Chronic widespread pain (CWP), including fibromyalgia (FM), is characterized by generalized musculoskeletal pain and hyperalgesia. Plasma proteins from proteomics (non-targeted) and from targeted inflammatory panels (cytokines/chemokines) differentiate CWP/FM from controls. The importance of proteins obtained from these two sources, the protein-protein association network, and the biological processes involved were investigated. Plasma proteins from women with CWP (n = 15) and CON (n = 23) were analyzed using two-dimensional gel electrophoresis analysis and a multiplex proximity extension assay for analysis of cytokines/chemokines. Associations between the proteins and group were multivarietly analyzed. The protein-protein association network and the biological processes according to the Gene Ontology were investigated. Proteins from both sources were important for group differentiation; the majority from the two-dimensional gel electrophoresis analysis. 58 proteins significantly differentiated the two groups (R2 = 0.83). A significantly enriched network was found; biological processes were acute phase response, complement activation, and innate immune response. As with other studies, this study shows that plasma proteins can differentiate CWP from healthy subjects. Focusing on cytokines/chemokines is not sufficient to grasp the peripheral biological processes that maintain CWP/FM since our results show that other components of the immune and inflammation systems are also highly significant.

In this paper, we are going to verify the possibility to create a ransomware simulation that will use an arbitrary combination of known tactics and techniques to bypass an anti-malware defense. To verify this hypothesis, we conducted an experiment in which an agent was trained with the help of reinforcement learning to run the ransomware simulator in a way that can bypass anti-ransomware solution and encrypt the target files. The novelty of the proposed method lies in applying reinforcement learning to anti-ransomware testing that may help to identify weaknesses in the anti-ransomware defense and fix them before a real attack happens.

The paper presents the research of the stability of the system with a redundancy of communication channels. For this, two prototypes have been developed that are built (1) according to the classical circuit-switched scheme and (2) with an aggregation of several virtual channels. Prototyping, installation on various vehicles and measurements of the stability of the entire system as a whole were carried out. The paper also presents structural diagrams, hardware, and a list of problems and difficulties that the authors encountered during the practical implementation and implementation of these systems. In the future, it is planned to expand the study of these systems when working with high-level channel virtualization and the search for methods to accelerate its work.

In the last years, several attempts have been made to study specific biological markers of temporomandibular disorders (TMD). So far, no laboratory tests have been appropriately validated for the diagnosis and prognosis of these disorders. This study aimed to investigate the proteomic profile of the whole stimulated saliva of TMD myalgia patients in order to evaluate potential diagnostic and/or prognostic salivary candidate proteins which could be useful for the management of TMD. Twenty patients diagnosed with TMD myalgia according to the validated Diagnostic Criteria for TMD (DC/TMD) and 20 matched healthy pain-free controls were enrolled. Saliva samples were collected in the morning. Comparative proteomic analysis was performed with two-dimensional gel electrophoresis followed by identification with liquid chromatography–tandem mass spectrometry. Statistical analysis of the quantitative proteomics data revealed that 20 proteins were significantly altered in patients compared to controls. Among these proteins, 12 showed significantly increased levels, and 8 showed significantly decreased levels in patients with TMD myalgia compared to controls. The identified proteins are involved in metabolic processes, immune response, and stress response. This proteomic study shows that the salivary protein profile can discriminate patients with TMD myalgia from healthy subjects, but the protein signature has no correlation with the clinical features of TMD myalgia. Additional studies are needed to validate our observations in additional sample sets and to continue assessing the utility of saliva as a suitable sample for studying processes related to TMD myalgia.

The study aimed to investigate salivary levels of nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), substance P (SP) and glutamate at five time points from morning to afternoon in a well-characterised healthy and pain-free individuals. Ten young adults were included. Unstimulated and stimulated whole saliva were collected from each participant repeatedly across the day. Blood samples were drawn in connection with the first and last saliva sample as reference standard. Levels of NGF and BDNF were determined using gel-free Western blot technology, glutamate levels were analysed using a colorimetric assay, and SP was determined using a commercially available ELISA. Salivary NGF and BDNF showed significant differences between the different collection times in both unstimulated (NGF; P = .006; BDNF; P = .026) and stimulated whole saliva (NGF; P = .006; BDNF; P = .019). The highest concentrations of the neuropeptides were expressed in the early morning, and they thereafter decreased across the day. In contrast, the expression of salivary glutamate and SP did not show any significant changes across the day. Plasma levels of NGF were higher in the evening sample (P = .028); otherwise, there were no significant differences for any of the other markers between morning and evening samples. NGF and BDNF in whole saliva showed a significant variation across the day. On the contrary, no variation in the levels of SP and glutamate was detected. These findings highlight the importance of consistency in the collection time and approach in biomarker studies using saliva.

To meet the high demand of educating the next generation of MSc students in Cyber security, we propose a well-composed curriculum and a configurable cloud based learning support environment ReSeLa. The proposed system is a result of the EU TEMPUS project ENGENSEC and has been extensively validated and tested.

In this paper, a home automation system model was constructed with purpose to investigate of the correlation between the performance of wireless communication, power consumption of the constrained IoT devices and security. The series of experiments were conducted using sensor nodes connected to Arduino microcontroller and an RF 433 MHz wireless communication module. Measurements of the execution time and power consumption of the Arduino during data transfer with different security levels, as well as the analysis of the experimental results, were performed. The results show that the lifetime of the IoT device is determined by the communication speed, sleep mode management and depends on encryption. The obtained results can be used to minimize the power consumption of the device and improve communication efficiency. The results show that applied security reduces the productivity and lifetime of the sensor node not significantly.

Abstract. Introduction:. Proteomics is a powerful approach for biochemical research because it directly studies the main functional components of biochemical systems. The understanding of the normal fluctuations of the proteome in health is essential to identify pain-specific biomarkers. Objective:. To investigate fluctuations of the plasma proteome in healthy pain-free individuals. Methods:. Blood samples were structurally collected in the early morning and evening from 10 clinically healthy individuals (26.3 ± 3.3 years). High abundant proteins were removed from plasma, and proteins were then analysed by nanoliquid chromatography combined with mass spectrometry. In addition, an assay of 71 cytokines/chemokines/growth factors was analysed. Results:. Multivariate statistical analysis displayed that there were up to 64 proteins whose expression levels were significantly altered between the plasma samples collected during the morning and evening; no changes existed for the assay. The levels of 34 proteins were increased and 30 proteins were decreased during the evening compared with the morning sample. The increased proteins were involved in the biological processes such as protein activation cascade, complement activation, and stress response. The decreased proteins were involved in regulation of endopeptidase activity, inflammatory response, and protein metabolic processes. Conclusion:. The circadian variations in the plasma proteome stress the need to collect blood samples of both patients and controls at a fixed time of the day. The results in this study might be useful for better understanding of the complexity of individual variation in the human plasma proteome over time and provide a baseline for improved pain biomarker discovery.

This paper represents the approach for estimation of the lifetime of the IoT end devices. The novelty of this approach is in the taking into account not only the energy consumption for data transmission, but also for ensuring the security by using the encryption algorithms. The results of the study showed the effect of using data encryption during transmission on the device lifetime depending on the key length and the principles of the algorithm used.

This paper contains an analysis of the LockerGoga ransomware that was used in the range of targeted cyberattacks in the first half of 2019 against Norsk Hydra - a world top 5 aluminum manufacturer, as well as the US chemical enterprises Hexion, and Momentive - those companies are only the tip of the iceberg that reported the attack to the public. The ransomware was executed by attackers from inside a corporate network to encrypt the data on enterprise servers and, thus, taking down the information control systems. The intruders asked for a ransom to release a master key and decryption tool that can be used to decrypt the affected files. The purpose of the analysis is to find out tactics and techniques used by the LockerGoga ransomware during the cryptolocker attack as well as an encryption model to answer the question if the encrypted files can be decrypted with or without paying a ransom. The scientific novelty of the paper lies in an analysis methodology that is based on various reverse engineering techniques such as multi-process debugging and using open source code of a cryptographic library to find out a ransomware encryption model.

The paper explores methods for assessing vulnerabilities and assessing the spread of an attack in an infocommunication network. A proactive approach to the quantitative assessment of network security, which allows us to assess risks at the user and network level through the presence of vulnerabilities is presented. The proposed solutions will be useful for decision making and will be further integrated into a single metric for displaying the integrated level of security of the infocommunication network.

Saliva is often neglected as a body fluid of diagnostic or prognostic value, even though generally well accepted by the patients. This is due to lack of a standardized collection procedure. The aim of this study was to identify the ideal saliva collection technique and develop new sensitive methods to detect and analyse markers related to pain in healthy pain-free subjects. Plasma and five different saliva collection approached was evaluated during strictly controlled conditions. Levels of nerve growth factor (NGF), calcitonin gene-related peptide (CGRP) and brain derived neurotropic factor (BDNF) were determined using novel western blotting based technology. Glutamate and substance P (SP) was determined using commercial available methods. Several new isoforms were found for NGF, CGRP and BDNF in saliva. The isoform pattern showed significant variation in both expression and chemiluminescence levels between different collection methods. New sensitive methods to study pain related markers in saliva were developed in this study. Furthermore, we are first to demonstrate a correlation between the Glutamate concentration in stimulated whole saliva and blood. However, the fundamental conclusion drawn is the importance of consistency in the collection method.

This paper represents new functional architecture for the Internet of Things systems that use an avatar concept in displaying interaction between components of the architecture. Object-oriented representation of "thing" in the avatar concept allows simplify building and deployment of IoT systems over the web network and bind "things" to such application protocols as HTTP, CoAP, and WebSockets mechanism. The assets and stakeholders for ensuring security in IoT were specified. These assets are needed to isolate the risks associated with each of assets of IoT system. Example of Thing Instance's description and its functionality using JSON format is shown also in the paper.

Low power wide area (LPWA) technologies becomes popular for IoT use cases because LPWA is enable the broad range communications and allows to transmit small amounts of information in a long distance. Among LPWA technologies there are LTE-M, SigFox, LoRa, Symphony Link, Ingenu RPMA, Weightless, and NB-IoT. Currently all these technologies suffer from lack of documentation about deployment recommendation, have non-investigated limitations that can affect implementations and products using such technologies. This paper is focused on the testing of LPWAN LoRa technology to learn how a LoRa network gets affected by different environmental attributes such as distance, height and surrounding area by measuring the signal strength, signal to noise ratio and any resulting packet loss. The series of experiments for various use cases are conducted using a fully deployed LoRa network made up of a gateway and sensor available through the public network. The results will show the LoRa network limitation for such use cases as forest, city, open space. These results allow to give the recommendation for companies during early analysis and design stages of network life circle, and help to choose properly technology for deployment an IoT application.

This article considers a short survey of basic methods of social networks analysis, which are used for detecting cyber threats. The main types of social network threats are presented. Basic methods of graph theory and data mining, that deals with social networks analysis are described. Typical security tasks of social network analysis, such as community detection in network, detection of leaders in communities, detection experts in networks, clustering text information and others are considered.

In the rapidly growing Internet of Things (IoT) applications from personal electronics to industrial machines and sensors are getting wirelessly connected to the Internet. Many well-known communication technologies such as WiFi, ZigBee, Bluetooth and cellular are used for transfer data in IoT. The choice of corresponding technology or combination of technologies depends on application or other factors such as data requirements, communication range, security and power demands, battery life.In this paper we will focuse on ZigBee wireless technology and testing ZigBee end devices in order to see how transmission range impacts on quality parameters.

The paper introduces a new scheme of dynamic interference free channel allocation. The scheme is based on additional spectral analyzers in wireless networks IEEE 802.11. Design and implementation is presented.

This paper contains an analysis of the payload of the popular ransomware for Windows, Android, Linux, and MacOSX platforms. Namely, VaultCrypt (CrypVault), TeslaCrypt, NanoLocker, Trojan-Ransom.Linux.Cryptor, Android Simplelocker, OSX/KeRanger-A, WannaCry, Petya, NotPetya, Cerber, Spora, Serpent ransomware were put under the microscope. A set of characteristics was proposed to be used for the analysis. The purpose of the analysis is generalization of the collected data that describes behavior and design trends of modern ransomware. The objective is to suggest ransomware threat mitigation techniques based on the obtained information. The novelty of the paper is the analysis methodology based on the chosen set of 13 key characteristics that helps to determine similarities and differences thorough the list of ransomware put under analysis. Most of the ransomware samples presented were manually analyzed by the authors eliminating contradictions in descriptions of ransomware behavior published by different malware research laboratories through verification of the payload of the latest versions of ransomware.

The paper focus on cyber weapons used in Advanced Persistent Threat (ATP) attacks in present and future cyber warfare. The combined use of propaganda and cyber warfare supports military operations on the ground and is exemplified with the ongoing Russian hybrid warfare in Ukraine. New models and methods to develop future trustworthy critical infrastructures in our societies are presented. Some mitigation ideas to meet the challenges of future hybrid warfare are also discussed.

Chronic widespread pain (CWP) is a complex pain condition that is difficult to treat. The prevalence of CWP approximates ~10% of the general population, with higher prevalence in women. Lack of understanding of molecular mechanisms has been a challenge for diagnosis and treatment of chronic pain. The aim of this study was to explore the systemic protein changes in CWP compared to those in healthy controls (CON). By applying 2-dimensional gel electrophoresis, we analyzed the protein pattern of plasma samples from women with CWP (n=16) and healthy women (n=23). The proteomic data were analyzed using multivariate statistical models, and altered proteins were identified using mass spectrometry. The proteome analysis was further validated by gel-free Western blot. Multivariate statistical data analysis of quantified proteins revealed 22 altered proteins in women with CWP, compared to CON group. Many of the identified proteins are previously known to be involved in different parts of the complement system and metabolic and inflammatory processes, e.g., complement factor B, vitamin D-binding protein, ceruloplasmin, transthyretin and alpha-2-HS-glycoprotein. These results indicate that important systemic protein differences exist between women with CWP and healthy women. Further, this study illustrates the potential use of proteomics to detect biomarkers that may provide new insights into the molecular mechanism(s) of chronic pain. However, further larger investigations are required in order to confirm these findings before it will be possible to identify proteins as potential pain biomarkers for clinical use.