Khaled N. Khasawneh

Orcid: 0000-0002-2116-2223

According to our database1, Khaled N. Khasawneh authored at least 38 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Spectre Returns! Speculation Attacks Using the Return Stack Buffer.
IEEE Des. Test, 2024

Evasive Hardware Trojan through Adversarial Power Trace.
CoRR, 2024

2023
SecureVolt: Enhancing Deep Neural Networks Security via Undervolting.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., December, 2023

Adversarial Attacks Against Machine Learning-Based Resource Provisioning Systems.
IEEE Micro, 2023

HeteroScore: Evaluating and Mitigating Cloud Security Threats Brought by Heterogeneity.
Proceedings of the 30th Annual Network and Distributed System Security Symposium, 2023

VPP: Privacy Preserving Machine Learning via Undervolting.
Proceedings of the IEEE International Symposium on Hardware Oriented Security and Trust, 2023

A Brain-inspired Approach for Malware Detection using Sub-semantic Hardware Features.
Proceedings of the Great Lakes Symposium on VLSI 2023, 2023

Stochastic-HMDs: Adversarial-Resilient Hardware Malware Detectors via Undervolting.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022
Imitating Functional Operations for Mitigating Side-Channel Leakage.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

Efficient Hardware Malware Detectors That are Resilient to Adversarial Evasion.
IEEE Trans. Computers, 2022

Defending with Errors: Approximate Computing for Robustness of Deep Neural Networks.
CoRR, 2022

Characterization of AES Implementations on Microprocessor-based IoT Devices.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2022

Repttack: Exploiting Cloud Schedulers to Guide Co-Location Attacks.
Proceedings of the 29th Annual Network and Distributed System Security Symposium, 2022

ROOM: Adversarial Machine Learning Attacks Under Real-Time Constraints.
Proceedings of the International Joint Conference on Neural Networks, 2022

Secure and Energy-Efficient Proximity-Based Pairing for IoT Devices.
Proceedings of the IEEE Globecom 2022 Workshops, 2022

2021
Stochastic-HMDs: Adversarial Resilient Hardware Malware Detectors through Voltage Over-scaling.
CoRR, 2021

Cloak & Co-locate: Adversarial Railroading of Resource Sharing-based Attacks on the Cloud.
Proceedings of the 2021 International Symposium on Secure and Private Execution Environment Design (SEED), 2021

Monotonic-HMDs: Exploiting Monotonic Features to Defend Against Evasive Malware.
Proceedings of the 22nd International Symposium on Quality Electronic Design, 2021

Lower Voltage for Higher Security: Using Voltage Overscaling to Secure Deep Neural Networks.
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021

Energy-Efficient and Adversarially Robust Machine Learning with Selective Dynamic Band Filtering.
Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021

Defensive approximation: securing CNNs using approximate computing.
Proceedings of the ASPLOS '21: 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2021

2020
EnsembleHMD: Accurate Hardware Malware Detectors with Specialized Ensemble Classifiers.
IEEE Trans. Dependable Secur. Comput., 2020

Defensive Approximation: Enhancing CNNs Security through Approximate Computing.
CoRR, 2020

SpecCFI: Mitigating Spectre Attacks using CFI Informed Speculation.
Proceedings of the 2020 IEEE Symposium on Security and Privacy, 2020

Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks.
Proceedings of the 21st International Symposium on Quality Electronic Design, 2020

ND-HMDs: Non-Differentiable Hardware Malware Detectors against Evasive Transient Execution Attacks.
Proceedings of the 38th IEEE International Conference on Computer Design, 2020

The Evolution of Transient-Execution Attacks.
Proceedings of the GLSVLSI '20: Great Lakes Symposium on VLSI 2020, 2020

Evolution of Defenses against Transient-Execution Attacks.
Proceedings of the GLSVLSI '20: Great Lakes Symposium on VLSI 2020, 2020

A Review of In-Memory Computing Architectures for Machine Learning Applications.
Proceedings of the GLSVLSI '20: Great Lakes Symposium on VLSI 2020, 2020

Lightweight Implementation of the LowMC Block Cipher Protected Against Side-Channel Attacks.
Proceedings of the 4th ACM Workshop on Attacks and Solutions in Hardware Security Workshop, 2020

2019
Architectural Support for Securing Systems Against Software Vulnerabilities.
PhD thesis, 2019

LATCH: A Locality-Aware Taint CHecker.
Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019

SafeSpec: Banishing the Spectre of a Meltdown with Leakage-Free Speculation.
Proceedings of the 56th Annual Design Automation Conference 2019, 2019

2017
Constructing and characterizing covert channels on GPGPUs.
Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture, 2017

RHMD: evasion-resilient hardware malware detectors.
Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture, 2017

RIC: Relaxed Inclusion Caches for Mitigating LLC Side-Channel Attacks.
Proceedings of the 54th Annual Design Automation Conference, 2017

2016
Hardware-Based Malware Detection Using Low-Level Architectural Features.
IEEE Trans. Computers, 2016

2015
Ensemble Learning for Low-Level Hardware-Supported Malware Detection.
Proceedings of the Research in Attacks, Intrusions, and Defenses, 2015


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