Josef Danial

Orcid: 0000-0001-5837-1304

According to our database1, Josef Danial authored at least 13 papers between 2019 and 2022.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2022
Syn-STELLAR: An EM/Power SCA-Resilient AES-256 With Synthesis-Friendly Signature Attenuation.
IEEE J. Solid State Circuits, 2022

EM-X-DL: Efficient Cross-device Deep Learning Side-channel Attack With Noisy EM Signatures.
ACM J. Emerg. Technol. Comput. Syst., 2022

2021
Sub-μWRComm: 415-nW 1-10-kb/s Physically and Mathematically Secure Electro-Quasi-Static HBC Node for Authentication and Medical Applications.
IEEE J. Solid State Circuits, 2021

EM and Power SCA-Resilient AES-256 Through >350× Current-Domain Signature Attenuation and Local Lower Metal Routing.
IEEE J. Solid State Circuits, 2021

36.2 An EM/Power SCA-Resilient AES-256 with Synthesizable Signature Attenuation Using Digital-Friendly Current Source and RO-Bleed-Based Integrated Local Feedback and Global Switched-Mode Control.
Proceedings of the IEEE International Solid-State Circuits Conference, 2021

2020
120.147 Efficient Electromagnetic Side Channel Analysis by Probe Positioning using Multi-Layer Perceptron.
IACR Cryptol. ePrint Arch., 2020

SCNIFFER: Low-Cost, Automated, Efficient Electromagnetic Side-Channel Sniffing.
IEEE Access, 2020

27.3 EM and Power SCA-Resilient AES-256 in 65nm CMOS Through >350× Current-Domain Signature Attenuation.
Proceedings of the 2020 IEEE International Solid- State Circuits Conference, 2020

A 415 nW Physically and Mathematically Secure Electro-Quasistatic HBC Node in 65nm CMOS for Authentication and Medical Applications.
Proceedings of the 2020 IEEE Custom Integrated Circuits Conference, 2020

Deep Learning Side-Channel Attack Resilient AES-256 using Current Domain Signature Attenuation in 65nm CMOS.
Proceedings of the 2020 IEEE Custom Integrated Circuits Conference, 2020

2019
Practical Approaches Toward Deep-Learning-Based Cross-Device Power Side-Channel Attack.
IEEE Trans. Very Large Scale Integr. Syst., 2019

X-DeepSCA: Cross-Device Deep Learning Side Channel Attack.
IACR Cryptol. ePrint Arch., 2019

SCNIFFER: Low-Cost, Automated, EfficientElectromagnetic Side-Channel Sniffing.
CoRR, 2019


  Loading...