NPerseus
Computer Science & Engineering · DTU
Neural Security · Privacy · Digital Forensics

Secure intelligence.
Verifiable by design.

Inspired by Neural intelligence and Perseus, the legendary Greek hero, NPerseus represents our pursuit of resilient, trustworthy, and secure intelligent systems.

We are a research group in the Department of Computer Science & Engineering at Delhi Technological University working at the intersection of neural network security and privacy, digital and multimedia forensics, secure communication, and copyright protection. Our research develops robust learning systems, privacy-preserving methods, forensic techniques, and secure information technologies for trustworthy digital environments.

Deepfake DetectionDigital ForensicsDeep ClusteringAdversarial MLReversible Data HidingImage SteganographyAI Privacy & SecurityTrustworthy AIBackdoor Defense

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More from the lab
129Reviewed publications56 journal · 62 conference
39Patent records21 granted · 18 published
15Active people3 faculty · 12 researchers
6Ph.D. scholarsAcross the research team
4Research directionsSecurity, privacy & forensics
5AlumniPart of the lab network

23 listed works in 2026 · Publications are deduplicated across faculty and members. Patent statuses follow source records. Browse publications →

Faculty

Faculty at DTU

Computer Science & Engineering, Delhi Technological University.

Meet the team →

Dr. Rajeev Kumar

Assistant Professor

Leads the lab's work on security and privacy of deep neural networks, data hiding and multimedia forensics. Ph.D. (University of Delhi, 2017) with a post-doctorate at Kyungil University, South Korea and an NRF Korea Brain Pool Plus Fellowship.

Privacy & Security of Deep Neural NetworksReversible Data Hiding & WatermarkingImage & Text Steganography

Dr. Anurag Goel

Assistant Professor

Works on machine learning, deep learning and deep clustering, graph algorithms, image processing, AI for social good and computational creativity. He earned his Ph.D. in CSE from IIIT-Delhi in 2023 with a thesis on Deep Clustering and received IIIT-Delhi’s M.Tech. Gold Medal in 2017.

Machine LearningDeep LearningDeep Clustering

Ms. Anukriti Kaushal

Assistant Professor

Researches manipulated-image detection, deepfake generation and detection, and digital image integrity. M.Tech. in Software Engineering (DTU) and a Ph.D. in progress at DTU on intelligent image-forensics strategies.

Image ForensicsDeepfake DetectionDeep Learning
Research areas

What we study

Projects & research →
Research output

Recent publications

Papers and preprints from the group, newest first.

All 129 records →
Research focus · security × data hiding

Reversible adversarial perturbations

Studying perturbations that can be removed to recover the original image, connecting adversarial robustness with reversible data hiding.

A Survey on Reversible Adversarial Perturbations

Nikhil Gupta, Ankur, Rajeev Kumar · 2026

Conference paper

Read the survey ↗
The people

Research students

Full team →

6 of 12 researchersExplore at your pace

Ayush Kumar

B.Tech Student

Android Security, Vulnerability Research and Secure Systems

Platform engineering

Built and maintains the NPerseus website and research tools.

NPerseus

Ajit Kumar Yadav

Full-time Ph.D. Candidate

Reversible Data Hiding in Encrypted Images, Image Security, Backdoor Detection in Neural Networks

Latest listed publication

Adaptive Weighted Predictor for Checkerboard based Reversible Data Hiding in Encrypted Images

2026 · Conference paper

Mahaveer Prasad

M.Tech Student

Adversarial Machine Learning, Backdoor and Data-Poisoning Defense, Network Intrusion Detection, Android Malware Analysis

Latest listed publication

A Unified Multi-Signal Indicator Framework for Backdoor Detection and Label Correction in Deep Neural Networks

2026 · Conference paper

Nikhil Gupta

Full-time Ph.D. Candidate

Enabling Technologies for Trustworthy Artificial Intelligence, Adversarial Machine Learning, AI Security and Robustness

Latest listed publication

A Survey on Reversible Adversarial Perturbations

2026 · Conference paper

From the lab

News & achievements

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