A Study on Swarm Intelligence Techniques in Intrusion Detection
... At the same time it decreases for all other terms (evaporation). Among the discovered rules the best one is selected and augmented to the discovered rules. This is done iteratively until a large base of rules is constructed which can be later on used in test sets as criteria for classifying network ...
... At the same time it decreases for all other terms (evaporation). Among the discovered rules the best one is selected and augmented to the discovered rules. This is done iteratively until a large base of rules is constructed which can be later on used in test sets as criteria for classifying network ...
Music Similarity Estimation with the Mean
... We aggregate local features into a global descriptor by histogramming, which discards the order of features similar to Bag-of-Words approaches successfully used in text processing [27]. This is straightforward for k-Means features: We just count the number of occurrences of each cluster label. For m ...
... We aggregate local features into a global descriptor by histogramming, which discards the order of features similar to Bag-of-Words approaches successfully used in text processing [27]. This is straightforward for k-Means features: We just count the number of occurrences of each cluster label. For m ...
Music Blocks
... essential to explore underlying musical structures beyond reusing precomposed phrases. Csound has been used as the underlying engine for many music applications, as a language itself, its design is intended neither for children nor beginning programmers. There are a plethora of programming environme ...
... essential to explore underlying musical structures beyond reusing precomposed phrases. Csound has been used as the underlying engine for many music applications, as a language itself, its design is intended neither for children nor beginning programmers. There are a plethora of programming environme ...
BIOINFORMATICS ORIGINAL PAPER
... that take many days to acquire. Under limited time constraints, oftentimes small samples of tissue are imaged and analyzed to infer spatial properties of a whole tissue. However, many tissues are spatially heterogeneous; application of mining or quantification methods on small images may not provide ...
... that take many days to acquire. Under limited time constraints, oftentimes small samples of tissue are imaged and analyzed to infer spatial properties of a whole tissue. However, many tissues are spatially heterogeneous; application of mining or quantification methods on small images may not provide ...
Artificial Intelligence in Network Intrusion Detection
... DARPA 1998 remain in KDD'99 too. One of the most important deficiencies in both data sets is the huge number of redundant records, which causes the learning algorithms to be biased towards the frequent records, and thus prevent them from learning infrequent records which are usually more harmful to ...
... DARPA 1998 remain in KDD'99 too. One of the most important deficiencies in both data sets is the huge number of redundant records, which causes the learning algorithms to be biased towards the frequent records, and thus prevent them from learning infrequent records which are usually more harmful to ...
pixel measurement of thyroid gland by using ultrasound image
... Image processing is one of the kind of signal processing in which an image or video is an input and output may be an image, video or set of parameters interconnected with that image. Any Image can get taken according to our field or requirements. Image processing generally refers as digital image pr ...
... Image processing is one of the kind of signal processing in which an image or video is an input and output may be an image, video or set of parameters interconnected with that image. Any Image can get taken according to our field or requirements. Image processing generally refers as digital image pr ...
Lecture Notes 5 - Fall 2009
... Suppose IDS warns whenever N or more failed logins in M seconds Must set N and M so that false alarms not common Can do this based on normal behavior But if attacker knows the signature, he can try N-1 logins every M seconds! In this case, signature detection slows the attacker, but might not stop h ...
... Suppose IDS warns whenever N or more failed logins in M seconds Must set N and M so that false alarms not common Can do this based on normal behavior But if attacker knows the signature, he can try N-1 logins every M seconds! In this case, signature detection slows the attacker, but might not stop h ...
Human Facial Expression Recognition using Gabor
... into a number of expressive regions). These regions are combined with terric map. LDA was used as a classifier and performance of the system was about 82.61%. ...
... into a number of expressive regions). These regions are combined with terric map. LDA was used as a classifier and performance of the system was about 82.61%. ...
Slides ClassSlides - School of Computer Science
... colour axes (e.g., red, green, blue), the colour histogram is obtained by discretizing the image colours and counting the number of times each discrete colour occurs in the image. The image colours that are transformed to a common discrete colour are usefully thought of as being in the same 3D his ...
... colour axes (e.g., red, green, blue), the colour histogram is obtained by discretizing the image colours and counting the number of times each discrete colour occurs in the image. The image colours that are transformed to a common discrete colour are usefully thought of as being in the same 3D his ...
Classification of Clustered Microcalcifications using Resilient
... clusters of Microcalcifications. In this paper, Resilient Backpropagation training algorithm is investigated for automated classification of clustered Microcalcifications (MCCs) as benign or malignant. The classifier is a part of computer aided disease diagnosis (CAD) system that is widely used to a ...
... clusters of Microcalcifications. In this paper, Resilient Backpropagation training algorithm is investigated for automated classification of clustered Microcalcifications (MCCs) as benign or malignant. The classifier is a part of computer aided disease diagnosis (CAD) system that is widely used to a ...
Fundamentals of Multimedia, Chapter 18
... • To deal with illumination change from the query image to different database images, each color channel band of each image is first normalized, and then compressed to a 36-vector. • A 2-dimensional color histogram is then created by using the chromaticity, which is the set of band ratios {R,G}/(R+G ...
... • To deal with illumination change from the query image to different database images, each color channel band of each image is first normalized, and then compressed to a 36-vector. • A 2-dimensional color histogram is then created by using the chromaticity, which is the set of band ratios {R,G}/(R+G ...
Volumetric MRI Classification for Alzheimer`s Diseases Based on
... structures may be preferentially modified by particular cognitive skills, genes or diseases1,2. Morphological analysis of medical images is therefore used in a variety of research and clinical studies that detect and quantify spatially complex and often subtle abnormal imaging patterns of pathology. ...
... structures may be preferentially modified by particular cognitive skills, genes or diseases1,2. Morphological analysis of medical images is therefore used in a variety of research and clinical studies that detect and quantify spatially complex and often subtle abnormal imaging patterns of pathology. ...
Fundamentals of Multimedia, Chapter 18
... • To deal with illumination change from the query image to different database images, each color channel band of each image is first normalized, and then compressed to a 36-vector. • A 2-dimensional color histogram is then created by using the chromaticity, which is the set of band ratios {R,G}/(R+G ...
... • To deal with illumination change from the query image to different database images, each color channel band of each image is first normalized, and then compressed to a 36-vector. • A 2-dimensional color histogram is then created by using the chromaticity, which is the set of band ratios {R,G}/(R+G ...
PDF
... are segment labels, plotted at the position of the segment center. Two nodes are connected by an edge if they touch each other. The resulting graph are rather complex. In order to test and validate the main idea of this paper, we therefore chose a simplified abstract example of this scenario (see Fi ...
... are segment labels, plotted at the position of the segment center. Two nodes are connected by an edge if they touch each other. The resulting graph are rather complex. In order to test and validate the main idea of this paper, we therefore chose a simplified abstract example of this scenario (see Fi ...
Image Texture Classification using Gray Level Co
... to similar look textures and different look textures. In the fourth experiment, the ability of the proposed classifier system is evaluated when the original image is corrupted under different degree of Gaussian white noise. In this experiment, the mean and variance value of the Gaussian white noise ...
... to similar look textures and different look textures. In the fourth experiment, the ability of the proposed classifier system is evaluated when the original image is corrupted under different degree of Gaussian white noise. In this experiment, the mean and variance value of the Gaussian white noise ...
IOSR Journal of Computer Engineering (IOSR-JCE)
... communication costs. Because most techniques used in today's IDS are not able to deal with the dynamic and complex nature of cyber-attacks on computer networks. So the author reviewed several influential algorithms for intrusion detection based on various machine learning techniques, and divided the ...
... communication costs. Because most techniques used in today's IDS are not able to deal with the dynamic and complex nature of cyber-attacks on computer networks. So the author reviewed several influential algorithms for intrusion detection based on various machine learning techniques, and divided the ...
Classifier Ensembles for Detecting Concept Change in Streaming
... reverse is also possible but batch data usually comes in massive quantities, and instance-based processing may be too timeconsuming. • Explicit versus implicit change detection. After explicit change detection, action is taken, for example, setting up a window of latest data to re-train the classifi ...
... reverse is also possible but batch data usually comes in massive quantities, and instance-based processing may be too timeconsuming. • Explicit versus implicit change detection. After explicit change detection, action is taken, for example, setting up a window of latest data to re-train the classifi ...
A Watershed-based Social Events Detection Method with Support of
... In this paper, a watershed-based method with support from external data sources is proposed to detect Social Events defined by MediaEval 2012. This method is based on two main observations: (1) people cannot be involved in more than one event at the same time, and (2) people tend to introduce simila ...
... In this paper, a watershed-based method with support from external data sources is proposed to detect Social Events defined by MediaEval 2012. This method is based on two main observations: (1) people cannot be involved in more than one event at the same time, and (2) people tend to introduce simila ...
A Behavior Based Intrusion Detection System Using Machine
... records, which causes the learning algorithms to be biased towards the frequent records, and thus prevent them from learning infrequent records, which are usually more harmful to networks such as U2R and R2L attacks [21]. In addition, the existence of these repeated records in the test set will caus ...
... records, which causes the learning algorithms to be biased towards the frequent records, and thus prevent them from learning infrequent records, which are usually more harmful to networks such as U2R and R2L attacks [21]. In addition, the existence of these repeated records in the test set will caus ...
IOSR Journal of Computer Engineering (IOSR-JCE)
... Artificial neural networks (ANNs) are computational models inspired by humans' central nervous systems (in particular the brain) that are capable of machine learning and pattern recognition. They are usually presented as systems of interconnected "neurons" that can compute values from inputs by feed ...
... Artificial neural networks (ANNs) are computational models inspired by humans' central nervous systems (in particular the brain) that are capable of machine learning and pattern recognition. They are usually presented as systems of interconnected "neurons" that can compute values from inputs by feed ...
content based image retrieval
... visual system is specially organized to detect subtle image features and perform high-level processing, which is further processed to generate object entities and concepts. The anatomy of the visual system explains from the structure aspect why visual information is so important to human cognition. ...
... visual system is specially organized to detect subtle image features and perform high-level processing, which is further processed to generate object entities and concepts. The anatomy of the visual system explains from the structure aspect why visual information is so important to human cognition. ...
Neural Robot Detection in RoboCup
... After calculating the different features, they are passed to two artificial neural networks as can be seen in Figure 2. One network only processes the simple features, the input for the second one are the orientation histogram values. The breakdown into two networks turned out to be necessary in ord ...
... After calculating the different features, they are passed to two artificial neural networks as can be seen in Figure 2. One network only processes the simple features, the input for the second one are the orientation histogram values. The breakdown into two networks turned out to be necessary in ord ...
Scalable spatial event representation
... using supervised and unsupervised learning techniques is used to label the image features. SECs can be used to not only visualize the dominant spatial arrangements of feature classes but also discover non-obvious configurations. SECs also provide the framework for high-level data mining techniques s ...
... using supervised and unsupervised learning techniques is used to label the image features. SECs can be used to not only visualize the dominant spatial arrangements of feature classes but also discover non-obvious configurations. SECs also provide the framework for high-level data mining techniques s ...
IOSR Journal of Computer Engineering (IOSR-JCE)
... the expectations of researchers and vendors. Promises that IDSs would be capable of reliably identifying malicious activity never turned into reality. While virus scanners and firewalls have visible benefits and remain virtually unnoticed during normal operation, intrusion detection systems are know ...
... the expectations of researchers and vendors. Promises that IDSs would be capable of reliably identifying malicious activity never turned into reality. While virus scanners and firewalls have visible benefits and remain virtually unnoticed during normal operation, intrusion detection systems are know ...
Multi-objective optimization of support vector machines
... Perhaps the most elaborate techniques for choosing hyperparameters are gradient-based approaches [14, 15, 16, 17, 18]. When applicable, these methods are highly efficient. However, they have some drawbacks and limitations. The most important one is that the score function for assessing the performan ...
... Perhaps the most elaborate techniques for choosing hyperparameters are gradient-based approaches [14, 15, 16, 17, 18]. When applicable, these methods are highly efficient. However, they have some drawbacks and limitations. The most important one is that the score function for assessing the performan ...