Mr. Mohammad Shafkat M. Khan Profile

Mohammad Shafkat M. Khan

at Univ. of Florida

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Author

Publications (3)

Proceedings Article | 3 October 2024 Presentation + Paper

Fault-marking: defect-pattern leveraged inherent fingerprinting of advanced IC package with thermoreflectance imaging

Nitin Varshney, M. Shafkat Khan, Shajib Ghosh, Antika Roy, Je-Hyeong Bahk, Navid Asadizanjani

Proceedings Volume 13145, 131450A (2024) https://doi.org/10.1117/12.3027447

KEYWORDS: Thermoreflectance, Manufacturing, Digital watermarking, Reliability, Integrated circuits, Information security, Temperature metrology, Semiconductors, Reflection, Inspection

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In the quest to secure the authenticity and ownership of advanced integrated circuit (IC) packages, a novel approach has been introduced in this paper that capitalizes on the inherent physical discrepancies within these components. This method, distinct from traditional strategies like physical unclonable functions (PUFs) and cryptographic techniques, harnesses the unique defect patterns naturally occurring during the manufacturing process. By employing thermo-reflectance imaging (TRI), a non-destructive evaluation technique, in this proposed method we inspect, characterize and localize defects within IC package structures such as Through-silicon Vias (TSV) and micro-bumps. TRI’s ability to detect minute temperature variations caused by defects enables the creation of a detailed map that outlines the specific locations and types of manufacturing irregularities. This novel technique leverages the uniqueness of each IC’s defect pattern to generate an inherent identifier or ’fault-mark.’ These identifiers are derived from the specific arrangement and combination of defects, making them virtually impossible to replicate or forge due to the randomness and complexity of the manufacturing process variations. The creation of these fault-marks offers a robust and tamper-resistant means of authentication, providing a reliable method for establishing proof of ownership for advanced IC packages. The implementation of this approach not only can enhance supply chain security but also acts as a deterrent against the counterfeiting of IC packages. By verifying the authenticity of ICs against a reference database of fingerprints captured during the post-silicon validation stage, stakeholders can ensure the integrity of their components. This method’s potential of using inherent fingerprinting for reliable authentication and traceability of advanced IC packages is also been discussed, thereby offering a promising solution to the challenges of counterfeiting and unauthorized reproduction in the electronics industry.

Proceedings Article | 11 March 2024 Presentation + Paper

Enhancing counterfeit detection of integrated circuits through machine learning-assisted THz-TDS analysis

Chengjie Xi, Nitin Varshney, Mohammad Shafkat Khan, Hamed Dalir, Navid Asadizanjani

Proceedings Volume 12885, 128850C (2024) https://doi.org/10.1117/12.3003766

KEYWORDS: Counterfeit detection, Terahertz radiation, Machine learning, Data modeling, Refractive index, Packaging, Inspection, Integrated circuits, Semiconductors

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Proceedings Article | 11 March 2024 Presentation + Paper

THz-TDS for IC packaging material changes detection under real-world conditions

Chengjie Xi, Nitin Varshney, Mohammad Shafkat Khan, Hamed Dalir, Navid Asadizanjani

Proceedings Volume 12885, 128850B (2024) https://doi.org/10.1117/12.3004241

KEYWORDS: Packaging, Materials properties, Moisture, Polymers, Terahertz radiation, Epoxies, Counterfeit detection, Structural materials, Reliability, Refractive index

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