Search results for "DETECT"
showing 10 items of 5902 documents
State of the Art Literature Review on Network Anomaly Detection
2018
As network attacks are evolving along with extreme growth in the amount of data that is present in networks, there is a significant need for faster and more effective anomaly detection methods. Even though current systems perform well when identifying known attacks, previously unknown attacks are still difficult to identify under occurrence. To emphasize, attacks that might have more than one ongoing attack vectors in one network at the same time, or also known as APT (Advanced Persistent Threat) attack, may be hardly notable since it masquerades itself as legitimate traffic. Furthermore, with the help of hiding functionality, this type of attack can even hide in a network for years. Additi…
A Novel Method for Detecting APT Attacks by Using OODA Loop and Black Swan Theory
2018
Advanced Persistent Threat(APT) attacks are a major concern for the modern societal digital infrastructures due to their highly sophisticated nature. The purpose of these attacks varies from long period espionage in high level environment to causing maximal destruction for targeted cyber environment. Attackers are skilful and well funded by governments in many cases. Due to sophisticated methods it is highly important to study proper countermeasures to detect these attacks as early as possible. Current detection methods under-performs causing situations where an attack can continue months or even years in a targeted environment. We propose a novel method for analysing APT attacks through OO…
A Novel Deep Learning Stack for APT Detection
2019
We present a novel Deep Learning (DL) stack for detecting Advanced Persistent threat (APT) attacks. This model is based on a theoretical approach where an APT is observed as a multi-vector multi-stage attack with a continuous strategic campaign. To capture these attacks, the entire network flow and particularly raw data must be used as an input for the detection process. By combining different types of tailored DL-methods, it is possible to capture certain types of anomalies and behaviour. Our method essentially breaks down a bigger problem into smaller tasks, tries to solve these sequentially and finally returns a conclusive result. This concept paper outlines, for example, the problems an…
State of the Art Literature Review on Network Anomaly Detection with Deep Learning
2018
As network attacks are evolving along with extreme growth in the amount of data that is present in networks, there is a significant need for faster and more effective anomaly detection methods. Even though current systems perform well when identifying known attacks, previously unknown attacks are still difficult to identify under occurrence. To emphasize, attacks that might have more than one ongoing attack vectors in one network at the same time, or also known as APT (Advanced Persistent Threat) attack, may be hardly notable since it masquerades itself as legitimate traffic. Furthermore, with the help of hiding functionality, this type of attack can even hide in a network for years. Additi…
Scratches Removal in Digitised Aerial Photos Concerning Sicilian Territory
2007
In this paper we propose a fast and effective method to detect and restore scratches in aerial photos from a photographic archive concerning Sicilian territory. Scratch removal is a typical problem for old movie films but similar defects can be seen in still images. Our solution is based on a semiautomatic detection process and an unsupervised restoration algorithm. Results are comparable with those obtained with commercial restoration tools.
A robust aerial image registration method using Gaussian mixture models
2014
Aerial image registration is one of the bases in many aerospace applications, such as aerial reconnaissance and aerial mapping. In this paper, we propose a novel aerial image registration algorithm which is based on Gaussian mixture models. First of all, considering the characters of the aerial images, the work uses a shape feature detector which computes the boundaries of regions with nearly the same gray-value to extract invariant feature. Then, a Gaussian mixture models (GMM) based image registration model is built and solved to estimate the transformation matrix between two aerial images. Furthermore, the proposed method is applied on real aerial images, and the results demonstrate the …
Drop-on-demand sample introduction system coupled with the flowing atmospheric-pressure afterglow for direct molecular analysis of complex liquid mic…
2012
One of the fastest developing fields in analytical spectrochemistry in recent years is ambient desorption/ionization mass spectrometry (ADI-MS). This burgeoning interest has been due to the demonstrated advantages of the method: simple mass spectra, little or no sample preparation, and applicability to samples in the solid, liquid, or gaseous state. One such ADI-MS source, the flowing atmospheric-pressure afterglow (FAPA), is capable of direct analysis of solids just by aiming the source at the solid surface and sampling the produced ions into a mass spectrometer. However, direct introduction of significant volumes of liquid samples into this source has not been possible, as solvent loads c…
Towards comprehensive non-target screening using heart-cut two-dimensional liquid chromatography for the analysis of organic atmospheric tracers in i…
2021
Abstract Non-target screening of secondary organic aerosol compounds in ice cores is used to reconstruct atmospheric conditions and sources and is a valuable tool to elucidate the chemical profiles of samples with the aim to obtain as much information as possible from one mass spectrometric measurement. The coupling of mass spectrometry to chromatography limits the results of a non-target screening to signals of compounds within a certain polarity range based on the utilized stationary phases of the columns. Comprehensive two-dimensional liquid chromatography (LCxLC) introduces a second column of different functionality to enable the analysis of a broader range of analytes. Conventional LCx…
Comparison of UV and charged aerosol detection approach in pharmaceutical analysis of statins
2009
Abstract CAD (charged aerosol detector) has recently become a new alternative detection system in HPLC. This detection approach was applied in a new HPLC method for the determination of three of the major statins used in clinical treatment—simvastatin, lovastatin and atorvastatin. The method was optimized and the influence of individual parameters on CAD response and sensitivity was carefully studied. Chromatography was performed on a Zorbax Eclipse XDB C18 (4.6 mm × 75 mm, 3.5 μm), using acetonitrile and formic acid 0.1% as mobile phase. The detection was performed using both CAD (20 pA range) and DAD (diode array detector—238 nm) simultaneously connected in series. In terms of linearity, …
Application of time-of-flight aerosol mass spectrometry for the online measurement of gaseous molecular iodine.
2012
Here we present a new application of a time-of-flight aerosol mass spectrometer (TOF-AMS) for the measurement of atmospheric trace gases in real-time. Usually, TOF-AMS instruments are not sensitive to gas-phase species due to the aerodynamic particle focusing inlet system which reduces the gas phase species by a factor of about 10(7) relative to the particle phase. This efficient removal of the gas phase and the resulting high relative enrichment of particles is one reason for the very high sensitivity of TOF-AMS instruments for particle phase compounds (detection limits in the sub-μg/m(3)-range for online measurements with 1 min integration time), which allows application of the instrument…