An automated vulnerability scanner for injection attack based on injection point

2010 ◽  
Author(s):  
Jan-Min Chen ◽  
Chia-Lun Wu
Keyword(s):  
Injection Point ◽  
Vulnerability Scanner

scholarly journals A Dynamical Study of Fusion Hindrance with Nakajima-Zwanzig Projection Method

2021 ◽  
Author(s):  
Yasuhisa Abe ◽  
David Boilley ◽  
Quentin Hourdillé ◽  
Caiwan Shen
Keyword(s):  
Cross Sections ◽  
Degrees Of Freedom ◽  
Operator Method ◽  
Initial Distribution ◽  
Physical Parameters ◽  
Relaxation Processes ◽  
Fast Variable ◽  
Dynamical Study ◽  
Injection Point ◽  
Slow Variables

Abstract A new framework is proposed for the study of collisions between very heavy ions which lead to the synthesis of Super-Heavy Elements (SHE), to address the fusion hindrance phenomenon. The dynamics of the reaction is studied in terms of collective degrees of freedom undergoing relaxation processes with different time scales. The Nakajima-Zwanzig projection operator method is employed to eliminate fast variable and derive a dynamical equation for the reduced system with only slow variables. There, the time evolution operator is renormalised and an inhomogeneous term appears, which represents a propagation of the given initial distribution. The term results in a slip to the initial values of the slow variables. We expect that gives a dynamical origin of the so-called “injection point s” introduced by Swiatecki et al in order to reproduce absolute values of measured cross sections for SHE. A formula for the slip is given in terms of physical parameters of the system, which confirms the results recently obtained with a Langevin equation, and permits us to compare various incident channels.

MoScan: a model-based vulnerability scanner for web single sign-on services

2021 ◽  
Author(s):  
Hanlin Wei ◽  
Behnaz Hassanshahi ◽  
Guangdong Bai ◽  
Padmanabhan Krishnan ◽  
Kostyantyn Vorobyov
Keyword(s):  
Single Sign On ◽  
Model Based ◽  
Vulnerability Scanner

scholarly journals Enhancing bioenergy production from food waste by in situ biomethanation: Effect of the hydrogen injection point

2021 ◽  
Author(s):  
Cynthia Kusin Okoro‐Shekwaga ◽  
Andrew Ross ◽  
Miller Alonso Camargo‐Valero
Keyword(s):  
Food Waste ◽  
Injection Point ◽  
Bioenergy Production

Estimating saturation and density changes caused by CO2 injection at Sleipner — Using time-lapse seismic amplitude-variation-with-offset and time-lapse gravity

2017 ◽  
Vol 5 (2) ◽  
pp. T243-T257 ◽  
Author(s):  
Martin Landrø ◽  
Mark Zumberge
Keyword(s):  
Gravity Data ◽  
Time Lapse ◽  
Co2 Injection ◽  
Injection Point ◽  
Amplitude Variation With Offset ◽  
Seismic Method ◽  
Seismic Amplitude ◽  
Gravity Measurements ◽  
Measured Time ◽  
Best Fit

We have developed a calibrated, simple time-lapse seismic method for estimating saturation changes from the [Formula: see text]-storage project at Sleipner offshore Norway. This seismic method works well to map changes when [Formula: see text] is migrating laterally away from the injection point. However, it is challenging to detect changes occurring below [Formula: see text] layers that have already been charged by some [Formula: see text]. Not only is this partly caused by the seismic shadow effects, but also by the fact that the velocity sensitivity for [Formula: see text] change in saturation from 0.3 to 1.0 is significantly less than saturation changes from zero to 0.3. To circumvent the seismic shadow zone problem, we combine the time-lapse seismic method with time-lapse gravity measurements. This is done by a simple forward modeling of gravity changes based on the seismically derived saturation changes, letting these saturation changes be scaled by an arbitrary constant and then by minimizing the least-squares error to obtain the best fit between the scaled saturation changes and the measured time-lapse gravity data. In this way, we are able to exploit the complementary properties of time-lapse seismic and gravity data.

Using impressed current cathodic protection systems of pipelines for electromagnetic exploration

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. B155-B165 ◽  
Author(s):  
Tobias Lindau ◽  
Michael Becken
Keyword(s):  
Cathodic Protection ◽  
Transfer Functions ◽  
Spatial Behavior ◽  
Local Source ◽  
Phase Lag ◽  
Injection Point ◽  
Frequency Dependency ◽  
Pipeline Segment ◽  
Impressed Current ◽  
Impressed Current Cathodic Protection

Low-frequency electromagnetic (EM) signals generated by networks of technical infrastructure such as power-lines, pipelines, or railways may provide a cheap and efficient means to perform EM depth sounding of the upper few kilometers of the earth. We attempt to use the signals emitted by an impressed current cathodic protection (ICCP) system of a 35 km long gas pipeline segment in northwestern Germany. The installed ICCP system uses a periodical 12 s on/3 s off current switching scheme, which resembles current waveforms used in controlled-source electromagnetics (CSEM). In contrast to CSEM, where a grounded electrical dipole is used as the source, the current flow in pipelines is not constant along its legs. Our efforts are therefore concentrated toward the determination of the temporal and spatial behavior of the electrical current within the investigated pipeline segment. Although the time dependency of the current can be measured directly at the injection point, the spatial distribution is only accessible through indirect observations. We use fluxgate magnetic field measurements at multiple locations directly above the pipeline to infer the local source current and its frequency-dependency and phase lag. We observe that the current decays roughly exponentially away from the injection point, exhibits a position-dependent frequency dependency, and experiences a phase shift that accumulates to more than 30° at the ends of the segment. These effects can be consistently explained with a transmission line model. Having determined the current distribution, we can represent the pipeline as an EM source superposed of point dipoles. The estimated source model allows us to predict the electric (and magnetic) fields at remote locations. To verify our approach, we deploy an array of telluric recorders in the vicinity of the pipeline, estimate the frequency-domain transfer functions, and invert the data into a 3D electrical conductivity model using smoothness-constrained inversion techniques.

Collisional radiative model for the evaluation of the Thermal Helium Beam diagnostic at ASDEX Upgrade

2022 ◽  
Author(s):  
Daniel Wendler ◽  
Ralph Dux ◽  
Rainer Fischer ◽  
Michael Griener ◽  
Elisabeth Wolfrum ◽  
...  
Keyword(s):  
Excited States ◽  
Ultra Violet ◽  
Plasma Edge ◽  
Excitation Mechanism ◽  
Computationally Efficient ◽  
Injection Point ◽  
Collisional Radiative Model ◽  
Radiative Model ◽  
Measured Line ◽  
Vacuum Ultra Violet

Abstract The thermal helium beam diagnostic at ASDEX Upgrade is used to infer the electron density ne and temperature Te in the scrape-off layer and the pedestal region from the emission of visible lines of the locally injected helium. The link between ne and Te and the emission is provided by a collisional radiative model, which delivers the evolution of the populations of the relevant excited states as the He atoms travel through the plasma. A computationally efficient method with just three effective states is shown to provide a good approximation of the population dynamics. It removes an artificial rise of Te at the plasma edge when using a simple static model. Furthermore, the re-absorption of the vacuum ultra-violet resonance lines has been introduced as additional excitation mechanism being mainly important in the region close to the injection point. This extra excitation leads to a much better fit of the measured line ratios in this region for larger puff rates.

AUTOMATED VULNERABILITY SEARCH IN A WEB APPLICATION BASED ON REINFORCEMENT LEARNING

2021 ◽  
Vol 53 (1) ◽  
pp. 91-97
Author(s):  
OLGA N. VYBORNOVA ◽  
◽  
ALEKSANDER N. RYZHIKOV ◽  
Keyword(s):  
Reinforcement Learning ◽  
Web Application ◽  
Web Applications ◽  
Subject Area ◽  
Learning Technology ◽  
Web Application Security ◽  
Vulnerability Scanner ◽  
Learning Agent ◽  
Markov Decision ◽  
Python Programming

We analyzed the urgency of the task of creating a more efficient (compared to analogues) means of automated vulnerability search based on modern technologies. We have shown the similarity of the vulnerabilities identifying process with the Markov decision-making process and justified the feasibility of using reinforcement learning technology for solving this problem. Since the analysis of the web application security is currently the highest priority and in demand, within the framework of this work, the application of the mathematical apparatus of reinforcement learning with to this subject area is considered. The mathematical model is presented, the specifics of the training and testing processes for the problem of automated vulnerability search in web applications are described. Based on an analysis of the OWASP Testing Guide, an action space and a set of environment states are identified. The characteristics of the software implementation of the proposed model are described: Q-learning is implemented in the Python programming language; a neural network was created to implement the learning policy using the tensorflow library. We demonstrated the results of the Reinforcement Learning agent on a real web application, as well as their comparison with the report of the Acunetix Vulnerability Scanner. The findings indicate that the proposed solution is promising.

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