Attack Strength Research Articles

Can Caffeine Intake Improve Neuromuscular and Technical-Tactical Performance During Judo Matches?

Athayde, MSdS, Lima Kons, R, and Detanico, D. Can caffeine intake improve neuromuscular and technical-tactical performance during judo matches? J Strength Cond Res 32(11): 3095-3102, 2018-This study aimed to verify the effect of caffeine intake on blood lactate concentrations and neuromuscular and technical-tactical performance during simulated judo matches. Fourteen male judo athletes received capsules containing caffeine or placebo and were evaluated in both conditions. Before the baseline and 1 hour after the caffeine/placebo intake, athletes performed the countermovement jump (CMJ) test, handgrip strength, judogi grip strength test (JGST), and blood samples were collected. Subsequently, the athletes were submitted to three 5-minute matches with 15-minute intervals. All neuromuscular tests were performed and blood samples were taken during the matches' intervals. Significant interaction between condition and time (p = 0.01) was found for blood lactate concentrations. No interaction between condition and time was verified for CMJ performance (p > 0.05), handgrip strength (p > 0.05), JGST performance (p = 0.32), and number of attacks (p = 0.97). However, for all variables, a significant decrease was observed throughout time (p ≤ 0.05). According to clinical results (magnitude-based inference), we identified that post-match 2 and post-match 3 showed higher effect (most likely positive effect) regarding delta caffeine-placebo than other moments (pre-match and post-match 1) for blood lactate. Caffeine increased the estimated glycolytic contribution over the matches; however, it did not induce improvements in neuromuscular performance or number of attacks.

Attack-Aware Defense Strategy: A Robust Cooperative Spectrum Sensing in Cognitive Radio Sensor Networks

Cognitive radio (CR) is a key enabling technology of dynamic spectrum access to achieve better utilization of frequency spectrum. Cooperative spectrum sensing (CSS) exploits the spatial diversity between CR users to improve the accuracy of spectrum sensing. But, in practice, the reliability of the CSS is vulnerable to spectrum sensing data falsification (SSDF) attack. In this type of attack, some malicious CR sensors intentionally report falsified local sensing results to a fusion center and disrupt the global decision-making process. In this study, we present a smart and robust defense scheme called attack-aware CSS (ACSS). The idea is based on the estimation of attack strength where the attack strength corresponds to the attack population. The attack strength is defined as the ratio of the number of malicious sensors to the total number of sensors which is equal to the probability that a specific sensor is malicious. Assuming the malicious sensor behavior or attack strategy, the proposed approach estimates attack strength and uses the Bayesian hypothesis test to improve the collaborative sensing performance. Computer simulation results illustrate the effectiveness of the proposed ACSS approach against SSDF attacks, especially for CR networks located in hostile environments.

Dynamic Threshold Selection Approach in Voting Rule for Detection of Primary User Emulation Attack

DOI: 10.5152/iujeee.2018.1819 Cognitive radio (CR) technology presents a mechanism for efficient spectrum usage. Spectrum sensing is an essential CR function which includes an intelligent signal processing algorithm to identify the vacant frequency bands. Cooperative spectrum sensing (CSS) has been widely adopted to improve the performance of CR networks. Unfortunately, CR networks are vulnerable to security threats. In this study, we propose an optimal threshold selection approach to address one of the most important attacks called primary user emulation attack (PUEA). In PUEA, a malicious attacker mimics some important primary signal features and deceives CR sensors to prevent them from accessing the available channels. In this study, we assume a malicious PUEA which is relatively located near the potential user (PU) transmitter and senses the spectrum and accurately detects the vacant frequency bands to transmit its fake signal. We estimate attack strength and then apply the K-out-of-N rule to obtain an optimum and dynamic threshold K, minimizing the global error probability. Here, the attack strength is defined as the ratio of the average transmission power of the PUEA to the average power of the PU. The achieved simulation results indicate that the performance of the suggested method is satisfactory in detecting the malicious PUEA compared with conventional methods.

Network overload due to massive attacks.

We study the cascading failure of networks due to overload, using the betweenness centrality of a node as the measure of its load following the Motter and Lai model. We study the fraction of survived nodes at the end of the cascade p_{f} as a function of the strength of the initial attack, measured by the fraction of nodes p that survive the initial attack for different values of tolerance α in random regular and Erdös-Renyi graphs. We find the existence of a first-order phase-transition line p_{t}(α) on a p-α plane, such that if p<p_{t}, the cascade of failures leads to a very small fraction of survived nodes p_{f} and the giant component of the network disappears, while for p>p_{t},p_{f} is large and the giant component of the network is still present. Exactly at p_{t}, the function p_{f}(p) undergoes a first-order discontinuity. We find that the line p_{t}(α) ends at a critical point (p_{c},α_{c}), in which the cascading failures are replaced by a second-order percolation transition. We find analytically the average betweenness of nodes with different degrees before and after the initial attack, we investigate their roles in the cascading failures, and we find a lower bound for p_{t}(α). We also study the difference between localized and random attacks.

Bacteria Use Collective Behavior to Generate Diverse Combat Strategies

Animals have evolved a wide diversity of aggressive behavior often based upon the careful monitoring ofother individuals. Bacteria are also capable of aggression, with many species using toxins to kill or inhibit their competitors. Like animals, bacteria also have systems to monitor others during antagonistic encounters, but how this translates into behavior remains poorly understood. Here, we use colonies of Escherichia coli carrying colicin-encoding plasmids as a model for studying antagonistic behavior. We show that in the absence of threat, dispersed cells with low reproductive value produce colicin toxins spontaneously, generating efficient pre-emptive attacks. Cells can also respond conditionally to toxins released by clonemates via autoinduction orother genotypes via competition sensing. The strength of both pre-emptive and responsive attacks varies widely between strains. We demonstrate that this variability occurs easily through mutation by rationally engineering strains to recapitulate the diversity in naturally occurring strategies. Finally, we discover that strains that can detect both competitors and clonemates are capable of massive coordinated attacks on competing colonies. This collective behavior protects established colonies from competitors, mirroring the evolution of alarm calling in the animal world.

Throughput of cognitive radio networks with improved energy detector under security threats

SummarySpectrum sensing in cognitive radio networks (CRNs) is subjected to some security threats such as primary user emulation (PUE) attack and spectrum sensing data falsification (SSDF) attack. In PUE attack, a malicious user (MUPUE) transmits an emulated primary signal throughout the spectrum sensing interval to secondary users (SUs) to forestall them from accessing the primary user (PU) spectrum bands. In SSDF attack, malicious users (MUSSDF) intentionally report false sensing decisions to the fusion center (FC) to influence the overall decision. While most of the existing literatures have studied the effects of these 2 types of attacks separately, the present paper evaluates the secondary network performance in terms of throughput under both the PUE and SSDF attacks with improved energy detectors (IEDs) where SU's spectrum access is hybrid, ie, either in overlay or in underlay mode. An analytical expression on throughput of SU under the simultaneous influence of both of these attacks is developed. Impact of several parameters such as IED parameter, attacker probabilities, and attacker strength on the throughput of SU is investigated. Performance of the present scheme is also compared with only PUE and only SSDF attacks. A simulation test bed is developed in MATLAB to validate our analytical results.

Forecasting the results of football matches on the Internet based information

The purpose of the article is making a model of results forecasting for football matches, which works better than bookmakers organizations. Lately the popularity of football forecasting has been increased. The existing statistic approaches show difficult and low prediction. The developed model for predicting the results of football matches uses information about the previous results of the teams. The forecast is based on forecasting factors. Although it is difficult to consider all the factors that influence the results of matches the model makes an attempt to find the most important ones. The described model of forecasting takes into consideration such characteristics as: place in the tournament table; total points; goal difference; total number of players, skipping the match; points home / away; home match; "defence strength"; "attack strength"; team form. Testing shows that forecasting and actual results of football matches coincide. The offered model could be used in commercial computer programs for forecasting results of football matches in bookmakers organizations.

Throughput performance under primary user emulation attack in cognitive radio networks

SummarySpectrum sensing in cognitive radio networks imposes some security threats to the secondary users (SUs) such as primary user emulation attack (PUEA). In the present paper, throughput of an SU is studied for cognitive radio network under PUEA where SU spectrum access is hybrid, ie, either in overlay mode or in underlay mode. A novel analytical expression for throughput of an SU in presence of PUEA is developed. Impact of several parameters such as sensing time, attacker strength, attacker's presence probabilities, maximum allowable SU transmit power, and tolerable interference limit at primary user on the throughput of an SU is investigated. The throughput performance under PUEA and without PUEA is compared.

Efeito da adição de zircônia estabilizada com céria nas propriedades mecânicas de compósitos à base de alumina

Coatings for machinery and equipment, in consequence of industrial processes, are demaged by erosion, impact and chemical attack, which lead to frequent production shutdown for maintenance actions. This fact encourages the development of higher strength materials to attend the processing needs. The addition of zirconium and cerium oxides into alumina based compounds has shown promising results as to increase the modulus properties of ceramic such as strength, density and hardness. In this context, the objective of this work was to study the influence of the addition of ceria partially stabilized zirconia (ZPEC, 3-10%) in alumina based composites. To obtain these compounds, aluminum oxide, cerium oxide and zirconium oxide were mixed in a ball mill and formed by cold isostatic pressing, dried and sintered at 1500 or 1600 °C. The raw materials were characterized by XRD and laser granulometry. Mechanical properties, density, porosity, strength and hardness of the materials after sintering were evaluated by linear shrinkage, apparent porosity and density and flexural strength. As a compound to be used as coating which will be subject to erosive wear, the erosion rate was determined by applying a test based on ASTM G-76. The results indicate that the increase in ZPEC content in the alumina-based composites tends to increase the values of resistance to erosive attack, density and flexural strength of these materials, which are important properties for application of materials in industrial environments. Keywords: alumina, ceria-stabilized zirconia, mechanical properties.

Interview

Dr. Selçuk Köse from the University of South Florida in the United States talks to us about the work behind the paper ‘Security implications of simultaneous dynamic and leakage power analysis attacks on nanoscale cryptographic circuits’, page 466. Dr. Selçuk Köse The two primary research thrusts of our group are improving the power efficiency and the trustworthiness of modern integrated circuits. More than 30% of all the power is typically dissipated before even reaching the load circuits during power conversion and delivery. To increase the overall power efficiency, we focus on the source of the problem where we develop circuit, architecture, and system level design methodologies to maximise the voltage conversion efficiency. We have recently proposed a new on-chip power delivery architecture, regulator-gating, where we adaptively turn-on and turn-off individual stages of a multiphase voltage regulator based on the workload to improve power efficiency. In our second research thrust, we further leverage the on-chip voltage regulators as a countermeasure against hardware-based side-channel attacks. In our Letter, one of my PhD students, Weize Yu, and I have investigated the implications of combining two different hardware-based side-channel attacks: dynamic and leakage power analysis attacks. We have shown that combining two different attacks, can be significantly more powerful than performing individual attacks. The strength of a combined attack increases as the correlation between the obtained information with each individual attack decreases. Intuitively, when an attacker performs an individual attack, each subsequent data will be highly correlated with the preceding data sample. When another attack that provides loosely correlated data samples to the existing attack is performed, combining these two attacks would significantly reduce the number of measurements to disclose. The work reported in our Letter highlights the security implications of combined side-channel attacks where combining two attacks could be ten times more powerful than an individual attack. This work accentuates the need for more effective countermeasures against hardware-based side-channel attacks. With the prospected proliferation of Internet-of-Things (IoT) devices with 5G networks, hardware-­security will become even more crucial. The research covered in the Letter exemplifies one of the various possible attack scenarios that may target critical information stored in commercial or personal devices. Since people typically tend to use the same password for various devices, the implications of a successful attack could be quite devastating. IoT devices are quite vulnerable to hardware-attacks since they are typically more accessible to an attacker as compared to the other general purpose computing devices. Additionally, IoT have limited battery power and significant physical constraints. These limitations when combined with the cost constraints make the design of security measures for the IoT quite challenging. Existing countermeasures utilised in general purpose computing devices are mostly not feasible for IoT. Design and management of on-chip power delivery play a central role in our research. While our group is working on several topics at different levels of abstraction for secure and efficient design of next generation power delivery systems, we also leverage on-chip voltage regulators for thermal management and hardware Trojan detection. With the continuous scaling of the transistor size, temperature has recently become a significant design parameter where only a small portion of the transistors can be active at a certain time to not exceed the maximum thermal design power. We are currently working on on-chip thermal management techniques with the help of on-chip voltage regulators. Over the past couple of years, security has become a new design constraint in addition to the existing constraints such as power, noise, speed, and performance. In the next ten years, the importance of security and privacy will continue to increase with the number of connected devices that have become an integral part of our lives. Designing effective security measures at all levels of design abstraction without significant power, performance, and cost overhead will therefore be a significant research area in the next decade.

Defense Against SSDF Attack in Cognitive Radio Networks: Attack-Aware Collaborative Spectrum Sensing Approach

The reliability of the collaborative spectrum sensing (CSS) can be severely decreased by spectrum sensing data falsification (SSDF) attacks. In an SSDF attack, some malicious users intentionally report incorrect local sensing results to the fusion center (FC) and disrupt the global decision-making process. The present study introduces a new defense scheme called attack-aware CSS (ACSS). The proposed method estimates attack strength and applies it in the $k {-} \text{out} {-} N$ rule to obtain the optimum value of $k$ that minimizes the Bayes risk. The attack strength is defined as the ratio of the number of malicious users to the total number of users, which is equal to the probability that a specific user is malicious.

The Performance and Limitations of $\epsilon$- Stealthy Attacks on Higher Order Systems

In a cyber-physical system, security problems are of vital importance as the failure of such system can have catastrophic effects. Detection methods can be employed to sense the existence of an attack. In a previous study of an attack on the controller while avoiding detection in scalar systems under a certain control assumption, the notion of e-stealthiness was introduced and the strength of e-stealthy attacks was fully characterized. We generalize to the vector system and prove the cases in which we show that the limitations of e-stealthy attack do not extend, in the sense that e-stealthy can inflict damage of arbitrary magnitude to a vector system.

Modeling cascading failures in interdependent infrastructures under terrorist attacks

An attack strength degradation model has been introduced to further capture the interdependencies among infrastructures and model cascading failures across infrastructures when terrorist attacks occur. A medium-sized energy system including oil network and power network is selected for exploring the vulnerabilities from independent networks to interdependent networks, considering the structural vulnerability and the functional vulnerability. Two types of interdependencies among critical infrastructures are involved in this paper: physical interdependencies and geographical interdependencies, shown by tunable parameters based on the probabilities of failures of nodes in the networks. In this paper, a tolerance parameter α is used to evaluation of the overloads of the substations based on power flow redistribution in power transmission systems under the attack. The results of simulation show that the independent networks or interdependent networks will be collapsed when only a small fraction of nodes are attacked under the attack strength degradation model, especially for the interdependent networks. The methodology introduced in this paper with physical interdependencies and geographical interdependencies involved in can be applied to analyze the vulnerability of the interdependent infrastructures further, and provides the insights of vulnerability of interdependent infrastructures to mitigation actions for critical infrastructure protections.

Active authentication with reinforcement learning based on ambient radio signals

Active authentication of mobile devices such as smartphones and ipads is promising to enhance security to access confidential data or systems. In this paper, we propose an active authentication scheme, which exploits the physical-layer properties of ambient radio signals to identify mobile devices in indoor environments. More specifically, we discriminate mobile devices in different locations by analyzing the ambient radio sources, because the received signal strength indicator set of the ambient signals measured by a smartphone is usually different from that observed by its spoofer located in another area. We formulate the interactions between the legitimate mobile device and its spoofer as an active authentication game, in which the receiver chooses its test threshold in the hypothesis test in the spoofing detection, while the spoofer chooses its attack strength. In a dynamic radio environment with unknown attack parameters, we propose a learning-based authentication algorithm based on the physical-layer properties of the ambient radio environments. Simulation results show that the proposed scheme accurately detects spoofers in typical indoor environments.

Collaborative Spectrum Sensing under Primary User Emulation Attack in Cognitive Radio Networks

ABSTRACTSpectrum sensing is the main function of cognitive radio (CR), which enables the CR users to detect the spectrum holes. Inherent characteristics of CR have imposed some serious threats to the networks. One of the common threats in CR network is primary user emulation attack (PUEA). In this particular type of attack, some malicious users try to imitate primary signal characteristics and defraud CR users to prevent them from accessing the spectrum holes. Therefore, an effective defense strategy is extremely important for robust collaborative spectrum sensing (CSS). The current study introduces a new CSS scheme in the presence of an intelligent PUEA, called attack-aware CSS (ACSS), which is aware of spectrum holes and actually co-located with the licensed primary user (PU) and transmits with the same power level in a way that CR users are not easily able to differentiate between received signal from PU and PUEA. The idea is based on attack strength estimation, where the attack strength is defined as the channel occupancy rate of malicious PUEA which equals to the probability that the malicious emulator occupies a specific spectrum hole. The proposed approach estimates the attack strength and innovatively applies in Neyman–Pearson or likelihood ratio test to improve collaborative sensing performance. Simulation results are provided to indicate the superiority of the proposed ACSS method against PUEA compared with the conventional method.

A new colour vision system to quantify automatically foliar discolouration caused by insect pests feeding on leaf cells

Leaf colour and leaf area are key parameters for many plant studies, including plant protection. The quantification of foliar bleached area is often used to evaluate the strength of plant attack by pests or diseases, to compare the efficiency of different treatments, the resistance of some populations, and to set up some control methods. The quantification of such area by human vision often lacks accuracy and reliability. Image analysis systems could bring a more accurate and objective measure, and could be automated to treat a great number of samples. Such an automated tool has been developed in order to measure quantitatively foliar bleaching due to the sycamore lace bug, Corythucha ciliata (SAY) on Plane tree. This tool was built up with a colour image capture bench and a fast automated segmentation process based on an original chlorophyll histogram unsupervised classification. Dedicated software was developed and integrated in an operational image processing platform capable of routine use by non-specialists in image analysis. The accuracy of the tool was determined by comparison to human expert segmentation. A very low error rate was observed in the absence of artefacts, but artefacts such as powdery mildew symptoms were not well distinguished and lead to weaker performance. Comparing its reliability and robustness to classical visual estimation and classification method, the tool performance was similar to the most experienced rater. The advantage of such a system is the possibility to treat automatically a large number of pictures and produce accurate, reliable, repeatable and non-subjective quantitative measurements.

Network Protection Against DDoS Attacks

The paper deals with possibilities of the network protection against Distributed Denial of Service attacks (DDoS). The basic types of DDoS attacks and their impact on the protected network are presented here. Furthermore, we present basic detection and defense techniques thanks to which it is possible to increase resistance of the protected network or device against DDoS attacks. Moreover, we tested the ability of current commercial Intrusion Prevention Systems (IPS), especially Radware DefensePro 6.10.00 product against the most common types of DDoS attacks. We create five scenarios that are varied in type and strength of the DDoS attacks. The attacks intensity was much greater than the normal intensity of the current DDoS attacks.

AFM-based quantification of conformational changes in DNA caused by reactive oxygen species.

Radical induced modification of DNA plays an important role in many pathological pathways like cancer development, aging, etc. In this work, we quantify radical-induced DNA damage that causes transitions from double to single stranded DNA using atomic force microscopy (AFM). The plasmid pBR322 is attacked by free hydroxyl radicals that are produced by Fenton's reaction; the strength of the radical attack is controlled via the ratio of hydroxyl radical molecules to DNA base pairs. The extent of DNA modification is assessed by AFM tapping mode (TM) imaging of the plasmids (after adsorption onto PAH-functionalized mica) in air. As single stranded DNA chains (height ∼2 Å) are much smaller than intact DNA strands (∼5 Å), their fraction can be quantified based on the height distribution, which allows a simplified data analysis in comparison to similar AFM-based approaches. It is found that the amount of damaged DNA strands increases with increasing strength of radical attack, and decreases if ROS scavengers like sodium acetate are added. Competition curves are calculated for the interaction of hydroxyl radicals with DNA and sodium acetate, which finally allows calculation of relative rate constants for the respective reactions.

Robustness of network of networks with interdependent and interconnected links

Robustness of network of networks (NON) has been studied only for dependency coupling (Gao et al., 2012) and only for connectivity coupling (Leicht and Souza, arxiv:0907.0894). The case of network of networks with both interdependent and interconnected links is more complicated, and also more close to real-life coupled network systems. Understanding the robustness of NON with interdependent and interconnected links is helpful to design resilient infrastructures. Here we develop a framework to study analytically and numerically the robustness of this system with no-feedback and feedback conditions for the case of starlike NON. When assumed that all degree distributions of the connectivity intra- and inter-links are Poissonian, we find that the system undergoes from second order through hybrid order to first order phase transition as coupling strength q increases. Additionally, for both conditions, the results suggest that increasing density of connectivity links (intra-connectivity links or inter-connectivity links) can increase the robustness of the system, while the interdependency links decrease its robustness. Furthermore, by comparing critical attacking strength under same parameters for both conditions, we also find that feedback condition of dependency links, in contrast to no-feedback condition, makes the system extremely vulnerable. Although our detailed analysis is for Poisson degree distribution, the theory can be applied to any degree distribution and other basic topological structure of network such like tree-like and loop-like NON.

Analysis of Intrusion Detection Response System (IDRS) In Cyber Physical Systems (Cps) Using Regular Expression (Regexp)

In this research we aim to design and validate Intrusion Detection Response System (IDRS) for a cyber physical system (CPS) comprising for controlling and protecting physical infrastructures. The design part includes host IDS, system IDS and IDS response designs. The validation part includes a novel model-based analysis methodology with simulation validation. Our objective is to maximize the CPS reliability or lifetime in the presence of malicious nodes performing attacks which can cause security failures. Our host IDS design results in a lightweight, accurate, autonomous and adaptive protocol that runs on every node in the CPS to detect misbehavior of neighbor nodes based on state-based behavior specifications. Our system IDS design results in a robust and resilient protocol that can cope with malicious, erroneous, partly trusted, uncertain and incomplete information in a CPS. Our IDS response design results in a highly adaptive and dynamic control protocol that can adjust detection strength in response to environment changes in attacker strength and behavior. The end result is an energy-aware and adaptive IDS that can maximize the CPS lifetime in the presence of malicious attacks, as well as malicious, erroneous, partly trusted, uncertain and incomplete information. We develop a probability model based on regular expression technique to describe the behavior of a CPS incorporating our proposed intrusion detection and response designs, subject to attacks by malicious nodes exhibiting a range of attacker behaviors, including reckless, random, insidious and opportunistic attacker models. We identify optimal intrusion detection settings under which the CPS reliability or lifetime is maximized for each attacker model. Adaptive control for maximizing IDS performance is achieved by dynamically adjusting detection and response strength in response to attacker strength and behavior detected at runtime.