75 citations · 143 across the 9 of their papers we have counts for
9 papers
Security Theater: On the Vulnerability of Classifiers to Exploratory Attacks
Tegjyot Singh Sethi, Mehmed Kantardzic, Joung Woo Ryu
The increasing scale and sophistication of cyberattacks has led to the adoption of machine learning based classification techniques, at the core of cybersecurity systems. These tec…
A Dynamic-Adversarial Mining Approach to the Security of Machine Learning
Tegjyot Singh Sethi, Mehmed Kantardzic, Lingyu Lyua +1
Operating in a dynamic real world environment requires a forward thinking and adversarial aware design for classifiers, beyond fitting the model to the training data. In such scena…
Handling Adversarial Concept Drift in Streaming Data
Tegjyot Singh Sethi, Mehmed Kantardzic
Classifiers operating in a dynamic, real world environment, are vulnerable to adversarial activity, which causes the data distribution to change over time. These changes are tradit…
On the Reliable Detection of Concept Drift from Streaming Unlabeled Data
Tegjyot Singh Sethi, Mehmed Kantardzic
Classifiers deployed in the real world operate in a dynamic environment, where the data distribution can change over time. These changes, referred to as concept drift, can cause th…
Evaluating Complex Task through Crowdsourcing: Multiple Views Approach
Lingyu Lyu, Mehmed Kantardzic
With the popularity of massive open online courses, grading through crowdsourcing has become a prevalent approach towards large scale classes. However, for getting grades for compl…
Data Driven Exploratory Attacks on Black Box Classifiers in Adversarial Domains
Tegjyot Singh Sethi, Mehmed Kantardzic
While modern day web applications aim to create impact at the civilization level, they have become vulnerable to adversarial activity, where the next cyber-attack can take any shap…