4 citations · 10 across the 8 of their papers we have counts for
8 papers
On Trojan Signatures in Large Language Models of Code
Aftab Hussain, Md Rafiqul Islam Rabin, Mohammad Amin Alipour
Trojan signatures, as described by Fields et al. (2021), are noticeable differences in the distribution of the trojaned class parameters (weights) and the non-trojaned class parame…
Measuring Impacts of Poisoning on Model Parameters and Neuron Activations: A Case Study of Poisoning CodeBERT
Aftab Hussain, Md Rafiqul Islam Rabin, Navid Ayoobi +1
Large language models (LLMs) have revolutionized software development practices, yet concerns about their safety have arisen, particularly regarding hidden backdoors, aka trojans.…
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
Aftab Hussain, Md Rafiqul Islam Rabin, Bowen Xu +2
Although deep neural models substantially reduce the overhead of feature engineering, the features readily available in the inputs might significantly impact training cost and the…
DIAR: Removing Uninteresting Bytes from Seeds in Software Fuzzing
Aftab Hussain, Mohammad Amin Alipour
Software fuzzing mutates bytes in the test seeds to explore different behaviors of the program under test. Initial seeds can have great impact on the performance of a fuzzing campa…
FMViz: Visualizing Tests Generated by AFL at the Byte-level
Aftab Hussain, Mohammad Amin Alipour
Software fuzzing is a strong testing technique that has become the de facto approach for automated software testing and software vulnerability detection in the industry. The random…
Data Poisoning: Lightweight Soft Fault Injection for Python
Mohammad Amin Alipour, Alex Groce
This paper introduces and explores the idea of data poisoning, a light-weight peer-architecture technique to inject faults into Python programs. This method requires very small mod…