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112 publications
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∙ 04/27/2023

Holo-Block Chain: A Hybrid Approach for Secured IoT Healthcare Ecosystem

The Internet-of-Things (IoT) is an imminent and corporal technology that...

0 Asad Aftab, et al. ∙

∙ 08/29/2022

Reliable and Resilient AI and IoT-based Personalised Healthcare Services: A Survey

Recent technological and economic developments have transformed the heal...

0 Najma Taimoor, et al. ∙

∙ 08/16/2022

EXTENT: Enabling Approximation-Oriented Energy Efficient STT-RAM Write Circuit

Spin Transfer Torque Random Access Memory (STT-RAM) has garnered interes...

0 Saeed Seyedfaraji, et al. ∙

∙ 08/02/2022

SMART: Investigating the Impact of Threshold Voltage Suppression in an In-SRAM Multiplication/Accumulation Accelerator for Accuracy Improvement in 65 nm CMOS Technology

State-of-the-art in-memory computation has recently emerged as the most ...

0 Saeed Seyedfaraji, et al. ∙

∙ 07/24/2022

On the Validation of Multi-Level Personalised Health Condition Model

This paper presents a verification-based methodology to validate the mod...

0 Najma Taimoor, et al. ∙

∙ 04/15/2022

AID: Accuracy Improvement of Analog Discharge-Based in-SRAM Multiplication Accelerator

This paper presents a novel circuit (AID) to improve the accuracy of an ...

0 Saeed Seyedfaraji, et al. ∙

∙ 09/07/2021

BioNetExplorer: Architecture-Space Exploration of Bio-Signal Processing Deep Neural Networks for Wearables

In this work, we propose the BioNetExplorer framework to systematically ...

0 Bharath Srinivas Prabakaran, et al. ∙

∙ 12/09/2020

MLComp: A Methodology for Machine Learning-based Performance Estimation and Adaptive Selection of Pareto-Optimal Compiler Optimization Sequences

Embedded systems have proliferated in various consumer and industrial ap...

0 Alessio Colucci, et al. ∙

∙ 01/29/2019

RED-Attack: Resource Efficient Decision based Attack for Machine Learning

Due to data dependency and model leakage properties, Deep Neural Network...

0 Faiq Khalid, et al. ∙

∙ 11/19/2018

Architectural-Space Exploration of Heterogeneous Reliability and Checkpointing Modes for Out-of-Order Superscalar Processors

Reliability has emerged as a key topic of interest for researchers aroun...

0 Bharath Srinivas Prabakaran, et al. ∙

∙ 11/19/2018

Heterogeneous Reliability Modes with Efficient State Compression for Out-of-Order Superscalar Processors

Reliability has emerged as a key topic of interest for researchers aroun...

0 Bharath Srinivas Prabakaran, et al. ∙

∙ 11/05/2018

TrojanZero: Switching Activity-Aware Design of Undetectable Hardware Trojans with Zero Power and Area Footprint

Conventional Hardware Trojan (HT) detection techniques are based on the ...

0 Imran Hafeez Abbassi, et al. ∙

∙ 11/05/2018

Security for Machine Learning-based Systems: Attacks and Challenges during Training and Inference

The exponential increase in dependencies between the cyber and physical ...

0 Faiq Khalid, et al. ∙

∙ 11/05/2018

ForASec: Formal Analysis of Security Vulnerabilities in Sequential Circuits

Security vulnerability analysis of Integrated Circuits using conventiona...

0 Faiq Khalid, et al. ∙

∙ 11/04/2018

FAdeML: Understanding the Impact of Pre-Processing Noise Filtering on Adversarial Machine Learning

Deep neural networks (DNN)-based machine learning (ML) algorithms have r...

0 Faiq Khalid, et al. ∙

∙ 11/04/2018

SSCNets: A Selective Sobel Convolution-based Technique to Enhance the Robustness of Deep Neural Networks against Security Attacks

Recent studies have shown that slight perturbations in the input data ca...

0 Hammad Tariq, et al. ∙

∙ 11/04/2018

QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks

Deep Neural Networks (DNNs) have recently been shown vulnerable to adver...

0 Hassan Ali, et al. ∙

∙ 11/02/2018

ISA4ML: Training Data-Unaware Imperceptible Security Attacks on Machine Learning Modules of Autonomous Vehicles

Due to big data analysis ability, machine learning (ML) algorithms are b...

0 Faiq Khalid, et al. ∙

∙ 10/30/2018

MPNA: A Massively-Parallel Neural Array Accelerator with Dataflow Optimization for Convolutional Neural Networks

The state-of-the-art accelerators for Convolutional Neural Networks (CNN...

0 Muhammad Abdullah Hanif, et al. ∙

∙ 10/27/2018

A Methodology for Automatic Selection of Activation Functions to Design Hybrid Deep Neural Networks

Activation functions influence behavior and performance of DNNs. Nonline...

0 Alberto Marchisio, et al. ∙

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