Massive Attack Research Articles

The structure-function relationship of Pseudomonas aeruginosa in infections and its influence on the microenvironment.

Pseudomonas aeruginosa is a human pathogen associated with both acute and chronic infections. While intensively studied, the basic mechanisms enabling the long-term survival of P. aeruginosa in the host, despite massive immune system attack and heavy antimicrobial treatment, remain to be identified. We argue that such infections may represent niche invasions by P. aeruginosa that influence the microenvironment by depleting host-derived substrate and activating the immune response. Bacteria embedded in cell aggregates establish a microenvironmental niche, where they endure the initial host response by slowing down their metabolism. This provides stable, lasting growth conditions with a constant, albeit slow supply of substrate and electron acceptors. Under such stable conditions, P. aeruginosa exhibits distinct adaptive traits, where its gene expression pattern reflects a life exposed to continuous attack by the host immune system and antimicrobials. Here, we review fundamental microenvironmental aspects of chronic P. aeruginosa infections and examine how their structural organization influences their in vivo microenvironment, which in turn affects the interaction of P. aeruginosa biofilm aggregates with the host immune system. We discuss how improving our knowledge about the microenvironmental ecology of P. aeruginosa in chronic infections can be used to combat persistent, hard-to-treat bacterial infections.

Joint Spectrum Sensing and Spectrum Access for Defending Massive SSDF Attacks: A Novel Defense Framework

Multiple secondary users (SUs) perform collaborative spectrum sensing (CSS) in cognitive radio networks to improve the sensing performance. However, this system severely degrades with spectrum sensing data falsification (SSDF) attacks from a large number of malicious secondary users, i.e., massive SSDF attacks. To mitigate such attacks, we propose a joint spectrum sensing and spectrum access framework. During spectrum sensing, each SU compares the decisions of CSS and independent spectrum sensing (IndSS), and then the reliable decisions are adopted as its final decisions. Since the transmission slot is divided into several tiny slots, at the stage of spectrum access, each SU is assigned with a specific tiny time slot. In accordance with its independent final spectrum decisions, each node separately accesses the tiny time slot. Simulation results verify effectiveness of the proposed algorithm.

HiAtGang: How to Mine the Gangs Hidden Behind DDoS Attacks

Identifying and determining behaviors of attack gangs is not only an advanced stage of the network security event tracing and analysis, but also a core step of large-scale combat and punishment of cyber attacks. Most of the work in the field of distributed denial of service (DDoS) attack analysis has focused on DDoS attack detection, and a part of the work involves the research of DDoS attack sourcing. We find that very little work has been done on the mining and analysis of DDoS attack gangs. DDoS attack gangs naturally have the attributes of human community relations. We propose a framework named HiAtGang, in which we define the concept of the gang detection in DDoS attacks and introduce the community analysis technology into DDoS attack gang analysis. Different attacker clustering algorithms are compared and analyzed. Based on analysis results of massive DDoS attack events that recorded by CNCERT/CC (The National Computer Network Emergency Response Technical Team/Coordination Center of China), the effective gang mining and attribute calibration have been achieved. More than 250 DDoS attack gangs have been successfully tracked. Our research fills the gaps in the field of the DDoS attack gang detection and has supported CNCERT/CC in publishing “Analysis Report on DDoS Attack Resources” for three consecutive years and achieved a good practical effect on combating DDoS attack crimes.

ANALYSIS OF THE ROLE OF ADDITIONAL PROFESSIONAL EDUCATION PROGRAMS IN PREVENTING THE SPREAD OF EXTREMISM AND TERRORISM IN THE EDUCATIONAL SPHERE AND YOUTH ENVIRONMENT

The problem of organizing counteraction to terrorist activity and other destructive phenomena ineducational institutions today seems more relevant than ever. Throughout the country, there has been anincrease in the statistics of acts of the use of firearms or cold steel in educational institutions (acts of schoolshooting), as a result of which the level of anxiety is growing among students and teachers of educationalorganizations who do not have the opportunity or do not know the rules of behavior in such emergencysituations. It can be noted that in the future, such actions can lead to the undermining of the spiritual andmoral bonds of society, the weakening of Russia in the domestic political and international arena. Today, within the framework of the hybrid-information war, a massive attack is being carried out on one of the mostimportant social institutions — education.It should be noted that the scientific and methodological support of activities to counter the ideology ofterrorism does not fully meet the real needs of practice and needs to be further improved. And in the contextof transferring, in particular, the education system, to remote rails, this problem becomes more relevantthan ever.It is the network of universities that can become the flagship for the formation of an anti-terroristideology and skills to counter terrorism and near-terrorist destructive phenomena.

Fungi as potential factors limiting natural regeneration of pedunculate oak (Quercus robur) in mixed‐species forest stands in Poland

AbstractDieback of youngQuercus roburseedlings can limit natural regeneration in mixed‐species forest stands in Poland. The aim of this study was to examine the role of fungi in the dieback of oak seedlings in central Europe. Fungi were isolated from the stems and roots ofQ.robur, from both healthy seedlings and seedlings with symptoms, that were sampled from four stands in Poland. In total, 111 distinct taxa were identified. Ascomycota was dominant, representing 95.6% of the isolates. Among the taxa identified,Alternaria alternata,Colletotrichum fioriniae,Colletotrichumgodetiae,Coniella quercicola,Diaporthe eres,Gnomoniopsis paraclavulata,Ilyonectria rufa,Mucor genevensis,Penicillium glandicola,Tubakia dryina, andUmbelopsis changbaiensiswere most frequently isolated, and were consistently found in stems and roots of both healthy and diseased plants. The community compositions of fungi in healthy and diseased stems were similar, althoughFusariumspecies, especiallyFusariumsp. 1 (FTSC 5) andF.sporotrichioides, were found mainly in seedlings with symptoms. The pathogenicity of the most consistently isolated species from stems and roots of diseased seedlings was tested onQ.roburseedlings.F.sporotrichioidescaused the largest lesions on inoculated seedlings. Six weeks after inoculation,D.eres,C.fioriniae,G.paraclavulata,T.dryina, andF.sporotrichioideskilled 0%–18.8% of seedlings, whileI.rufaandIlyonectriapseudodestructansdid not cause any lesions or other symptoms. This study is the first comprehensive report suggesting that massive fungal attack can lead to oak seedling dieback in mixed‐species forest stands in central Europe.

An Improvement of Security Scheme for Radio Environment Map Under Massive Attacking

Radio environment maps (REM) are widely used to enhance communication efficiency in spatial spectrum sharing. This can be generated using reports from the terminals. However, an open characteristic environment always leads to a security problem; for example, when malicious terminals exist in the environment and data falsification attacks occur, the accuracy of the REM is affected by the malicious action. In this study, we improve the double-layer monitor algorithm by optimizing the reward penalty function using a similarity comparison and sustainable monitor. The proposed algorithm can remove malicious terminal reports from the database to improve accuracy. Additionally, we propose a new algorithm involving interpolation based on spatial information to solve the problem of unequal information obtained from the meshes. By interpolation, a database can obtain sufficient datasets from each mesh. Furthermore, we defined an optimal attack strategy using the proposed security algorithm. The influence of malicious terminals can be the strongest among data falsification attacks; thus, we can check the performance more comprehensively. The simulation results indicate that the proposed method can eliminate the influence of malicious terminals and that a highly accurate REM can be obtained under massive malicious terminal attacks.

Eight Years and Nine Months of War

The Ukrainian army has undergone significant modernisation since the start of the war in 2014. That said, it was inadequately prepared for Russia’s invasion in February 2022. There was a shortage of heavy weapons, armoured vehicles, and ammunition. Nonetheless, the Ukrainian army proved itself able to cope with the massive attack and to liberate occupied areas. Decisive factors were the strong will to fight, the support of the population, good coordination of mobile units acting with great autonomy, the delivery of western artillery and rocket systems, a smart tactical approach, and not least of all mistakes made by the invaders. This enabled the Ukrainian army to achieve great successes in the defence of Kiev and Kharkiv in the first two months of the war and in significant reconquests during the summer and autumn. Where the occupying army has entrenched itself in urban areas or along well-fortified front lines, the Ukrainian armed forces are running into difficulties and paying a high price in blood.

Manufacturing and labor productivity as key elements of economic recovery in the course of the Marshall Plan implementation

The article addresses the best practices of manufacturing recovery and productivity improvement in the course of the Marshall Plan implementation in Europe post-World War II. It outlines the three most essential elements of the economic crisis on the continent in 1947: low manufacturing level, inflation, and inability to urgently cover the necessary imports from other parts of the world, especially from the United States of America. The following main reasons for falling labor productivity are determined: malnutrition, long break in the training of qualified workers for manufacturing, and equipment destruction and obsolesce. The article defines and characterizes three phases of manufacturing recovery in the course of the Marshall Plan implementation: elimination of the critical shortage of food, raw materials, and substitute goods, new investment program, and solution to productivity problem. Public savings supplemented by the substantial financial assistance of supporting partner funds are determined to be the most essential source of domestic investment funds in the countries covered by the Marshal Plan. Private capital mostly consisted of the funds of private companies. The following factors impacting productivity are examined: investment, technology and maintenance, attitude and motivation, managerial competence and training, personal relationship, labor efficiency, full employment, markets, diversification, competition, and governmental measures. The article shows the losses incurred by russian military aggression to Ukrainian industry and infrastructure, namely, direct losses to retail trade, manufacturing, land fund, agriculture, infrastructural facilities, railway infrastructure, and critical infrastructure. In particular, as of 1 September 2022, the estimated total direct losses of companies’ assets are $9.9 billion, which is the third largest item of direct infrastructural losses accounting for about 10% of the total losses. Taking into account massive russian missile attacks, the situation in the energy sector of Ukraine is especially hard since the problems with electricity cause disruption in the operation of many companies and risks for manufacturing and make impossible the continuous economic activity and the keeping of commitments to counteragents and customers, inevitably leading to the GDP decline. The article substantiates the reasonability of the consideration of the Marshall Plan implementation in Europe in the process of the post-war recovery of Ukraine. In particular, the factors like technological assistance, investment in modern industrial and energy equipment, establishment of the qualitative process of employee training and retraining, and labor efficiency will play an important role in the process of Ukraine’s post-war recovery. Significant destruction of Ukraine’s manufacturing and infrastructure caused by russian military aggression constitutes a powerful negative factor since they require much effort and funds to recover. However, they can also be considered from another standpoint – as a chance to modernize the destroyed companies and infrastructural facilities in the course of their reconstruction.

Системы ПРО и концепции ограниченной ядерной войны

In the case of an intercepting massive nuclear missile attack, the technical capabilities of modern missile defense systems remain poor, nevertheless, the options for using the latest missile defense systems go beyond the “classic nuclear scenario”. First and foremost, missile defense systems have been used in conventional armed conflicts. This practice has already demonstrated their combat effectiveness which has become an impetus for the ongoing technical modernization of their main elements. In recent years, the conflict scenarios have been worked out in the United States and Russia where the limited use of low-yield nuclear weapons is allowed. The limited nuclear strike can be launched at the initial stages of a traditional conflict to consolidate the acquired military benefits and disrupt the enemy’s counteroffensive. Obviously, the limited use of nuclear weapons is fraught with an aggravation of the risk of a rapid and uncontrolled nuclear escalation. Unexpectedly, in this context, missile defense becomes a severe deterrent. Missile defense systems deployed at critical military facilities can remove the incentives for the limited nuclear strike as well as give considerable strategic and political advantages. Under these circumstances, missile defense systems become key players in the military balance. To reduce the risks of the limited use of nuclear weapons the author proposes “a roadmap” based on revitalization of the main arms control regimes and use of the capabilities of modern missile defense systems. It is hypothesized that “thin” missile defense removes the incentive to launch the first limited nuclear strike, thus enhancing strategic stability.

The new energy model of post-war Ukraine: distributed generation and the electricity exchange market

Introduction. The task of Russia as an aggressor country during a large-scale war is to destroy the statehood of Ukraine, which is accompanied by the genocide of the population due to the destruction of critical life support infrastructure, in particular, facilities for generating electricity and transmitting it to consumers. As of the end of 2022, as a result of massive missile attacks, more than 50% of energy capacities have been destroyed, which in turn leads to long-term emergency power outages for household consumers and businesses. Such significant damage was caused by the legacy of the USSR model of centralized generation at several nuclear, thermal and hydroelectric power stations. Ukraine's signing of the Association Agreement with the EU provided for the reform of the energy sector, but centralization and monopolization did not allow the planned implementation, in particular, the formation of an electricity market with transparent exchange pricing mechanisms for this resource. The purpose. Based on the analysis of foreign experience, develop recommendations for the formation of a new energy model of post-war Ukraine. Methods. In the process of research, methods of analysis and synthesis, generalization and comparison, benchmarking was used to find the best foreign practices. It was revealed that the processes of distribution of electricity generation have been taking place on the energy market of EU countries for a long time, which increases the number of participants and contributes to the formation of exchange mechanisms for transparent pricing of this resource. The results. It has been proven that the restoration of the existing centralized generation will not solve the issue of energy security of the country in the future. It is proposed to include the formation of a new energy model based on the decentralization (distribution) of generation based on new environmentally friendly technologies and the electricity exchange market as part of Ukraine's post-war reconstruction strategies.

МОЖЛИВОСТІ ТА ПРОБЛЕМНІ ПИТАННЯ УДОСКОНАЛЕННЯ ЗАХИСТУ ОБʼЄКТІВ КРИТИЧНОЇ ІНФРАСТРУКТУРИ У СУЧАСНИХ УМОВАХ

The aggressive war against Ukraine makes it clear that the hopes of mankind that future wars will take place in the form of low-intensity conflicts, but rather in the economic, informational spheres without the use of military force, turned out to be in vain. Russia has demonstrated that such seemingly wild actions for the modern civilized world as the seizure of territories, the destruction of cities, attempts to destroy the statehood and self-consciousness of nations will remain relevant as long as autocratic regimes exist and there are no effective international mechanisms that would make any armed aggression impossible. Consequently, the issue of protecting territories and infrastructure in the face of large-scale aggression using the entire list of available types of means of armed struggle will, unfortunately, be relevant in the near future. The article analyzes the recent massive attacks on infrastructure facilities and modern technologies of air defense weapons. As a result of the analysis, possible directions for improving the protection of critical infrastructure facilities were proposed, the main of which is the use of a wide range of systems and complexes of very short-range weapons. In addition, a number of problematic issues and tasks were identified that need to be considered in order to improve the protection of critical infrastructure facilities, the main of which are: safety providing of using the proposed systems directly in populated areas or near them; ensuring the rational use of the resource of weapons, ammunition and other equipment and materiel associated with the functioning of the protection systems of objects; determination of the military formation which will be responsible for infrastructure facilities protecting.

Machine Learning With Variational AutoEncoder for Imbalanced Datasets in Intrusion Detection

As a result of the explosion of security attacks and the complexity of modern networks, machine learning (ML) has recently become the favored approach for intrusion detection systems (IDS). However, the ML approach usually faces three challenges: massive attack variants, imbalanced data issues, and appropriate data segmentation. Improper handling of the issues will significantly degrade ML performance, e.g., resulting in high false-negative and low recall rates. Despite many efforts have done in the literature, detecting security attacks in a complicated network environment with imperfect data collection is still an open issue. This work proposes a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">machine learning</i> framework with a combination of a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">variational autoencoder</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multilayer perceptron</i> model to deal with imbalanced datasets and detect the explosion of attack variants on the Internet. The detection engine also includes an efficient <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">range-based sequential search</i> algorithm to address the segmentation challenge in data pre-processing from multiple sources (network packets, system/statistic logs) effectively. Our work is the first attempt to demonstrate the effect of using an appropriate combination of ML models for boosting IDS detection capability in a heterogeneous environment, where data collection imperfection is common. Experimental results on a public system log dataset (e.g., HDFS) show that our method gains approximately as much as 97% on F1 score and 98% on recall rate, a promising result compared to the same measurement of other solutions. Even better, we found that the proposed treatment of imbalanced datasets can improve up to 35% on the F1 score and 27% on recall rate. The testing results also indicate that our model can detect new attack variants.

Popularna kultura u funkciji društvene kritike - slučaj Eutopia

The objective of this paper is to show how popular culture can have a function of social critique, discussing the ideas of Massive Attack's Eutopia EP. Despite problems related to a certain definition of popular culture and its ideologization, the paper will try to show that popular culture represents an appropriate and efficient instrument of social critique. Social criticism in popular culture points to the problems of the society in current circumstances. During the COVID-19 pandemic in 2020, a conceptual album, Eutopia, was published on the Internet platforms. Eutopia is presented as an audio-visual material in a popular format, with the voice-over narrative expositions of the scholars and activists about the contemporary problems, economic insecurities and inequalities, social injustices and climate emergencies. The pandemic situation caused a dramatic manifestation of the global structural problems, which represent an existential threat to the entire human society. From this standpoint, Eutopia provides solutions to some of the greatest problems of humanity today, suggesting a universal basic income, elimination of tax havens and general activism steered to overcoming and avoiding a climate emergency. Inspired by Thomas More's Utopia, a popular novel and masterpiece of Renaissance humanism, Eutopia presents a realistic Utopian vision that should motivate the entire public to assess and engage in a search for a better, just society. Therefore, Eutopia represents a creative piece of contemporary popular culture with a role of social critique, based on a humanistic endeavor of amelioration of humanity.

Monte Carlo method for predicting the stability of the functioning of the informatization object in the conditions of massive computer attacks

The application of the Monte Carlo method for solving the problem of predicting the functioning stability of the object of informatization in the conditions of massive computer attacks (MCA) is considered. The field of research represents practical and theoretical interests, since the methods developed by the theory of reliability are focused on simple, stationary, failure flows, which cannot be applied to the MCA conditions. In the conditions of the MCA, the period of normal functioning is commensurate with the recovery time, therefore, the application of the Poisson flow model leads to a significant error. To ensure the reliability of modeling, it is necessary to use an alternating process model, where the recovery time is commensurate with the period of operation and has a finite value, while analytical models of the real functioning processes are cumbersome, difficult to interpret and have no practical application.

Fluctuating Decision-Making in People with Mental Illness

Fluctuating Decision-Making in People with Mental Illness

SERP4IoT'21 Workshop Report

We face a new software crisis. In 1968, computer scientists learned that developing robust software requires skills, methods, and tools. Today, software and hardware engineers realize that developing a robust Internet of Things (IoT) also pushes the states of their art and practice. Recent news illustrate the many problems faced by IoT: from lack of interoperability to broken updates to massive security attacks. In this context, the 3rd International Workshop on Software Engineering Research and Practices for the Internet of Things (SERP4IoT) aims to provide a highly interactive forum for researchers and practitioners to address the challenges of, nd solutions for, and share experiences with the development, release, and testing of robust software for IoT systems.

An Effective Text Classifier using Machine Learning for Identifying Tweets’ Polarity Concerning Terrorist Connotation

Terrorist groups in the Arab world are using social networking sites like Twitter and Facebook to rapidly spread terror for the past few years. Detection and suspension of such accounts is a way to control the menace to some extent. This research is aimed at building an effective text classifier, using machine learning to identify the polarity of the tweets automatically. Five classifiers were chosen, which are AdB_SAMME, AdB_SAMME.R, Linear SVM, NB, and LR. These classifiers were applied on three features namely S1 (one word, unigram), S2 (word pair, bigram), and S3 (word triplet, trigram). All five classifiers evaluated samples S1, S2, and S3 in 346 preprocessed tweets. Feature extraction process utilized one of the most widely applied weighing schemes tf-idf (term frequency-inverse document frequency).The results were validated by four experts in Arabic language (three teachers and an educational supervisor in Saudi Arabia) through a questionnaire. The study found that the Linear SVM classifier yielded the best results of 99.7 % classification accuracy on S3 among all the other classifiers used. When both classification accuracy and time were considered, the NB classifier demonstrated the performance on S1 with 99.4% accuracy, which was comparable with Linear SVM. The Arab world has faced massive terrorist attacks in the past, and therefore, the research is highly significant and relevant due to its specific focus on detecting terrorism messages in Arabic. The state-of-the-art methods developed so far for tweets classification are mostly focused on analyzing English text, and hence, there was a dire need for devising machine learning algorithms for detecting Arabic terrorism messages. The innovative aspect of the model presented in the current study is that the five best classifiers were selected and applied on three language models S1, S2, and S3. The comparative analysis based on classification accuracy and time constraints proposed the best classifiers for sentiment analysis in the Arabic language.

Античные и средневековые авторы об укреплениях городов Азербайджана

The city is distinguished by a special way of life, the specifics of political, economic, socio-cultural and intellectual activities, worldview of various segments of the population. Questions about the emergence of cities, the formation of urban culture, the city-forming role of economic, socio-political, cultural processes in society are topical issues of historical science. When researching most of the questions on the history of ancient cities, the method of analyzing written sources is of particular importance. The reports of ancient and medieval authors contain valuable information about the country's natural resources, routes of communication, trade relations, political events, as well as about cities and the distance between them, about their social structure, planning, fortifications, etc. The available written sources in different languages testify that Azerbaijan has long been the center of a highly developed urban culture. They contain important information about the fortified Azerbaijani cities, which were mainly located on the main trade routes, in strategically reliable areas, climatically favorable regions of the country. The defense of cities was a permanent and decisive factor. The fortifications of the cities met all the necessary requirements of their time. The powerful defensive system of cities, including several belts of fortress walls with towers of various shapes, detached observation and signal towers and castles, reliably resisted massive attacks, throwing weapons and battering machines, both during a swift assault and a long siege, as evidenced by written sources. The article briefly analyzes the reports of ancient and medieval authors about fortifications in the system of protection of the historical cities of Azerbaijan.

Novelty Messages Filtering for Multi Agent Privacy-Preserving Plannin

In multi-agent planning, agents jointly compute a plan that achieves mutual goals, keeping certain information private to the individual agents. Agents' coordination is achieved through the transmission of messages, but they can be a source of privacy leakage as they can permit a malicious agent to collect information about other agents' search processes and states. In this paper, we investigate the usage of novelty techniques in the context of (decentralised) multi-agent privacy preserving planning, addressing the challenges related to the agents' privacy and performance. In particular, we show that novelty based techniques allow a significant reduction on the number of messages transmitted among agents, increasing their privacy levels and also their performances. An experimental study analyses the effectiveness of our techniques and compares them with the state of-the-art. Finally, we examine the robustness of our approach considering different delays in the messages transmission as would occur in overloaded networks, due for example to massive attacks or critical situations.

"Among the troops he chose brave warriors, who were battling through ranks...". On Some Peculiar Aspects of Amir Timur's Tactical Art

This article revises the peculiarities of Amir Timur's army tactical peculiarities, as well as their influence on the development of martial art of the Muslim East. It is established that Timur effectively used the mobilization potential of his state. The sedentary population of Chorasa and Transoxiana formed the infantry archery units who were taught to fight under cover of large standing shields - chapars. At the same time, loyal nomad tribes were the source of horse cavalry for the Timur's army. The base of battle formation was represented by a tactical "skeleton" formed of forced kanbuls, powerful advance guard and a reserve (that included elite warriors). Such battle formation allowed Timur to effectively face outflanking and frontal attacks of the enemy. Besides, such battle formation also fit for quick shift from defense to massive counterattack, performed by advance guard and kanbuls projected towards the enemy. The vulnerability of weakened flank corps was partially compensated by using infantry archery units with support of dismounted archers. As a rule, massive archery attack stopped the enemy's attack and provided for counterattack. The organizational and tactical autonomy of kul corps, which could embattle independently even if there was a front breakthrough or encirclement, played an important role. Dismounted, enshielded warriors of the corps could repulse the attacks until the deblocking unit approaches. A fast-moving reserve under Timur's personal command could be used for both repulsing an attack and augmenting the advancing troops.