key Algorithm

The multi-source data collected by the power Internet of Things (IoT) provide the data foundation for the power big data analysis. Due to the limited computational capability and large amount of data collection terminals in power IoT, the traditional security mechanism has to be adapted to such an environment. In order to ensure the security of multi-source data in the power monitoring networks, a security system for multi-source big data in power monitoring networks based on the adaptive combined public key algorithm and an identity-based public key authentication protocol is proposed. Based on elliptic curve cryptography and combined public key authentication, the mapping value of user identification information is used to combine the information in a public and private key factor matrix to obtain the corresponding user key pair. The adaptive key fragment and combination method are designed so that the keys are generated while the status of terminals and key generation service is sensed. An identification-based public key authentication protocol is proposed for the power monitoring system where the authentication process is described step by step. Experiments are established to validate the efficiency and effectiveness of the proposed system. The results show that the proposed model demonstrates satisfying performance in key update rate, key generation quantity, data authentication time, and data security. Finally, the proposed model is experimentally implemented in a substation power IoT environment where the application architecture and security mechanism are described. The security evaluation of the experimental implementation shows that the proposed model can resist a series of attacks such as counterfeiting terminal, data eavesdropping, and tampering.

Research on Application of Artificial Intelligence in Network Security Defence

Network security gradually matures with the development of IT technology, and the exponential growth of massive data makes data leakage more common for many reasons. To explore the application of artificial intelligence technology in network security defense. Based on the security problems existing in different network information systems, this paper constructs an intelligent security analysis and management system from the perspective of network security protection, and introduces it into the big data network security platform. In combination with different security protection requirements, the existing network security problems are detected and dealt with. The VLAN routing command is configured to multiple switches to quickly complete multiple sets of network security solutions and implementation, and achieve a more comprehensive and intelligent network security defense.