most citedPerformance analysis of Machine learning algorithms for predicting malware

19 citations

5 papers

cs.CR202612 cited

ShielDroid: A Hybrid Approach Integrating Machine and Deep Learning for Android Malware Detection

Md Faisal Ahmed, Zarin Tasnim Biash, Abu Raihan Shakil +4

The rapid advancement of modern technology has led to a significant increase in the use of smart devices, such as smartphones and tablets, resulting in the widespread adoption of m…

cs.CR202619 cited

Performance analysis of Machine learning algorithms for predicting malware

ABM. Adnan Azmee, Pranto Protim Choudhury, Md. Aosaful Alam +2

Malware poses a persistent and evolving threat to modern computing systems, making accurate and timely detection a critical cybersecurity challenge. Traditional signature-based ant…

cs.AI2026

Truth Lies Deep: Countering Semantic Camouflage via Latent Intent Verification

Md. Hasib Ur Rahman

Safety alignment in Large Language Models (LLMs) is often superficial, relying on refusal mechanisms that trigger only at the final stages of generation without erasing the foundat…

math-ph2026

From Bopp Shifts to Toroidal Shadows: K-Theoretic Gap Labels in Noncommutative Quantum Mechanics

S. Hasibul Hassan Chowdhury

We study Bopp shifts in two-dimensional noncommutative quantum mechanics (NCQM) through a functorial lens. A nondegenerate NCQM sector with central character $(\hbar,\vartheta,B_{\…

hep-th20261 cited

Effect of Moduli Redefinitions on Fibre Inflation

Dibya Chakraborty, Mishaal Hai, Sayeda Tashnuba Jahan +2

In this paper, we have discovered a new avenue of fibre inflation in perturbative large volume scenario (pLVS) due to the redefinition of the base modulus. pLVS offers a novel regi…