Localized Attack Research Articles

Corrosion behaviour of Ni and nickel aluminide coatings exposed in a biomass fired power plant for two years

Ni and Ni2Al3 coatings were applied to superheater tubes that were built into a wood-fired boiler with an outlet steam temperature of 520 °C. The present paper evaluates the performance of the coatings after two years of service. The corrosion performance of the coatings is discussed with respect to the temperature histograms and deposit composition and compared to the performance of the coatings after the first year. The Ni coatings showed extremely protective behaviour for 1 year however after 2 years exposure, the Ni coating was chemically attacked, thick NiO was formed and sulphur containing precipitates were present at the base of the Ni layer indicating grain boundary ingress of corrosive species. For the Ni2Al3 coatings, localized attack was observed after the first year of exposure, but after two years no intact nickel aluminide coatings were observed.

On connectivity of post-earthquake road networks

This paper proposes a novel stochastic mathematical framework to investigate the connectivity of road networks impacted by earthquakes. The concepts of “global connectivity” and “local connectivity” are defined and evaluated using percolation theory. Specifically, global connectivity measures the extent to which the whole network is connected, and local connectivity measures the distances between each node to its neighbors. Furthermore, the concept of efficiency is employed to integrate local connectivity. A new percolation process integrating the traditional localized attack and random failure is proposed, which sheds light on the application of percolation theory to practical networks when facing disruptions.

Differential mobility and local variation in infection attack rate.

Infectious disease transmission is an inherently spatial process in which a host’s home location and their social mixing patterns are important, with the mixing of infectious individuals often different to that of susceptible individuals. Although incidence data for humans have traditionally been aggregated into low-resolution data sets, modern representative surveillance systems such as electronic hospital records generate high volume case data with precise home locations. Here, we use a gridded spatial transmission model of arbitrary resolution to investigate the theoretical relationship between population density, differential population movement and local variability in incidence. We show analytically that a uniform local attack rate is typically only possible for individual pixels in the grid if susceptible and infectious individuals move in the same way. Using a population in Guangdong, China, for which a robust quantitative description of movement is available (a travel kernel), and a natural history consistent with pandemic influenza; we show that local cumulative incidence is positively correlated with population density when susceptible individuals are more connected in space than infectious individuals. Conversely, under the less intuitively likely scenario, when infectious individuals are more connected, local cumulative incidence is negatively correlated with population density. The strength and direction of correlation changes sign for other kernel parameter values. We show that simulation models in which it is assumed implicitly that only infectious individuals move are assuming a slightly unusual specific correlation between population density and attack rate. However, we also show that this potential structural bias can be corrected by using the appropriate non-isotropic kernel that maps infectious-only code onto the isotropic dual-mobility kernel. These results describe a precise relationship between the spatio-social mixing of infectious and susceptible individuals and local variability in attack rates. More generally, these results suggest a genuine risk that mechanistic models of high-resolution attack rate data may reach spurious conclusions if the precise implications of spatial force-of-infection assumptions are not first fully characterized, prior to models being fit to data.

Monitoring localized corrosion of Inconel 82 weld overlay on 304L SS weld by electrochemical noise

The manuscript presents the results from the electrochemical noise (EN) monitoring of Inconel 82 weld overlay on Type 304L stainless steel (SS) weld in 0.01M FeCl3. The microstructure of the weld overlay obtained from optical and scanning electron microscopy (SEM) showed an austenite structure, containing equiaxed dendrites and secondary phases at the interdendritic region. Energy dispersive spectroscopy (EDS) attached to SEM revealed the secondary phases to be Nb rich Laves phase. The electrochemical potential noise was monitored using a three identical electrode configuration. The acquired signals were detrended, and wavelet analysis was employed to encode useful information from the noise transients. Visual examination of the potential noise-time record contained distinct high amplitude transients typical of localized corrosion attack. The energy distribution plots (EDP) of the potential noise derived from wavelet analysis depicted maximum relative energy on D6-D8 crystals, which represent large time scale events such as those occurring from localized attacks. Also, repassivation events too could be divulged from the potential EDP. The micrographs of the post electrochemical noise experimented specimens revealed the occurrence of localized attacks along the interdendritic region and none inside the dendritic cores. The presence of secondary phases along the interdendritic regions was found to be detrimental in chloride medium, imparting inferior localized corrosion resistance to the weld overlay.

Localized attack on networks with clustering

Network systems with clustering have been given much attention due to their wide occurrence in the real world. One focus of these studies has been on robustness of single clustered networks and interdependent clustered networks under random attack (RA) or hub-targeted attack. However, infrastructure networks could suffer from a damage that is localized, i.e. a group of neighboring nodes attacked or fail, a topic that was not studied earlier on clustered networks. In this paper, we analytically and via simulations study the robustness under localized attack (LA) of single Erdős–Rényi clustered network and interdependent clustered network. For generating networks with clustering we use two models: (i) double Poisson distribution (DPD) and (ii) fixed degree distribution (FDD). For the LA case, the DPD model shows a second order phase transition behavior for a single clustered network, while for dependent networks, the system undergoes a change of percolation phase transition from a first order (abrupt transition) to a second order (continuous) transition when the coupling strength q decreases below a critical value qc. Our results imply that single networks become significantly more vulnerable with increasing clustering coefficient c with respect to LA. This is in contrast to RA where the robustness is almost independent of c. We obtain similar results when testing different real networks. For LA on dependent networks, we also observe that the system becomes more vulnerable as c increases. This is again in contrast to RA, where for, q < qc, the system robustness is almost unaffected by increasing clustering. We also solved analytically the case of LA on random regular networks which are clustered and interdependent and find that as m (the number of clustered networks that each network depends on) or c increases, the system becomes significantly more vulnerable. We also analyzed via simulations the case of generating clustering in networks for the model of keeping a FDD, and find that the influence of clustering on the robustness of two partially interdependent networks under LA is smaller than for DPD, which is very different from these cases under RA.

The Effective Healing Strategy against Localized Attacks on Interdependent Spatially Embedded Networks

Many real‐world infrastructure networks, such as power grids and communication networks, always depend on each other by their functional components that share geographic proximity. A lot of works were devoted to revealing the vulnerability of interdependent spatially embedded networks (ISENs) when facing node failures and showed that the ISENs are susceptible to geographically localized attacks caused by natural disasters or terrorist attacks. How to take emergency methods to prevent large scale of cascading failures on interdependent infrastructures is a longstanding problem. Here, we propose an effective strategy for the healing of local structures using the connection profile of a failed node, called the healing strategy by prioritizing minimum degrees (HPMD), in which a new link between two active low‐degree neighbors of a failed node is established during the cascading process. Afterwards, comparisons are made between HPMD and three healing strategies based on three metrics: random choice, degree centrality, and local centrality, respectively. Simulations are performed on the ISENs composed of two diluted square lattices with the same size under localized attacks. Results show that HPMD can significantly improve the robustness of the system by enhancing the connectivity of low‐degree nodes, which prevent the diffusion of failures from low‐degree nodes to moderate‐degree nodes. In particular, HPMD can outperform other three strategies in the size of the giant component of networks, critical attack radius, and the number of iterative cascade steps for a given quota of newly added links, which means HPMD is more effective, more timely, and less costly. The high performance of HPMD indicates low‐degree nodes should be placed on the top priority for effective healing to resist the cascading of failures in the ISENs, which is totally different from the traditional methods that usually take high‐degree nodes as critical nodes in a single network. Furthermore, HPMD considers the distance between a pair of nodes to control the variation in the network structures, which is more applicable to spatial networks than previous methods.

The Effect of Microstructural Refinement on the Localized Corrosion of Model Zn-Al-Mg Alloy Coatings on Steel

A combination of in-situ Scanning Vibrating Electrode Technique (SVET) and time-lapse immersion optical microscopy (TLM) is used to investigate the effect of microstructural refinement on patterns of localized corrosion affecting zinc-aluminum-magnesium (ZAM) galvanized coatings on steel. Model ZAM coatings comprising Zn-2.7 wt% Al-1.5 wt% Mg are produced on 0.7 mm mild steel sheet by hot dipping, and the resulting coating microstructure is systematically refined by increasing the cooling (solidification) rate from 5°C.sec−1 to 1000°C.sec−1. The intact ZAM coated surface is immersed in 0.17 M aqueous NaCl, and SVET and TLM are used to follow the resulting localized corrosive attack. TLM shows that corrosion initiates preferentially within MgZn2 and spreads laterally over the ZAM surface by preferentially following MgZn2 rich phases. In coarse microstructures, large primary zinc grains tend to deflect and constrain lateral spreading whereas in fine microstructures the smaller primary zinc grains do not. Consequently, lateral spreading rate increases with microstructural refinement. SVET shows that global corrosion rates are similar for all the ZAM coatings but that increased lateral spreading results in lower rates of through-coating penetration for the refined microstructures. These findings are explained in terms of the lateral diffusion of aggressive anolyte species.

Optimizing the Plasma Arc Welding Process Parameters to Attain the Minimum Corrosion Rate in the AISI 409M grade Ferritic Stainless Steel Autogenous Joints

Abstract The combination with good mechanical properties and manufacturing characteristics, makes stainless steel an indispensable tool for the designer. Stainless steels become susceptible to localized intergranular corrosion when chromium carbides form at the grain boundaries during high temperature exposure. This depletion of chromium at the grain boundaries is termed ‘sensitization’, because the alloys become more sensitive to localized attack in corrosive environments. Stainless steels like AISI 409M grade, which are having low chromium content (approximately 11%), are susceptible to localized corrosion. The susceptibility of these alloys are strongly affected by welding processes and filler metals, which change the microstructure of the alloy in order to have optimum mechanical properties. Hence, the present investigation has been carried out to understand the effect of Plasma Arc Welding (PAW) process on pitting corrosion behavior of AISI 409M grade stainless steel joints. Also, the PAW process parameter such as welding speed, voltage, heat input were optimized with help of Response Surface Methodology (RSM) to attain the maximum tensile strength and minimum corrosion rate in the welded joints.

Percolation on random networks with proliferation

The literature on growing network models, exemplified by the preferential attachment model and the copying model, has followed an exponential growth in the last few years. In many real-life scenarios, however, the adding of new nodes and edges is not an exogenous process, but involves inheritance and sharing of the local environment of the existing ones. In this paper, we develop a mathematical framework to analytically and numerically study the percolation properties of the random networks with proliferation. We compare random attack (RA) and localized attack (LA) on benchmark models, including Erdős–Rényi (ER) networks, random regular (RR) networks, and scale-free (SF) networks, with proliferation mechanism. Our results highlight the nonmonotonic connections with robustness and growth, and unravel an intriguing opposite effect for RA and LA. In particular, it is shown that unbalanced proliferation enhances robustness to RA while it mitigates robustness to LA, both independent of the network degree distribution.

Sensitization of an austenitic stainless steel due to the occurrence of δ-ferrite

Abstract A series of analyses were conducted on samples of an austenitic type 304 stainless steel that exhibited a high degree of sensitization (DOS) after being subjected to a solution annealing treatment at 1050°C. The DOS was detected by electrochemical potentiokinetic tests. Examination by scanning electron microscopy of etched samples revealed the presence of δ-ferrite within the austenitic matrix, and of the segregation of chromium and nickel in either phase; images obtained by atomic force microscopy revealed localized attack at the austenite/δ-ferrite interface. It was found that the DOS and the ferrite number of the steel were reduced as the material was held at the solution temperature for longer times. Aging at 650°C showed precipitation of chromium carbides at grain boundaries and at the austenite/δ-ferrite interface; this treatment increased the DOS.

РАСПРЕДЕЛЕННАЯ СИСТЕМА СБОРА, ОБРАБОТКИ И АНАЛИЗА СОБЫТИЙ ИНФОРМАЦИОННОЙ БЕЗОПАСНОСТИ СЕТЕВОЙ ИНФРАСТРУКТУРЫ ПРЕДПРИЯТИЯ

The majority of the network infrastructures of government agencies and private enterprises operate on the basis of a TCP/IP protocol stack, which has significant vulnerabilities. For illustrative purposes, it is worth mentioning the lack of verification of the interaction subject authenticity in the basic protocols and technologies of this stack. Some of the TCP/IP stack vulnerabilities can be eliminated by the intelligent functions of managed network devices: from access profiling to traffic segmentation. Complex firewalls, which include intrusion detection and prevention systems, are also an important element of the network protection. Methods of signature, heuristic, behavioral, self-similar, predictable and other approaches for analyzing network traffic and identifying network threats are further being developed by Russian and foreign scientists. However, the proposed solutions do not give an unambiguous result when using overlay technologies and cryptographic protocols. Also, due attention is not being paid to the processing, analysis of network traffic and logs of Windows/Linux operating systems and applications. The aim of this work was the research, development and software implementation of a distributed system for collecting, processing and analyzing security information events of an enterprise network infrastructure. The key task was to ensure objective monitoring of network information security. An additional task was to ensure the monitoring of the activity of users of personal computers running Windows and Linux operating systems. In order to address this challenge, a concept for complex processing of computer network traffic and security information events both on the server and on the client sides was developed. An original signature and statistical method of compiling the knowledge base system by testing and simulating known network and local attacks with tracking the response of operating systems and applications in a virtualization environment is reviewed. The approach to performing the automated analysis of correlating events with the use of deep packets inspection (DPI) and monitoring of users' local activity is described. The reviewed solution was successfully tested and used as one of the modules for providing network information security of the system for intelligent adaptive enterprise network infrastructure management, designed by author.

Understanding the effect of the reinforcement addition on corrosion behavior of Fe/Mg2Si composites for biodegradable implant applications

Abstract Iron-based materials showed a high potential for degradable biomaterial applications. However, their slow corrosion rate limits their use as a biodegradable implant material. One approach to control and modify their mechanical properties is the use of reinforcement particles, to create metal matrix composites in which the second phase is aimed at tuning not only the mechanical properties but also the corrosion mode and rate in a physiological environment. Here, Fe/Mg2Si composites were produced via powder metallurgy from pure Fe and Mg2Si powders. The different conditions were fabricated by various combinations of milling or mixing processes followed by hot rolling consolidation. The effect of the Mg2Si addition on corrosion behavior of Fe/Mg2Si composites was studied by performing cyclic polarization and static corrosion tests for an immersion time of 24 and 240 h. The presence of the reinforcement particles played a crucial role in the susceptibility of Fe-based composites to localized corrosion attack. The corrosion initiation and its development were systematically monitored. Scanning electron microscopy, X-ray diffraction, and atomic emission spectroscopy were employed to investigate the corrosion mechanism. The importance of Mg2Si particles in the triggering of corrosion processes was explained. Electrochemical measurements and static immersion tests implied that the introduction of Mg2Si particles could accelerate the corrosion rate of Fe. It was confirmed that the size and distribution of the reinforcement influenced considerably the uniformity of the corrosion attack.

Guilt by Association: The Effects of Terrorism on Corporate Activity

We study the link between a previously neglected form of intangible asset—country reputation—and corporate sales. By exploiting variation in nationalities of foreign victims in local terror attacks, we detect unanticipated distortions in reputations of local countries in foreign countries and we pin down reductions in sales of local country firms in foreign markets. The reductions in sales are economically and statistically significant, persistent, and more pronounced after attacks with high levels of foreign media coverage. Local country firms, whose names resemble names from their countries of origin, experience greater deteriorations in their sales. The distortions in country reputations are associated with depreciations in overall firm value, asset growth, and profitability.

The effect of nitrogen saturation on the corrosion behaviour of Ti-35Nb-7Zr-5Ta beta titanium alloy nitrided by ion implantation

Corrosion behaviour of Ti-35Nb-7Zr-5Ta β titanium alloy nitrided by ion implantation was examined. Nitrogen ions were implanted with different fluences in the range from 1·1017 to 9·1017 cm−2 and an accelerating voltage of 90 kV. The specific effects of the nitrogen fluence on structural changes of the implantation zone showed the relationship between nitrogen concentration, nitride formation and corrosion behaviour. Nitrogen depth profiles measured by glow discharge optical emission spectroscopy showed the saturation limit approx. 60 at.% leading to the exo-diffusion of nitrogen. X-ray photoelectron spectroscopy indicated increasing formation of surface nitrides with the fluence of implanted nitrogen, up to the saturation fluence of 4 · 1017 cm−2. Oversaturation induced a decrease in nitrogen concentration, accompanied by a reduction in the amount of surface nitrides, and accompanied by blistering. The corrosion tests in physiological saline solution show high resistance of the implanted surfaces to corrosion attack. The corrosion resistance increased with increasing fluence up to saturation fluence. Fluences higher than saturation one caused decrease of the corrosion resistance to the level of lower fluences. All nitrogen implanted surfaces showed higher resistance than non-implanted surface. The surface nitriding has no influence on the susceptibility to the localized corrosion attack. The formation of surface nitrides and their concentration, rather than the defects of an oversaturated surface, affect the corrosion behaviour.

Numerical study on influence of structural vibration on cavitating flow around axisymmetric slender body

The unsteady behaviors of cloud cavitating flow would lead to structural vibration and deformation that conversely affect its development. The present paper aims to preliminarily discuss the influences of structural vibration on the development of the cavitating flow. Simulations of a slender body are carried out under different vibration amplitudes and frequencies. The results show that the structural vibration causes alternate variation of local attack angle at the head of the body, and thus changes the development of cavitation and re-entrant jet. On the downstream side, the length and thickness of the cavity are larger than that on the upstream side due to larger area of negative pressure. For a large vibration amplitude, alternate variations of the local attack angle change the adverse pressure gradient at the closure of the cavity, and then affect the development of the re-entrant jet, so that the phenomena of local shedding of the cavitation happen, compared with global shedding in the case of no structural vibration. For a frequency larger than 0.05, transverse speed of the vibration is suggested to be a dominant factor in controlling the behavior of the cavitating flow besides the local attack angle, since it causes local cavitating phenomena.

Study of Chloride Corrosion Organic Inhibitors in Alkaline Pore Solution

This paper compares the inhibition properties of aspartic and lactic acid salts with nitrite ions and their effect on critical chloride concentration. The tests were carried employing carbon steel specimens in saturated lime solution with varying pH in the range between13 to 13.6. The critical chloride concentration was estimated through multiple specimen potentiostatic tests at potentials in the usual range for passive rebar in the alkaline concrete of atmospheric structures. During tests, chloride salt was added every 48 h until all the specimens showed localized attacks. The cumulative distribution curves, i.e. the number of corroded specimens as a function of the chlorides concentration was obtained. Furthermore, IR spectra were recorded for the evaluation of the presence of the organic inhibitors on the passivity film. The results confirmed the inhibitory effect of 0.1M aspartate comparable with nitrite ions, at a similar concentration. Addition of calcium lactate did not result in an increase in the critical chloride concentration. However, the formation of a massive scale containing the substance that could reduce the corrosion propagation was observed.

Subgraph Robustness of Complex Networks Under Attacks

Network measures derived from empirical observations are often poor estimators of the true structure of system as it is impossible to observe all components and all interactions in many real world complex systems. Here, we study attack robustness of complex networks with data missing caused by: 1) a uniform random sampling and 2) a nonuniform random sampling. By introducing the subgraph robustness problem, we develop analytically a framework to investigate robustness properties of the two types of subgraphs under random attacks, localized attacks, and targeted attacks. Interestingly, we find that the benchmark models, such as Erdős-Renyi graphs, random regular networks, and scale-free networks possess distinct characteristic subgraph robustness features. We show that the network robustness depends on several factors including network topology, attack mode, sampling method and the amount of data missing, generalizing some well-known robustness principles of complex networks. Our results offer insight into the structural effect of missing data in networks and highlight the significance of understanding different sampling processes and their consequences on attack robustness, which may be instrumental in designing robust systems.

Crowdsourcing Analysis in 5G IoT: Cybersecurity Threats and Mitigation

Crowdsourcing can be a powerful weapon against cyberattacks in 5G networks. In this paper we analyse this idea in detail, starting with the use cases in crowdsourcing focused on security, and highlighting those areas of a 5G ecosystem where crowdsourcing could be used to mitigate local and remote attacks, as well as to discourage criminal activities and cybercriminal behaviour. We pay particular attention to the capillary network, where an infinite number of IoT objects coexist. The analysis considers the different participants in a 5G IoT ecosystem.

To Hide Private Position Information in Localization Using Time Difference of Arrival

In most existing localization schemes, location information leakage is inevitable, since both the locations of the target and the anchors will be revealed to the entity that conducts location estimation. A malicious entity may destroy the localization infrastructure or attack the target or anchors based on the revealed locations. Therefore, location privacy preservation in localization is of great significance. This paper investigates the privacy preservation problem in localization using time difference of arrival (TDOA) under the assumptions of safe internode communication and an honest-but-curious model. Adopting the privacy-preserving summation method, we propose two privacy-preserving localization protocols for two scenarios, where the TDOA measurements are, respectively, obtained by the target and the anchors. The proposed protocols do not utilize any encryption method, and can hide the locations of both the target and the anchors by limiting the available information to other nodes. The localization performance, sufficient conditions for privacy preservation, and computation and communication complexities of the proposed protocols are theoretically analyzed. Through simulation and numerical results, we show that the proposed protocols can implement location privacy preservation without degrading the localization performance.

Tracking corroding chloride

Metallurgy![Figure][1] Chloride ions attack passive films on metal surfaces and cause corrosion. PHOTO: RHONDA GUTENBERG/GETTY IMAGES Corrosion is a major problem for metals, reducing their performance and shortening their lifetimes. Passive films that form on metal surfaces can help provide corrosion resistance but are also susceptible to localized attack. Zhang et al. used transmission electron microscopy to take a detailed look at chloride attack on the passive films of an iron-chromium-nickel alloy. This direct visualization of chlorideion transport allows for a much better understanding of how these ions modify the surface layer of metals and deeper insight into the corrosion process. Nat. Commun. 10.1038/s41467-018-04942-x (2018). [1]: pending:yes