Chris Wen's Blog

Malware ReviewThis article introduces two major malware families, Zeus and Fareit. Zeus is a banking trojanthat steals online financial credentials through techniques such as keylogging and formgrabbing. Fareit is a credential-stealing trojan that collects passwords, usernames, and walletdata, often delivering other malware as well. The study outlines their impacts on target systemsand highlights key traffic patterns, providing insight into how these threats can be identifiedthrough network a...

Naive BayesIntroduction to Naive BayesNaive Bayes is a probability-based machine learning algorithm. It is based on Bayes’ Theorem and assumes that all features are independent of each other. This independence assumption is why it is called “naive”. Although this assumption is often not fully true in real-world data, Naive Bayes still performs very well in many practical tasks. Common applications include: Text classification Spam email detection Sentiment analysis Document classification Ne...

PerceptronWhat Is a Perceptron?A Perceptron is a simple binary classification model. It receives multiple input signals and produces one output signal. The output of a perceptron can only be one of two values: 0 1 A perceptron with two input signals can be represented as: x_1, x_2 \rightarrow yWhere: (x_1, x_2) are input signals. (w_1, w_2) are weights. (y) is the output signal. The circle, or node, is called a neuron. Each input signal is multiplied by its corresponding weight before be...

Logistic RegressionLogistic Regression is a binary classification technique that assumes numeric input variables with a Gaussian distribution. Although this assumption is not mandatory, the algorithm performs well even if the data does not adhere to this pattern. Logistic regression calculates coefficients for each input variable, combining them linearly into a regression function and applying a logistic transformation. While it is simple and fast, its effectiveness depends on the characteris...

Ways to Measure DistanceThere are several ways to measure distance between two points in a multidimensional space. The choice of distance metric depends on the specific problem and the characteristics of the data. Euclidean DistanceThe Euclidean distance is the straight-line distance between two points in a multidimensional space. It is calculated as the square root of the sum of the squared differences between the corresponding coordinates of the two points. 1d(A, B) = sqrt((x1 - y1)^2 + (x2...

Logistic RegressionLinear RegressionLinear regression is a statistical method for modeling the relationship between a dependent variable and one or more independent variables. It is used to predict the value of the dependent variable based on the values of the independent variables. Working PrincipleThe linear regression model is based on the assumption that there is a linear relationship between the dependent variable and the independent variables. The model is trained on a dataset of input-...

KNN AlgorithmsK-Nearest Neighbors (KNN) is a simple, non-parametric, and lazy learning algorithm used for classification and regression tasks. Working PrincipleThe KNN algorithm works by finding the K nearest neighbors to a given data point and making predictions based on the majority class (for classification) or the average value (for regression) of those neighbors.Normally, when we do prediction, there are two main methods: classification and regression. KNN can be used for both of these m...

BackgroundMachine learning (ML) components are increasingly being deployed in critical applications, form computer vision to cybersecurity. However, the data-driven nature of ML introduces new security challenges compared to traditional knowledge-based AI systems. Adversaries can exploit vulnerabilities in ML models through a variety of adversarial attacks, posing significant risks to the integrity, availability, and confidentiality of these systems. Key Attack TypesThe taxonomy of adversaria...

Comparative Analysis of Classification AlgorithmsAbstractThis report provides a comprehensive analysis of the performance of three popular classification algorithms:Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Support Vector Machines (SVM) and Multilayer Perceptron.The purpose of the study is to evaluate and compare these algorithms based on key performance metrics such as accuracy, precision, recall, F1-score, and false alarm rate (www.evidentlyai.com, n.d.), using two dif...

Dataset IntroductionNSL-KDDThe NSL-KDD dataset is a dataset for intrusion detection, which is a type of supervised learning problem. It consists of a large number of network traffic records that are labeled as either normal or malicious. The dataset contains a total of 41,478 network traffic records, which are categorized into 10 different types of attacks, such as DoS, Probe, U2R, R2L, etc. The dataset is publicly available and can be downloaded from the following link: https://www.unb.ca/ci...