Research Experience
Published / Presented
A COMPREHENSIVE INVESTIGATION OF RECONNAISSANCE THREATS AND ITS REMEDIATION
Bangladesh University | November 2024
ABSTRACT: The cyber world of today extends beyond the internet. Critical infrastructures, embedded systems, and telecommunication networks are all part of this interconnected network. Attacks by malicious actors targeting vital infrastructure pose a serious risk to government and commercial activities. Successful businesses rely on quick and simple network access, which also increases the vulnerability of important data to cybercriminals. Attackers and hackers of today are proficient and well-prepared with a variety of hacking tools to quickly take advantage of a little weakness. The initial stage of a cyberattack is known as reconnaissance, and this study will examine this stage to provide practical defenses. The methodology of this paper's complete approach to cybersecurity is Penetration Testing of Systems, Defending Against Foot printing and Reconnaissance, and foot printing and Reconnaissance. Understanding the techniques and resources employed to get data on possible targets is the first step. The second portion is dedicated to tactics and equipment for countering this kind of collection of information. The last stage uses simulated attacks to assess the security of the systems. The systematic approach seeks to improve the entire cybersecurity posture by the systematic identification, assessment, and mitigation of possible risks.
Keywords: Reconnaissance, Penetration Testing, Cyber Security, Ethical Hacking, OSINT.
Communication and Bandwidth Optimization Technique Using MikroTik
IJARCCE | May 2024
ABSTRACT: Wide Area Network (WAN) is one of the most important parts of communication technology in the world, and the Internet is an idle example for WAN. But, without bandwidth nobody is able to communicate via the internet. Moreover, day to day increases the number of user traffic on the internet. In this case medical science also consumes a huge number of bandwidths by the A.I operation technique. Therefore, bandwidth distribution is one of the vital issues for the technology of communication. This paper shows how MikroTik will be able to fulfill the needs of bandwidth management in future.
Keywords: Internet, Traffic, Bandwidth, MikroTik.
Working Papers & Under Review
Bilingual Speech Emotion Recognition
Under ReviewSubmitted to: Journal of Audio Processing, 2025
Research focused on developing a transformer-based model capable of accurately recognizing emotions from a Bengali-English code-mixed speech dataset.
Ongoing Research
AppleNetV1: An Efficient Convolutional Neural Network with Multilingual Decision Support for Automated Apple Leaf Disease Detection
MSc Thesis Project | Ongoing Research
ABSTRACT: Apple production is one of the most essential elements in the international agricultural business, but it is also one of the most threatened sectors. It is extremely susceptible to various infections such as Apple Scab, Black Rot, Cedar Apple Rust. These pathologies can rapidly extend, thereby resulting in significant yield reduction and economic instability for farmers. The major drawback of computer-assisted analysis systems is their reliance on manual interpretation by experts to arrive at a diagnosis of a disease or consuming, expensive, and prone to the subjective errors of humanity. Additionally, it is made worse by the fact that agricultural experts in rural regions are often scarce to respond to the problem. Thus, there is an immediate need for an accurate, automated, and accessible solution that could help in early detection and treatment of leaf diseases to ensure crop sustainability. To effectively address such challenges, this research proposes AppleNetV1, a robust and light deep learning framework, which adopts a custom designed Sequential Convolutional Neural Network (CNN) architecture. By using hierarchical features extraction tuned for diagnosing apple leaves, "AppleNetV1" achieves a computational efficiency and accuracy at a remarkable testing accuracy 99.57% on basic categories of apple leaves. The tool is implemented using a user-friendly Streamlit web interface integrated with a novel native (Bengali) prescription system, effectively bridging the technological gap between rural farmers. Such a holistic strategy will ensure low latency performance and high levels of diagnostic accuracy, enabling it to be a scalable foundation for future real-field diagnostics.
Keywords: Apple Leaf Disease, AppleNetV1, Custom CNN, Deep Learning, Streamlit, Precision Agriculture, Native Prescription.
Potato Disease Detection using CNN
Developing a lightweight, highly efficient neural network model specifically targeting early blight and late blight in potatoes.
Mobile Bandwidth Optimization under Emergency
Ongoing project experimenting with simulated disaster scenarios to ensure continuous mobile network connectivity.