6 citations · 11 across the 9 of their papers we have counts for
9 papers
Transparency and Privacy: The Role of Explainable AI and Federated Learning in Financial Fraud Detection
Tomisin Awosika, Raj Mani Shukla, Bernardi Pranggono
Fraudulent transactions and how to detect them remain a significant problem for financial institutions around the world. The need for advanced fraud detection systems to safeguard…
A Hybrid Approach using ARIMA, Kalman Filter and LSTM for Accurate Wind Speed Forecasting
Manas Ranjan Mohapatra, Rahul Radhakrishnan, Raj Mani Shukla
Present energy demand and modernization are leading to greater fossil fuel consumption, which has increased environmental pollution and led to climate change. Hence to decrease dep…
Cross Device Federated Intrusion Detector for Early Stage Botnet Propagation in IoT
Angela Grace Famera, Raj Mani Shukla, Suman Bhunia
A botnet is an army of zombified computers infected with malware and controlled by malicious actors to carry out tasks such as Distributed Denial of Service (DDoS) attacks. Billion…
Histopathological Image Classification and Vulnerability Analysis using Federated Learning
Sankalp Vyas, Amar Nath Patra, Raj Mani Shukla
Healthcare is one of the foremost applications of machine learning (ML). Traditionally, ML models are trained by central servers, which aggregate data from various distributed devi…
Give and Take: Federated Transfer Learning for Industrial IoT Network Intrusion Detection
Lochana Telugu Rajesh, Tapadhir Das, Raj Mani Shukla +1
The rapid growth in Internet of Things (IoT) technology has become an integral part of today's industries forming the Industrial IoT (IIoT) initiative, where industries are leverag…
Analyzing the vulnerabilities in SplitFed Learning: Assessing the robustness against Data Poisoning Attacks
Aysha Thahsin Zahir Ismail, Raj Mani Shukla
Distributed Collaborative Machine Learning (DCML) is a potential alternative to address the privacy concerns associated with centralized machine learning. The Split learning (SL) a…
Analyzing the Impact of Adversarial Examples on Explainable Machine Learning
Prathyusha Devabhakthini, Sasmita Parida, Raj Mani Shukla +2
Adversarial attacks are a type of attack on machine learning models where an attacker deliberately modifies the inputs to cause the model to make incorrect predictions. Adversarial…
A Deep Learning-based Compression and Classification Technique for Whole Slide Histopathology Images
Agnes Barsi, Suvendu Chandan Nayak, Sasmita Parida +1
This paper presents an autoencoder-based neural network architecture to compress histopathological images while retaining the denser and more meaningful representation of the origi…
Deep Ensemble Learning-based Approach to Real-time Power System State Estimation
Narayan Bhusal, Raj Mani Shukla, Mukesh Gautam +2
Power system state estimation (PSSE) is commonly formulated as weighted least-square (WLS) algorithm and solved using iterative methods such as Gauss-Newton methods. However, itera…