Vulnerabilities In Computer Networks Research Articles

Reinforcement learning-based autonomous attacker to uncover computer network vulnerabilities

Reinforcement learning-based autonomous attacker to uncover computer network vulnerabilities

Navigating the Cyber Threat Landscape: A Comprehensive Analysis of Attacks and Security in the Digital Age

In this contemporary digital age, cybersecurity stands as a crucial linchpin amid the expanding role of technology in our lives, encountering numerous challenges. This review addresses the imperative need for robust cybersecurity measures as malicious actors continually innovate methods to exploit vulnerabilities in computer systems, networks, and data. The exploration delves into the multifaceted realm of cybersecurity attacks, unveiling the evolving threat landscape and their profound implications. From cybercriminals utilizing phishing attacks to the covert tactics of malware and the disruptive potential of Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks, including Phishing, Zero-Day Exploits, Man-in-the-Middle, and SQL Injection Attacks, the cybersecurity battleground is ever-expanding. The study systematically categorizes cyber threats, scrutinizes their distinctive characteristics, and elucidates the modus operandi of each attack type. Through a meticulous dissection of cybercriminal methods and motivations and a comprehensive evaluation of countermeasure efficacy, this review offers indispensable insights for securing our digital future in an era marked by escalating interconnectivity and technological dependence.

Development of an Information Security System Based on Modeling Distributed Computer Network Vulnerability Indicators of an Informatization Object

Development of an Information Security System Based on Modeling Distributed Computer Network Vulnerability Indicators of an Informatization Object

CYBER SECURITY FRAMEWORK SELECTION: COMPARISION OF NIST AND ISO27001

Plans for preventing and mitigating vulnerabilities in computer networks are known as cybersecurity frameworks. With the assistance of the Cybersecurity Framework, organisations are able to reduce their vulnerability to cyber attacks and improve the strength of their defences. The cybersecurity framework has made the decision to take part in trials so that it may improve its ability to handle long-term security frameworks. This gives rise to concerns about cost and time rather than safety at this point in time because of the situation that is occurring. A firm may utilise the similarities that are shared by many cyber security frameworks as a reference to assist it in selecting the framework that is the most suitable for the needs that are unique to the organisation. According to the findings of this study, the risk maturity level, cost, and certification are the three most significant components of CSF implementation for firms.

Research on firewall technology and its application in computer network security strategy

Computer network is a double-edged sword, which brings convenience to people's life and work, but also brings hidden dangers, and even suffer losses, especially in recent years, the unscrupulous elements use computer network vulnerabilities to steal important data and seek improper benefits, which has caused serious network security problems. Among them, focus on the application of firewall technology can effectively prevent and supervise the existence of network security threats in the computer, control access to the Internet, and ensure the safe operation of computer networks. In this paper, from the importance of firewall, we explore the main functions, technical principles, architecture and use scenarios of cloud firewall, and propose the application in the computer network security strategy for reference.

Computer Network Vulnerability Detection and Semantic Data Analysis Optimization Based on Artificial Intelligence

In order to solve the network security vulnerabilities in the process of network information interaction, which affect the integrity and confidentiality of data. The computer network vulnerability detection and semantic data analysis optimization based on artificial intelligence are proposed, and the results show that the final accuracy of the test set is improved to 88.5%, but the false positive rate is as high as 18%. Based on the direct classification model, the code under test is compared with the vulnerability template, the model fuses the two direct classification models and reduces the false positive rate to less than 5% under the condition that the accuracy is basically the same.

A secured tor local network for nuclear power plant industry

The risk of cyber-attacks on a country has grown drastically. The cyber security risks against critical power infrastructure seem to be worsening. Obviously, any sort of assault on an atomic plant is very concerning. An attack that allows hackers to manipulate the system that control a nuclear reactor, while very difficult, could have very serious consequences. The main reason for this attack is vulnerabilities in local computer networks in power plants. Which has direct access to the internet without any major protection against cyber-attacks like phishing attacks against power plant employees, virus injection tools etc., As the main defense against this attacks is to make power plant networks and employees anonymous to the internet and making sure that no one is tracking the employees which can lead to loss of sensitive information of the plant. The Tor onion networking protocol is best suitable for these types of attacks on employees and computer networks in the power plant. Since providing Tor network for individual employee in practically impossible. Our projected work aims to establish an onion router which provide overall coverage of computer systems and employees which has access to power plant inside the perimeter of power plant. To simulate the plant local networks we construct an internet router using raspberry pi which is configured with Tor onion routing protocol access the internet by computers connected to our Router.

Zibererasoetatik babesteko, hacking etikoaren balioa

2020an, teknologiak bultzatutako gizarte batean bizi gara, eta datuak komunikatzeko sistemak funtsezkoak bihurtu dira gure eguneroko bizitzaren alderdi guztietan. Covid19-k erakutsi digu ezagutzen ez dugunak eszenatoki eta bizimodu berrietara eraman gaitzakeela, duela hilabete batzuk imajinatu ere ezin genituen lekuetara. Gaur egun, pertsonen, enpresen eta erakundeen arteko harremanak inoiz baino gehiago oinarritzen dira telekomunikazio-sareetan, eta, beraz, zibersegurtasun sofistikatuaren beharra oso garrantzitsua bihurtzen ari da gero eta handiagoak diren zibererasoetatik babesteko. Enpresak eta erakundeak diru kopuru handiak inbertitzen ari dira beren segurtasun zibernetikoan. Egoera horretan, hacking etikoa ohiko tresna bihurtu da behar den segurtasun-maila zehazteko. Hacking etikoaren helburua da sare informatikoetan ahuleziak eta kalteberatasunak aurkitzea, hackerrek sareetan sartzeko eta softwarearen ahuleziak azaltzeko erabiltzen dituzten ezagutza eta tresna berberak erabiliz. Dibulgazio-artikulu honek hacking etikoa zer den, zer onura dituen eta zergatik den beharrezkoa azaltzen du. Hacking etikoari buruzko artearen egoera bat aurkezten du, eta erakusten du enpresek eta erakundeek nola inplementa lezaketen hacking etikoa, sarbide-testetan (Penetration Testing Execution Standard, PTES) oinarritutako metodologia erabiliz.

The key technology of computer network vulnerability assessment based on neural network

With the wide application of computer network, network security has attracted more and more attention. The main reason why all kinds of attacks on the network can pose a great threat to the network security is the vulnerability of the computer network system itself. Introducing neural network technology into computer network vulnerability assessment can give full play to the advantages of neural network in network vulnerability assessment. The purpose of this article is by organizing feature map neural network, and the combination of multilayer feedforward neural network, the training samples using SOM neural network clustering, the result of clustering are added to the original training samples and set a certain weight, based on the weighted iterative update ceaselessly, in order to improve the convergence speed of BP neural network. On the BP neural network, algorithm for LM algorithm was improved, the large matrix inversion in the LM algorithm using the parallel algorithm method is improved for solving system of linear equations, and use of computer network vulnerability assessment as the computer simulation and analysis on the actual example designs a set of computer network vulnerability assessment scheme, finally the vulnerability is lower than 0.75, which is beneficial to research on related theory and application to provide the reference and help.

Assessing the effect size of users’ consciousness for computer networks vulnerability

Abstract In this paper the conditions and the findings of a simulation study is presented for assessing the effect size of users’ consciousness to the computer network vulnerability in risky cyber attack situations at a certain business. First a simple model is set up to classify the groups of users according to their skills and awareness then probabilities are assigned to each class describing the likelihood of committing dangerous reactions in case of a cyber attack. To quantify the level of network vulnerability a metric developed in a former work is used. This metric shows the approximate probability of an infection at a given business with well specified parameters according to its location, the type of the attack, the protections used at the business etc. The findings mirror back the expected tendencies namely if the number of conscious user is on the

Detection of vulnerabilities of the computer systems and networks using social engineering techniques

Information protection in computer systems and networks is focused on preserving its confidentiality properties of, integrity and availability from various inherently adverse impacts. Potentially possible adverse effects are interpreted as a threat. To prevent or complicate the possibility of realizing threats and reducing potential losses, a system of information protection measures is created and maintained in a healthy state. Such a system includes a computing system, physical environment, staff, and information. One of the most vulnerable elements of such system is staff. Within the framework of the socio-engineering approach, staff vulnerability is interpreted as its weaknesses, needs, mania (passions), hobbies. Manipulating them allows one to gain unauthorized access to information without destroying and distorting its main system-forming qualities. This is reflected in such forms as fraud, deception, scam, intrigue, hoax, provocation. The use of each of these manipulation forms is preceded by the determination of its content by careful planning, organization, and control. These actions are the basis of social engineering methods. Their use is aimed at imitating the actions of the information security violator, which are aimed at staff. This allows to assess the level of staff skills in the information security field and, as a result, to identify information vulnerabilities in computer systems and networks. The methods of social engineering used for this are divided into two groups, in particular, remote social engineering and personal contact. Methods of remote social engineering are implemented by means of modern telecommunications. In addition, the second group of methods involves the establishment of personal contact with the object of influence. In the end, it becomes possible not only to identify, neutralize, but also to prevent information vulnerabilities in computer systems and networks with the introduction of social engineering methods. Therefore, firstly, its protection is ensured taking into account the requirements of the information security policy; secondly, the rules of conduct of the staff are established, regulated by the job descriptions; thirdly, training is held to increase the persistence of employees stereotypes of the organization.

Computer Network Vulnerability Assessment and Safety Evaluation Application based on Bayesian Theory

Computer Network Vulnerability Assessment and Safety Evaluation Application based on Bayesian Theory

USING THE SECURITY NETWORK SCANNER GFI LANGUARD TO DISCOVER AND IMPROVE THE VULNERABILITIES IN THE COMPUTER NETWORK SYSTEMS

In this paper a comprehensive testing for computer network vulnerabilities is made. Thanks to the program product GFI LanGuard some critical flaws and vulnerabilities have been discovered and thereby this action improves the security mechanisms in the tested hosts. It is recommended that many cyber-security professionals and IT administrators to use GFI LanGuard in order to increase the computer and network security in their organizations.

A taxonomy framework based on ITU‐TX‐805 security architecture for quantitative determination of computer network vulnerabilities

ABSTRACTNetwork vulnerability taxonomy has become increasingly important in the area of information and data exchange for its potential use not only in identification of vulnerabilities but also in their assessment and prioritization. Computer networks play an important role in information and communication infrastructure. However, they are constantly exposed to a variety of vulnerability risks. In their attempts to create secure information exchange systems, scientists have concentrated on understanding the nature and typology of these vulnerabilities. Their efforts aimed at establishing secure networks have led to the development of a variety of methods and techniques for quantifying vulnerability. The objectives of the present paper are twofold: (1) to develop a taxonomy framework for the classification of network vulnerabilities on the basis of the ITU‐TX‐805 security architecture and (2) to develop a method on the basis of the second edition of Common Vulnerability Scoring System for the quantification of vulnerabilities within the proposed taxonomy framework. It is expected that the framework proposed in this paper will provide a comprehensive taxonomic structure that can be extended to all the different aspects of network vulnerability. Furthermore, it will help in the identification and effective management of vulnerabilities by their quantification. Copyright © 2012 John Wiley & Sons, Ltd.

A quantitative evaluation of vulnerability scanning

PurposeThe purpose of this paper is to evaluate if automated vulnerability scanning accurately identifies vulnerabilities in computer networks and if this accuracy is contingent on the platforms used.Design/methodology/approachBoth qualitative comparisons of functionality and quantitative comparisons of false positives and false negatives are made for seven different scanners. The quantitative assessment includes data from both authenticated and unauthenticated scans. Experiments were conducted on a computer network of 28 hosts with various operating systems, services and vulnerabilities. This network was set up by a team of security researchers and professionals.FindingsThe data collected in this study show that authenticated vulnerability scanning is usable. However, automated scanning is not able to accurately identify all vulnerabilities present in computer networks. Also, scans of hosts running Windows are more accurate than scans of hosts running Linux.Research limitations/implicationsThis paper focuses on the direct output of automated scans with respect to the vulnerabilities they identify. Areas such as how to interpret the results assessed by each scanner (e.g. regarding remediation guidelines) or aggregating information about individual vulnerabilities into risk measures are out of scope.Practical implicationsThis paper describes how well automated vulnerability scanners perform when it comes to identifying security issues in a network. The findings suggest that a vulnerability scanner is a useable tool to have in your security toolbox given that user credentials are available for the hosts in your network. Manual effort is however needed to complement automated scanning in order to get satisfactory accuracy regarding network security problems.Originality/valuePrevious studies have focused on the qualitative aspects on vulnerability assessment. This study presents a quantitative evaluation of seven of the most popular vulnerability scanners available on the market.