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Scanning Electron Microscope Search Algorithm That Locates Defects or Trojans in Integrated Circuits

Applies Object Localization Algorithm to Identify and Locate Objects in Large, Complex Images

This object localization algorithm and window search technique identifies and locates target objects from scanning electron microscope images of integrated circuits to assist detection of defects and malicious circuits. Integrated circuits play key roles in nearly all modern electronics and are valued at $391 billion globally. The integrated circuit supply chain is vulnerable to security breaches including the sale of substandard, counterfeited circuits that can lead to poor quality or entirely non-functional electronics. In the past, object localization algorithms identified target objects in other fields using optical images, but these did not assess the quality of integrated circuits due to limitations of the optical images themselves.

 

Researchers at the University of Florida have developed an object localization algorithm that identifies target objects in integrated circuits from scanning electron microscope images. This algorithm quickly identifies and locates problems such as defects in integrated circuits.

 

 

Application

Object localization algorithm that identifies and locates target objects in integrated circuits from scanning electron microscope images

 

Advantages

  • Quickly identifies and locates target objects in integrated circuits, allowing for rapid, high-quality hardware assurance of integrated circuits
  • Enables the localization of various structures with high reliability, allowing for the search of multiple target objects simultaneously
  • Reduces search time in comparison to traditional window search techniques, speeding up hardware assurance of integrated circuits

Technology

This object localization algorithm uses a 2D search-string algorithm in combination with the window search technique and a knowledge-based mask window to search for multiple target objects from scanning electron microscope images of integrated circuits.

Patent Information: