Integrated formal modeling and automated analysis of computer network attacks

In this paper, we present an approach for detecting and classifying attacks in computer networks by using neural networks. Specifically, a design of an intruder detection system is presented to protect the hypertext transfer protocol (HTTP). We propose the use of an application-based model using neural networks to model properly non-linear data. The benefit of this perspective is to work directly on the causes of an attack, which are determined directly by the commands used in the protected application. The intruder detection system is designed by defining three different neural networks, which include two multi-layer feed-forward networks and the Elman recurrent network. The results reported in this paper show that the Elman recurrent network achieved a performance around ninety percent of good detection, which demonstrates the reliability of the designed system to detect and classify attacks in high-level network protocols.

In article questions of detection of the distributed attacks in computer networks by means of artificial neural networks are considered. And also approximation of functions in space of quantitative signs is resulted.

Computer network attacks (CNA) is a no doubt actual theoretical and practical topic today. Espionage, public and private computer-systems disruptions committed by states have been a real life. States execute CNA's involving its agents or hiring private hacker groups. However, the application of lex lata remains unclear in practice and still undeveloped in doctrine. Nevertheless the international obligations, which states have accepted under the UN Charter and other treaties as well as customs - with any related exemptions and reservations - are still in force and create a legal framework, which one cannot ignore. Taking into account the intensity level or the consequences of a CNA the later could be considered as an unfriendly, but legal doing, or, as a use of force (prohibited under the article 2(4) of the UN Charter), or - in the case the proper threshold is taken - as an armed attack (which gives the victim-state the right to use force in self-defence under the customs and the article 51 of the UN Charter). Researches in the field of lex lata applicability to the CNAs could highlight gaps and week points of the nowadays legal regime. The subject is on agenda in western doctrine, and it is a pity - not in Russian one - the number of publication here is still unsatisfied. The article formulates issues related to CNAs and the modern international legal regime. The author explores the definition, legal volume of the term CNA, highlights main issues, which have to be analyzed from the point of the contemporary law.

Destructive and control operations are today a major threat for cyber physical systems. These operations, known as Computer Network Attack (CNA), and usually linked to state-sponsored actors, are much less analyzed than Computer Network Exploitation activities (CNE), those related to intelligence gathering. While in CNE operations the main tactics and techniques are defined and well structured, in CNA there is a lack of such consensuated approaches. This situation hinders the modeling of threat actors, which prevents an accurate definition of control to identify and to neutralize malicious activities. In this paper, we propose the first global approach for CNA operations that can be used to map real-world activities. The proposal significantly reduces the amount of effort need to identify, analyze, and neutralize advanced threat actors targeting cyber physical systems. It follows a logical structure that can be easy to expand and adapt.

With the development and popularization of the computer network, the security problem has increasingly become the focus of common concern. The computer network safety problems mainly include: protocol design issues, awareness, management system and technical operation. Hackers on the computer network attack techniques: Deceptive attack, masquerade attacks, vulnerability attack, covert attack and technical attack. Accordingly, we should take the corresponding safety countermeasures: strengthen network security education, using the network protection technology, detection technology and anti-virus technology. This paper mainly analyzes the defects and the security problems of computer network, discusses about the maintenance of computer network security and the way for computer network attack technology defense strategy.

The detection of computer network attacks is becoming increasingly important as the complexity of cyber-attacks threatening information systems and infrastructure continues to rise. To address these threats, artificial intelligence techniques have become a primary focus in the development of more effective attack detection systems. One algorithm that has proven reliable in this context is the C4.5 decision tree. This study aims to apply the C4.5 algorithm in network attack detection using a dataset that includes various types of attacks and network activities. The process includes data preprocessing, decision tree model building, and model performance evaluation. The results show that the C4.5 decision tree algorithm is effective in classifying network activities into attacks and normal activities with a satisfactory level of accuracy. The model successfully recognizes attack-related patterns, and further analysis identifies key factors influencing attack detection. This research provides a significant contribution to the development of reliable and efficient attack detection systems in computer networks. By applying the C4.5 decision tree algorithm, it is expected to help enhance information security and protect network infrastructure from increasingly complex cyber threats

Chapter 2 - Cyberwarfare Concepts

OLAP pre-aggregation techniques have proven to enable query time responses close to real-time in business and sta- tistical applications. In raster image databases (such as for geo services), similar data structures and operations appear. However, only one particular, comparatively sim- ple pre-aggregation technique is used there, namely image pyramids. We are working on systematically carrying over results from OLAP to geo raster databases. In this paper we identify a set of fundamental geo raster operations and formulate them algebraically, using a proven array model. We argue that pre-aggregation support for a few basic query patterns is sufficient for many practical situations.

SummaryIn today's world, many public and private services are provided virtually on the Internet. Due to the increasing dynamism and development of computer networks, intrusion detection systems, as one of the hottest topics in network security, has become an attractive area of research for researchers. The intrusion detection system tries to categorize the activity of the connections into two categories, normal and abnormal. In intrusion detection system, each connection is described based on a set of features, and decisions about whether that connection is normal or abnormal are made using those features. The act of determining the norm or abnormality of a connection is called classification. In this article, a method based on combined classification is proposed to detect zero‐day attacks. One of the most important innovations in this method is using a new version of the GRASP feature selection algorithm, which is used to diversify the base classifiers. In this method, an attempt is made to produce a subset of different features that have high accuracy; and variety to be used in the assembly stage. Experimental results showed that the method used to create feature subsets has high quality.

О дискретно-автоматных моделях атак в компьютерных сетях

There has been a dramatic increase in the total number of reported cyber security breaches and attacks in recent years. In response, government, and corporate entities have invested billions of dollars in funding research and development efforts for cyber operations, including computer network defense (CND) and computer network attack (CNA). While cyber operations have become an important national priority over the last decade, the Human Factors community has yet to approach it with critical mass. In its purest form, cyber operations are a complex sociotechnical system that can have effects across all levels of an organization. Due to a consistent interplay between human cognition, technology, and organizational constraints within the environment, the Human Factors community is particularly well-suited to address the problem space. We have assembled a panel of six scientists, technologists, and subject matter experts across multiple specializations in the Human Factors community to help begin this increasingly important discussion. The goal of this panel is to have an open discussion on how we can leverage our specializations and expertise to address the cyber operations landscape as a community.

: The Joint Chiefs of Staff envision information superiority, attained through the conduct of Information Operations (I0), as key in obtaining full spectrum dominance in future conflicts. Computer Network Attack (CNA) and Defense (CND) are relatively new I0 weapons that the operational commander will soon employ along with his other, more traditional, weapons to gain information superiority and maintain freedom of action while limiting that of his enemy. He will also have to defend against the same types of weapons wielded by his enemy, for the depth and breadth of networked computer system in the U.S. military makes him vulnerable to attack. Planning to execute, and defend against, a CNA is a task not addressed by current planning methodologies and procedures It will still require the planner to balance the operational factors of space, time, and force in relation to his objective, at times much like he would for a physical attack and at others in very new and interesting ways.

This chapter describes 5G networks based on the outcome of the study conducted in the 5GMF in Japan. The 5GMF identifies two key technologies necessary to support “extreme flexibility” and the wide range of use cases expected in the 5G era: “Advanced Heterogeneous Network” and “Network Softwarization and Slicing”. Network softwarization is an overall transformation trend about designing, implementing, deploying, managing, and maintaining network equipment and/or network components through software programming. Network slicing is the major feature provided by the overall trend expressed by the network softwarization. The chapter shows the breakdown of the end‐to‐end latency in the current mobile network. One of the aims of 5G is the provision of the emerging network paradigm that fits social requirements. Information‐Centric Network (ICN) is a promising candidate, with a variety of R&D activities ongoing worldwide. ITU‐T SG13 launched the focus group (FG) on IMT‐2020 in order to accelerate the study of the nonradio aspects of IMT‐2020.

The advantages of the multiple observation time approach for fault diagnosis have been demonstrated before by a fault diagnosis procedure based on partial specification of initial states. It was also shown that it is possible to perform fault simulation under the multiple observation time approach at very low computational overhead compared to conventional simulation. In this work, we combine these procedures and propose a low-complexity fault diagnosis procedure under the multiple observation time approach. Several observations made in this work allow us to increase the effectiveness of the proposed diagnosis scheme in terms of the resolution it achieves and its complexity.

Residential care facilities (RCF) for older people are facing high demands due to the COVID-19 pandemic. The aim of this study was to explore the workers’ perspectives on the changes in work and care dynamics amidst the first wave of the pandemic at Portuguese RCF. This is a descriptive, quantitative, and cross-sectional study. An online questionnaire about pandemic-induced changes in work and care dynamics was sent to 2325 RCF. These entities were then asked to share it with their workers. The participants (n = 784) were mostly women (92.7%) and mostly composed of technical directors (41.6%) and direct-care workers (17.1%). The respondents reported that during the first wave of the pandemic, when compared to the pre-pandemic period, there were greater difficulties in providing care related to the basic necessities of older people (52.7%); direct-care workers were required to work more consecutive hours in each shift (69.95%); direct-care workers had to live at RCF (14.8%), and there were changes concerning the possibility of promoting person-centered care (PCC) practices. It also revealed that focusing on disease prevention and sanitary measures alone facilitates practices that reinforce the traditional model of procedure-centered care and have negative consequences on the rights and well-being of those living and working at RCF, exposing and accentuating preexisting vulnerabilities. This study considers the pandemic’s serious implications and alarming questions about basic care, dignity, living, and working conditions at Portuguese RCF. These notions reinforce the need for change through redefining care policies and practices in Portuguese RCF beyond the pandemic. The current situation provides an opportunity to adopt a formal PCC model.