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, […]
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 […]
Backdoor: The Undercover Agent
As I was reading about backdoors sometime back, I could relate them to undercover agents. But much before getting to that, let’s see what backdoors are. A Backdoor in the world of internet and computerized systems, is like a stealthy / secret door that allows a hacker to get into a system by bypassing its security systems. For ML models, it’s pretty much the same except that these can be more scheming yet easier to deploy in ML models. Imagining huge applications running on ML models with such backdoors within, can be really worrisome. Furthermore, these backdoors up until sometime […]