Often we get confused between different types of Supervised learning models available. This is majorly due to lack of understanding of the goal and applicability of each kind of model. In this blogpost, I will try to clarify the difference and purpose of each kind of Supervised learning model using a common example across all these models. Apart from defining each model type, I will also mention if any models could be used interchangeably for certain scenarios. Types of Supervised Learning Models Understanding Models using an Example Let’s use the example of predicting whether a person has diabetes based on […]
Key Research Work on AI against Traditional Cybersecurity Measures
With the intelligence accompanied, AI has tapped enormous strength to stealthily bypass traditional cybersecurity measures. This blogpost enlists some key research work available in public domain that bring out insightful results on how AI in its adversarial form can be used to fool or bypass traditional cybersecurity measures. Such research work (by and large provide all the more reason why current security measures need to armor for bigger and conniving threats lurking around.
Comparative Assessment of Critical Adversarial AI Attacks
Often we come across various adversarial AI attacks. Over the time, there have been numerous attacks surfacing with extensive use of one or more AI model(s) together in any application. In this blog post, a one stop platform summarizing the critical adversarial AI attacks is provided. The comparative assessment of these attacks is performed on certain basic features – Modus Operandi, Type of information affected, Phase of AI operation, and More Realizable Applicable Case Study/ Use Case (Examples are not limited to the ones listed below. The examples below are only for better realization purpose). It is worth noting that, […]
Comparative Assessment of Critical AI Models
This blog post is a one stop platform for summary of different AI models that are in predominant use. The comparative assessment of these models is based on various parameters such as – Definition, Process, Main Learning Approach, Pros, Cons, and Applications. The idea is to summarize these models and make it available for a quick view. Note that the information about the model’s is not limited to the contents in this post. Readers are highly encouraged to refer valid sources for additional and detailed information. ModelDefinitionProcess Main Learning ApproachProsConsApplicationsLinear RegressionA model that predicts a continuous output by finding the […]
Triggered vs. Triggerless Backdoor Attacks using a Single Example
In previous blog post, there was an introduction to backdoor attack and its various forms. In this post, I will provide the basic difference between the two forms of attacks using a single example so as to understand the difference in a more precise manner and I will finally provide a comparative assessment of both the forms using different properties/ features. Triggered is the form where a specific input is injected with a trigger / adversarial information so as to activate the malicious behavior of the model. Triggerless is the form which does not inject a typical trigger or adversarial […]