A Fast Signal Integrity Design Model of Printed Circuit Board based on Monte-Carlo Tree

Zhang, Tingrui; Chen, Siyu; Wei, Shuwu; Chen, Jienan

doi:10.1109/asicon47005.2019.8983610

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…4 does not require complex algorithms such as BO or autoencoder (AE). Furthermore, the deployment of the decision tree in presented work differs from the implementation of Zhang et al (2019), because the method here is not directly dependent on physical parameters. The decision tree relies on anomaly detection based on output waveforms and models the human evaluation process.…”

Section: Reduction Of Si Analysis Complexity In Pcb Designmentioning

confidence: 99%

Anomaly Detection with Decision Trees for AI Assisted Evaluation of Signal Integrity on PCB Transmission Lines

Ecik,

John,

Withöft

et al. 2023

Adv. Radio Sci.

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Abstract. Printed circuit board (PCB) design can be supported to a high degree by adding AI modules to the design system. Predictions from these modules can be made available to the designer in order to speed up circuit design and make it more efficient. Problems regarding signal integrity (SI) can be detected in time by providing hints on component connection or routing. However, the optimization and ML methods used in this context are usually very sophisticated (e.g., Bayesian optimization). Therefore, the design parameters provided by the AI modules must be accepted without further insights (for the experienced as well as the inexperienced designer). In this paper, a decision tree for anomaly detection and SI verification is presented, which by nature of this algorithm provides insights to the decisions made to obtain the proposed design parameters. Using a point-to-point (P2P) network as an example, the prediction accuracy of the AI model is investigated. It is shown that assessing SI effects with a decision tree provides a simple approach to obtain the suggested design. Furthermore, the predictions of the decision tree can be verified against the design rules.

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Section: Reduction Of Si Analysis Complexity In Pcb Designmentioning

confidence: 99%

Anomaly Detection with Decision Trees for AI Assisted Evaluation of Signal Integrity on PCB Transmission Lines

Ecik,

John,

Withöft

et al. 2023

Adv. Radio Sci.

View full text Add to dashboard Cite

show abstract

“…Monte Carlo based simulation methods can enable designers to simulate their design and its vulnerabilities before the final design for fabrication. Algorithmic methods to analyze PCB designs and improve their design are lacking, but compared to randomly searching for optimal parameters combination, Monte Carlo methods can generate an optimal global analysis rather than working out a sub-optimum result for securing PCB designs [22]. In this paper, the proposed workflow for securing PCB designs with MEMS, EDA, X-ray simulation, and 3D PCB manufacturing demonstrates a complex solution to the growing vulnerabilities for PCB non-destructive attacks.…”

Section: Pcb Eda Software Toolmentioning

confidence: 99%

PCB Netlist Obfuscation with Micro Electro Mechanical Systems and Additive Manufacturing Techniques

True

Khan

et al. 2021

International Symposium for Testing and Failure Analysis

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Semiconductor manufacturing has been outsourced to un-trusted regions due to globalization. The complex multistep fabrication of micro-scale integrated circuits (ICs) and the tedious assembly of macro-scale Printed Circuit Boards (PCBs) are vulnerable to malicious attacks from design to final delivery. PCBs provide the functional connections of Integrated Circuits (ICs), sensors, power supplies, etc. of many critical electronic systems for consumers, corporations, and governments. The feature sizes of PCB signal traces in 2D and vias in 3D are an order of magnitude larger than IC devices, and are thereby more vulnerable to non-destructive attacks such as X-ray or probing. Active and passive countermeasures have been successfully developed for IC devices, however PCBs devices are difficult to wholly secure from all attacks. Passive countermeasures for X-ray attacks using high-z materials to block and scatter X-rays are effective, but there is a lack of active and passive countermeasures for PCB. In this paper, a framework for passively obfuscating a PCB's critical connections between components, such as ICs, from non-destructive attacks is demonstrated. This framework can be further extended to incorporate active countermeasures in future work. A proof of concept for a PCB electronic design automation (EDA) tool which combines the small features of micro electro-mechanical systems (MEMS), simulation of X-ray, and 3D PCB Manufacturing to iteratively optimize PCB design to thwart reverse engineering and probing attacks. Index Terms—Additive Manufacturing, MEMS, Hardware Assurance, Physical Inspection, Non-Destructive Technology

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Signal Integrity Design of PCB Transmission Paths using a Decision Tree Approach

Ecik,

John,

Withöft

et al. 2023

2023 International Symposium on Electromagnetic Compatibility – EMC Europe

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A Fast Signal Integrity Design Model of Printed Circuit Board based on Monte-Carlo Tree

Cited by 3 publications

References 14 publications

Anomaly Detection with Decision Trees for AI Assisted Evaluation of Signal Integrity on PCB Transmission Lines

Anomaly Detection with Decision Trees for AI Assisted Evaluation of Signal Integrity on PCB Transmission Lines

PCB Netlist Obfuscation with Micro Electro Mechanical Systems and Additive Manufacturing Techniques

Signal Integrity Design of PCB Transmission Paths using a Decision Tree Approach

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