Decoding AI Deception: Poisoning Attack

Hi! Welcome to my series of blogposts, “Decoding AI Deception” wherein we will take a closer look into each kind of adversarial AI attack. This post covers the details of poisoning attack comprising common types of poisoning attacks, their applicable cases, vulnerabilitiesof models that are exploited by these attacks, and remedial measures. Poisoning Attack and its Types As we all know from previous post that poisoning attack is the form of adversarial AI attack that is used to corrupt data intended for either training or retraining of a model. It has few common forms which are as follows: – Applicable […]

Understanding different Unsupervised learning models using a single example

As a part of previous blogpost and in continuation with similar lines, this blogpost will try to clarify the difference and purpose of each kind of Unsupervised learning model using a common example across all these models. Apart from defining each model type, this post will highlight if any models could be used interchangeably for certain scenarios. Types of Unsupervised Learning Models Understanding Models using an Example Let’s consider the example of customer segmentation in a retail store. The store wants to group its customers based on their purchasing behavior and preferences, in order to better target their marketing campaigns […]