Anomaly Detection Techniques

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What is a major limitation of supervised anomaly detection?

Limited applicability

High accuracy

High computational cost

Data unavailability and unbalanced classes (correct)

Which anomaly detection technique uses a labeled dataset?

Semi-supervised anomaly detection

Reinforcement learning

Supervised anomaly detection (correct)

Unsupervised anomaly detection

What is a common application of unsupervised anomaly detection?

Natural language processing

Network intrusion detection (correct)

Recommendation systems

Image classification

Which algorithm is often used in unsupervised anomaly detection?

Clustering algorithms Signup and view all the answers

What is the main advantage of unsupervised anomaly detection?

No need for labeled data Signup and view all the answers

What type of neural networks are used in anomaly detection to identify anomalies in limited labeled data?

Semi-supervised neural networks Signup and view all the answers

What is the purpose of categorizing anomaly detection techniques?

To compare and evaluate their effectiveness Signup and view all the answers

What is the primary objective of an agent in reinforcement learning?

To learn a policy that maximizes the reward over time Signup and view all the answers

What type of machine learning training method is used for anomaly detection?

Reinforcement learning Signup and view all the answers

What type of data is commonly used in supervised anomaly detection?

Labeled dataset Signup and view all the answers

Why are labels typically binary in anomaly detection?

No specific reason, it's just a convention Signup and view all the answers

What is the primary application of reinforcement learning models in anomaly detection?

Algorithmic trading Signup and view all the answers

What is the environment of an agent in reinforcement learning?

An environment with clear parameters defining beneficial and non-beneficial activity Signup and view all the answers

What is the goal of the agent's decision-making process in reinforcement learning?

To maximize the reward over time Signup and view all the answers

What type of anomaly detection systems use reinforcement learning?

Reinforcement learning models Signup and view all the answers

What is the characteristic of the overarching endgame in reinforcement learning?

Clear parameters defining beneficial and non-beneficial activity Signup and view all the answers

What can reinforcement learning be useful for in anomaly detection?

Learning through trial-and-error interactions with the environment Signup and view all the answers

What is the primary purpose of statistical methodologies in Network Anomaly Detection Systems (NADS)?

To identify and predict abnormal behavior Signup and view all the answers

What is the Z-score used for in anomaly detection?

To measure the distance of a data point from the mean Signup and view all the answers

What is the primary difference between parametric and non-parametric techniques in statistical anomaly detection models?

Parametric techniques assume data distribution, while non-parametric techniques do not Signup and view all the answers

What is the purpose of density-based algorithms in anomaly detection?

To determine outliers based on a data point's deviation from a specific density threshold Signup and view all the answers

What is the primary advantage of the modified Z-score method?

It is useful for detecting outliers in non-Gaussian distributions Signup and view all the answers

What is the purpose of the semi-supervised statistical approach in anomaly detection?

To create a probabilistic model of network normal behavior and detect deviations from this model Signup and view all the answers

What is the primary purpose of correlation methods in Network Anomaly Detection Systems (NADS)?

To identify and predict abnormal behavior Signup and view all the answers

What is the primary purpose of correlation-based feature selection in anomaly detection?

To select the most relevant features by calculating their correlation with the target variable Signup and view all the answers

What is the main advantage of using correlation methods in NADS?

They can analyze the correlation between different network variables Signup and view all the answers

Which method uses a deep neural network classifier to classify network traffic?

Correlation-based classification Signup and view all the answers

What is the primary goal of NADS?

To identify and predict abnormal behavior in computer networks Signup and view all the answers

What is used to identify anomalies in the data correlation method?

Regression relations Signup and view all the answers

What do logic methodologies aid in NADS?

Identifying and predicting abnormal behavior in computer networks Signup and view all the answers

What is the main difference between correlation-based anomaly detection and correlation-based feature selection?

Anomaly detection analyzes the correlation between different network variables, while feature selection analyzes individual variables Signup and view all the answers

What is the benefit of using correlation methods in complex network environments?

They can enhance the accuracy of anomaly detection Signup and view all the answers

What technique can Fuzzy Logic be used for in network anomaly detection systems?

Unsupervised Anomaly Detection Signup and view all the answers

What is the primary function of automation in AI-driven anomaly detection algorithms?

Automate dataset analysis Signup and view all the answers

What type of networks are used in NADS for unsupervised anomaly detection?

Artificial Neural Networks (ANNs) Signup and view all the answers

What is the purpose of Fuzzy Logic in NADS?

To determine if malicious activity is occurring on a network Signup and view all the answers

What is the advantage of using AI in NADS?

Reduced human analyst workload and improved anomaly detection accuracy Signup and view all the answers

What is the role of machine learning in NADS?

To analyze network traffic and identify anomalies Signup and view all the answers

What is the purpose of real-time analysis in AI-driven anomaly detection?

To allow for immediate detection of anomalies and quick response times Signup and view all the answers

What is the role of Genetic Algorithms in Fuzzy Logic?

To create a network profile using recent data Signup and view all the answers