Manaar Alam

Orcid: 0000-0002-3338-2944

According to our database1, Manaar Alam authored at least 57 papers between 2016 and 2025.

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Bibliography

2025
DRAUN: An Algorithm-Agnostic Data Reconstruction Attack on Federated Unlearning Systems.
CoRR, June, 2025

Veritas: Deterministic Verilog Code Synthesis from LLM-Generated Conjunctive Normal Form.
CoRR, June, 2025

ReVeil: Unconstrained Concealed Backdoor Attack on Deep Neural Networks using Machine Unlearning.
CoRR, February, 2025

Guardian of the Ensembles: Introducing Pairwise Adversarially Robust Loss for Resisting Adversarial Attacks in DNN Ensembles.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

RTL-Breaker: Assessing the Security of LLMs Against Backdoor Attacks on HDL Code Generation.
Proceedings of the Design, Automation & Test in Europe Conference, 2025

2024
Get Rid of Your Trail: Remotely Erasing Backdoors in Federated Learning.
IEEE Trans. Artif. Intell., December, 2024

Stealing the Invisible: Unveiling Pre-Trained CNN Models Through Adversarial Examples and Timing Side-Channels.
IEEE J. Emerg. Sel. Topics Circuits Syst., December, 2024

Decision Guided Robust DL Classification of Adversarial Images Combining Weaker Defenses.
IEEE J. Emerg. Sel. Topics Circuits Syst., December, 2024

On the Instability of Softmax Attention-Based Deep Learning Models in Side-Channel Analysis.
IEEE Trans. Inf. Forensics Secur., 2024

LLMPot: Automated LLM-based Industrial Protocol and Physical Process Emulation for ICS Honeypots.
CoRR, 2024

Detecting Backdoor Attacks in Black-Box Neural Networks through Hardware Performance Counters.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

AdvHunter: Detecting Adversarial Perturbations in Black-Box Neural Networks through Hardware Performance Counters.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

Ignorance is not Bliss: A Novel Ensemble Method to Counter Adversarial Attacks on Deep Learning Models.
Proceedings of the 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD), 2024

"Hello? Is There Anybody in There?" Leakage Assessment of Differential Privacy Mechanisms in Smart Metering Infrastructure.
Proceedings of the Applied Cryptography and Network Security, 2024

2023
Learn from Your Faults: Leakage Assessment in Fault Attacks Using Deep Learning.
J. Cryptol., July, 2023

Birds of the Same Feather Flock Together: A Dual-Mode Circuit Candidate for Strong PUF-TRNG Functionalities.
IEEE Trans. Computers, June, 2023

"Whispering MLaaS" Exploiting Timing Channels to Compromise User Privacy in Deep Neural Networks.
IACR Trans. Cryptogr. Hardw. Embed. Syst., 2023

HowkGPT: Investigating the Detection of ChatGPT-generated University Student Homework through Context-Aware Perplexity Analysis.
CoRR, 2023

PerDoor: Persistent Backdoors in Federated Learning using Adversarial Perturbations.
Proceedings of the IEEE International Conference on Omni-layer Intelligent Systems, 2023

2022
Exploring Bitslicing Architectures for Enabling FHE-Assisted Machine Learning.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

<i>NN-Lock</i>: A Lightweight Authorization to Prevent IP Threats of Deep Learning Models.
ACM J. Emerg. Technol. Comput. Syst., 2022

Resisting Adversarial Attacks in Deep Neural Networks using Diverse Decision Boundaries.
CoRR, 2022

On the Evaluation of User Privacy in Deep Neural Networks using Timing Side Channel.
CoRR, 2022

PerDoor: Persistent Non-Uniform Backdoors in Federated Learning using Adversarial Perturbations.
CoRR, 2022

TransNet: Shift Invariant Transformer Network for Side Channel Analysis.
Proceedings of the Progress in Cryptology, 2022

2021
RASSLE: Return Address Stack based Side-channel LEakage.
IACR Trans. Cryptogr. Hardw. Embed. Syst., 2021

Victims Can Be Saviors: A Machine Learning-based Detection for Micro-Architectural Side-Channel Attacks.
ACM J. Emerg. Technol. Comput. Syst., 2021

A Tale of Twin Primitives: Single-chip Solution for PUFs and TRNGs.
IACR Cryptol. ePrint Arch., 2021

TransNet: Shift Invariant Transformer Network for Power Attack.
IACR Cryptol. ePrint Arch., 2021

PARL: Enhancing Diversity of Ensemble Networks to Resist Adversarial Attacks via Pairwise Adversarially Robust Loss Function.
CoRR, 2021

A survey on adversarial attacks and defences.
CAAI Trans. Intell. Technol., 2021

Deep Learning assisted Cross-Family Profiled Side-Channel Attacks using Transfer Learning.
Proceedings of the 22nd International Symposium on Quality Electronic Design, 2021

A Good Anvil Fears No Hammer: Automated Rowhammer Detection Using Unsupervised Deep Learning.
Proceedings of the Applied Cryptography and Network Security Workshops, 2021

2020
LAMBDA: Lightweight Assessment of Malware for emBeddeD Architectures.
ACM Trans. Embed. Comput. Syst., 2020

Neural Network-based Inherently Fault-tolerant Hardware Cryptographic Primitives without Explicit Redundancy Checks.
ACM J. Emerg. Technol. Comput. Syst., 2020

Improving accuracy of HPC-based malware classification for embedded platforms using gradient descent optimization.
J. Cryptogr. Eng., 2020

TranSCA: Cross-Family Profiled Side-Channel Attacks using Transfer Learning on Deep Neural Networks.
IACR Cryptol. ePrint Arch., 2020

Leakage Assessment in Fault Attacks: A Deep Learning Perspective.
IACR Cryptol. ePrint Arch., 2020

Deep-Lock: Secure Authorization for Deep Neural Networks.
CoRR, 2020

RAPPER: Ransomware Prevention via Performance Counters.
CoRR, 2020

HARDY: Hardware based Analysis for malwaRe Detection in embedded sYstems.
Proceedings of the 33rd IEEE International System-on-Chip Conference, 2020

2019
IPA: an Instruction Profiling-Based Micro-architectural Side-Channel Attack on Block Ciphers.
J. Hardw. Syst. Secur., 2019

Enhancing Fault Tolerance of Neural Networks for Security-Critical Applications.
CoRR, 2019

RATAFIA: Ransomware Analysis using Time And Frequency Informed Autoencoders.
Proceedings of the IEEE International Symposium on Hardware Oriented Security and Trust, 2019

How Secure are Deep Learning Algorithms from Side-Channel based Reverse Engineering?
Proceedings of the 56th Annual Design Automation Conference 2019, 2019

In-situ Extraction of Randomness from Computer Architecture Through Hardware Performance Counters.
Proceedings of the Smart Card Research and Advanced Applications, 2019

Deep Learning Based Diagnostics for Rowhammer Protection of DRAM Chips.
Proceedings of the 28th IEEE Asian Test Symposium, 2019

A 0.16pJ/bit recurrent neural network based PUF for enhanced machine learning attack resistance.
Proceedings of the 24th Asia and South Pacific Design Automation Conference, 2019

2018
Customized Instructions for Protection Against Memory Integrity Attacks.
IEEE Embed. Syst. Lett., 2018

A 0.16pJ/bit Recurrent Neural Network Based PUF for Enhanced Machine Learning Atack Resistance.
CoRR, 2018

Adversarial Attacks and Defences: A Survey.
CoRR, 2018

RAPPER: Ransomware Prevention via Performance Counters.
CoRR, 2018

Side-Channel Assisted Malware Classifier with Gradient Descent Correction for Embedded Platforms.
Proceedings of the PROOFS 2018, 2018

2017
Performance Counters to Rescue: A Machine Learning based safeguard against Micro-architectural Side-Channel-Attacks.
IACR Cryptol. ePrint Arch., 2017

Tackling the Time-Defence: An Instruction Count Based Micro-architectural Side-Channel Attack on Block Ciphers.
Proceedings of the Security, Privacy, and Applied Cryptography Engineering, 2017

2016
A novel parallel search technique for optimization.
Proceedings of the 2016 3rd International Conference on Recent Advances in Information Technology (RAIT), 2016

SmashClean: A hardware level mitigation to stack smashing attacks in OpenRISC.
Proceedings of the 2016 ACM/IEEE International Conference on Formal Methods and Models for System Design, 2016


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