About Omics Group

1. About Omics Group OMICS Group International through its Open Access Initiative is committed to make genuine and reliable contributions to the scientific community. OMICS Group hosts over 400 leading-edge peer reviewed Open Access Journals and organize over 300 International Conferences annually all over the world. OMICS Publishing Group journals have over 3 million readers and the fame and success of the same can be attributed to the strong editorial board which contains over 30000 eminent personalities that ensure a rapid, quality and quick review process. 

2. About Omics Group conferences • OMICS Group signed an agreement with more than 1000 International Societies to make healthcare information Open Access. OMICS Group Conferences make the perfect platform for global networking as it brings together renowned speakers and scientists across the globe to a most exciting and memorable scientific event filled with much enlightening interactive sessions, world class exhibitions and poster presentations • Omics group has organised 500 conferences, workshops and national symposium across the major cities including SanFrancisco,Omaha,Orlado,Rayleigh,SantaClara,Chicago,Philadelphia,Unitedkingdom,Baltimore,SanAntanio,Dubai,Hyderabad,Bangaluru and Mumbai.

3. University of Connecticut Multi-level Authentication Platform Using Electronic Nano-Signatures Kiarash Ahi, Anas Mazady, Abdiel Rivera, Mohammad Tehranipoor and Mehdi Anwar Reflection from ENS Laser pointer

4. The Challenge Increased proliferation of counterfeit electronic components threatens both commercial and defense industries in the areas of product performance, reliability and dependability. Impacts Negative impact on innovation The threat to welfare of consumers

5. Existing Solutions • Visual Inspection • Optical Characterization • Electrical Testing • Material Inspection • X-ray Imaging • THz Imaging/Analysis (another ongoing effort at CHASE) Lacks Conclusivity and Cross Referencing Counterfeit detection still has much intrinsic subjectivity, and thus the confidence level of the associated results is lacking

6. Smart Electronics • PUFS/Smart Electrical-Optical Technology • May be designed and incorporated in electronic components in the design phase ensuring component authenticity. • Components currently either in the market or in the production line (without any built in component authentication signatures) • The challenge is to be able to incorporate counterfeit identification signatures in COTS electronic components. • Requirements • Inexpensive • Dependable/Electrically Robust • Integrable with existing production flow • Fast – able to incorporate signatures within a few seconds without causing delay in production line • Difficult to imitate

7. ENS – Engineered Nano-SignaturesTechnology Comparison

8. Multi-Layer Authentication

9. Introduction to Metamaterials • Metamaterials are periodic or quasi-periodic, sub-wavelength metal structures. The electro-magnetic material properties are derived from its structure rather than inheriting them directly from its material composition. • Electromagnetic properties altered to something beyond what can be found in nature, i.e. negative refractive index empty glass regular water, n = 1.3 “negative” water, n = -1.3

10. Introduction to Metamaterials μ POSITIVE REFRACTION ABSORPTION ε < 0, μ > 0 Plasma ε > 0, μ > 0 Dielectrics ε ε < 0, μ < 0 Not found in nature ε > 0, μ < 0 Gyrotropic ABSORPTION NEGATIVE REFRACTION!!

11. Snell`s Law Negative Refractive Index Regular Material Metamaterial

12. Split ring resonator (SRR) made from copper. c=0.8 mm, d=0.2 mm, r=1.5 mm. Resonance at 4.845 GHz Both permeability (μ) and permittivity (ɛ) are negative in microwave range Realization of Metamaterials Smith et al. Physical Review Lett. vol.84, no. 18 (2000)

13. Realization of Metamaterials Yao et al. Science. vol.321 (2008) • Ag nanowires: diameter=60 nm, length = 1.5 mm • Negative refraction was observed in optical frequencies for TM wave • Ag NWs inside porous alumina matrix acts as metamaterials. • The effective permittivity parallel to the NW is negative while along perpendicular direction it is positive

14. ENS Employing Metamaterials A tool allowing identification of good ICs, already been capped and in post design phase. Allows the detection of over-produced or counterfeit ICs as the counterfeiters will not be able to re-generate the random ENS and resurfacing will destroy the ENS. Non-destructive Inexpensive detection: only a laser pointer does the job !! The ENS array can be tailored to provide signatures unique to the IC.

15. Schematic of ENS 9 µm 0.5 µm 9 µm Single pixel of metamaterial ENS was written on a commercially available IC using Electron Beam Lithography (EBL) followed by Au sputtering ENS using a 5×5 array of metamaterials

16. SEM Images

17. Optical Microscope Images (> 1000x)

18. Experimental Setup Laser IC Laser Focus

19. Demonstration 2nd Reflection Video Demonstration

20. Optical Image of Metal Patches CHASE Meeting 20

21. Laser Experiment on Metal Patch Reflection from the metal patch is very weak and the 2nd reflection spot is not observed.

22. Laser Experiment on ENS(Background Minimized) Distance Adjustment Y-axis Adjustment Height Adjustment Video Demonstration Reflection from ENS Laser pointer

23. Frequency Information Height Adjustment Reflection from ENS Laser pointer

24. Preparing Images for Extracting Structural Information • 1. Adjusting the dimension: • The images have been rescaled to 181×242 pixels. • Rescaling have been done By resizing and cropping. • The aspect-ratios of the images have been maintained. • 2. Removing the color: • The color data has been removed from the images; only Y matrices which represents theLumainformation of the images have been kept for the comparisons. • 3. Filtering the unwanted disturbances and noise: • For removing the unwanted disturbances and noise on the background of the images pixels with intensities lower than 0.2 has been set to 0. • 4. Image Registration: • For the sake of keeping the aspect ratio, in the first set of similarity measurements, the images are not aligned by Image Registration process. • In a second set of similarity measurements, the images have been first aligned by employing image registration principles using Matlab (results are not presented in this paper).

25. Image Processing Original image is decomposed into three parts using the YIQ model: Luminance (Y) – containts the information about brightness Inphase (I) and Quadrature (Q) – contain color information Processing is performed on the luminance part, and the other two reamain untouched to reconstruct the original color Luminance (Y) Inphase (I) Qudrature (Q)

26. Inphase (I) Qudrature (Q) Luminance Reconstracted image

27. Histogram of Image Intensity

28. Image Reconstruction: Zone 1 Original color image Reconstructed color image Image with background removed

29. Image Reconstruction: Zone 2 Reconstructed color image Image with higher intensity pixels

30. Image Reconstruction: Zone 3 Reconstructed color image Image with highest intensity pixels

31. Extracted Structural Information MATLAB Routine Load image Decompose image into YIQ model Calculate image resolution Calculate image size in cm Create histogram and segmentize the image Compute FFT distribution in terms of wavenumber Determine the wavenumber at which peak occurs Calculate dimension

32. Effects of Aging and Ambient 3 Months Old ENS High Moisture Room Humidity The horizontal axis represents brightness levels and the vertical axis represents number of pixels with corresponding brightness. Histogram of the original image and the filter. Histograms after filtration Extracted dimension from FFT 60 µm × 108 µm Lumacomponents (Y matrix) of the Images after filtering

33. Similarity Analysis Table 1: Structural SIMilarity (SSIM), for identical images value = 1, for the poorest similarities value =0 Table 2: Mean squared error (MSE), for identical images value = 0, for the poorest similarities value = 1 Table 3: Euclidean distance(ED), for identical images value = 0

34. Risk and Roadblocks • Initial Demonstration • Metal Thickness Needs to be Optimized • Metal Type and Processing Steps Need Optimization • Significance of Optical Readout and Identifying areas of Interest

35. Conclusion Metamaterials were employed to create ENS IC chips with appropriated ENS show distinct features in the reflection IC chips with inappropriate ENS or just metal patches do not show such features Image processing was performed to extract the structural information of the ENS CHASE Meeting 35

36. Let Us Meet Again We welcome all to our future group conferences of Omics group international Please visit: www.omicsgroup.com www.Conferenceseries.com http://optics.conferenceseries.com/