Manaar Alam
Manaar Alam
Post-Doctoral Associate, New York University Abu Dhabi
Verified email at - Homepage
Cited by
Cited by
Adversarial attacks and defences: A survey
A Chakraborty, M Alam, V Dey, A Chattopadhyay, D Mukhopadhyay
arXiv preprint arXiv:1810.00069, 2018
A survey on adversarial attacks and defences
A Chakraborty, M Alam, V Dey, A Chattopadhyay, D Mukhopadhyay
CAAI Transactions on Intelligence Technology 6 (1), 25-45, 2021
Performance counters to rescue: A machine learning based safeguard against micro-architectural side-channel-attacks
M Alam, S Bhattacharya, D Mukhopadhyay, S Bhattacharya
Cryptology ePrint Archive, 2017
Rapper: Ransomware prevention via performance counters
M Alam, S Sinha, S Bhattacharya, S Dutta, D Mukhopadhyay, ...
arXiv preprint arXiv:2004.01712, 2020
RATAFIA: ransomware analysis using time and frequency informed autoencoders
M Alam, S Bhattacharya, S Dutta, S Sinha, D Mukhopadhyay, ...
2019 IEEE International Symposium on Hardware Oriented Security and Trust …, 2019
How Secure are Deep Learning Algorithms from Side-Channel based Reverse Engineering?
M Alam, D Mukhopadhyay
Proceedings of the 56th Annual Design Automation Conference, 226:1--226:2, 2019
Deep learning assisted cross-family profiled side-channel attacks using transfer learning
D Thapar, M Alam, D Mukhopadhyay
2021 22nd International Symposium on Quality Electronic Design (ISQED), 178-185, 2021
Deep learning based diagnostics for rowhammer protection of DRAM chips
A Chakraborty, M Alam, D Mukhopadhyay
2019 IEEE 28th Asian Test Symposium (ATS), 86-865, 2019
SmashClean: A hardware level mitigation to stack smashing attacks in OpenRISC
M Alam, DB Roy, S Bhattacharya, V Govindan, RS Chakraborty, ...
2016 ACM/IEEE International Conference on Formal Methods and Models for …, 2016
Deep-Lock: Secure Authorization for Deep Neural Networks
M Alam, S Saha, D Mukhopadhyay, S Kundu
arXiv preprint arXiv:2008.05966, 2020
Enhancing fault tolerance of neural networks for security-critical applications
M Alam, A Bag, DB Roy, D Jap, J Breier, S Bhasin, D Mukhopadhyay
arXiv preprint arXiv:1902.04560, 2019
LAMBDA: Lightweight assessment of malware for emBeddeD architectures
SP Kadiyala, M Alam, Y Shrivastava, S Patranabis, MFB Abbas, ...
ACM Transactions on Embedded Computing Systems (TECS) 19 (4), 1-31, 2020
Customized instructions for protection against memory integrity attacks
DB Roy, M Alam, S Bhattacharya, V Govindan, F Regazzoni, ...
IEEE Embedded Systems Letters 10 (3), 91-94, 2018
Victims Can Be Saviors: A Machine Learning--based Detection for Micro-Architectural Side-Channel Attacks
M Alam, S Bhattacharya, D Mukhopadhyay
ACM Journal on Emerging Technologies in Computing Systems (JETC) 17 (2), 1-31, 2021
A 0.16 pJ/bit recurrent neural network based PUF for enhanced machine learning attack resistance
N Shah, M Alam, DP Sahoo, D Mukhopadhyay, A Basu
Proceedings of the 24th Asia and South Pacific Design Automation Conference …, 2019
Side-Channel Assisted Malware Classifier with Gradient Descent Correction for Embedded Platforms.
M Alam, D Mukhopadhyay, SP Kadiyala, SK Lam, T Srikanthan
PROOFS@ CHES, 1-15, 2018
RASSLE: return address stack based side-channel leakage
A Chakraborty, S Bhattacharya, M Alam, S Patranabis, D Mukhopadhyay
IACR Transactions on Cryptographic Hardware and Embedded Systems 2, 275-303, 2021
A novel parallel search technique for optimization
M Alam, S Chatterjee, H Banka
2016 3rd International Conference on Recent Advances in Information …, 2016
Leakage assessment in fault attacks: a deep learning perspective
S Saha, M Alam, A Bag, D Mukhopadhyay, P Dasgupta
Cryptology ePrint Archive, 2020
Tackling the time-defence: an instruction count based micro-architectural side-channel attack on block ciphers
M Alam, S Bhattacharya, D Mukhopadhyay
International Conference on Security, Privacy, and Applied Cryptography …, 2017
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