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
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
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
Proceedings of the IEEE International Conference on Omni-layer Intelligent Systems, 2023
2022
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
CoRR, 2022
PerDoor: Persistent Non-Uniform Backdoors in Federated Learning using Adversarial Perturbations.
CoRR, 2022
Proceedings of the Progress in Cryptology, 2022
2021
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
IACR Cryptol. ePrint Arch., 2021
IACR Cryptol. ePrint Arch., 2021
PARL: Enhancing Diversity of Ensemble Networks to Resist Adversarial Attacks via Pairwise Adversarially Robust Loss Function.
CoRR, 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
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
IACR Cryptol. ePrint Arch., 2020
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
CoRR, 2019
Proceedings of the IEEE International Symposium on Hardware Oriented Security and Trust, 2019
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
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
IEEE Embed. Syst. Lett., 2018
A 0.16pJ/bit Recurrent Neural Network Based PUF for Enhanced Machine Learning Atack Resistance.
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
Proceedings of the 2016 3rd International Conference on Recent Advances in Information Technology (RAIT), 2016
Proceedings of the 2016 ACM/IEEE International Conference on Formal Methods and Models for System Design, 2016