Adam Markman

Roadmap on optical security

Information security and authentication are important challenges facing society. Recent attacks by hackers on the databases of large commercial and financial companies have demonstrated that more research and development of advanced approaches are necessary to deny unauthorized access to critical data. Free space optical technology has been investigated by many researchers in information security, encryption, and authentication. The main motivation for using optics and photonics for information security is that optical waveforms possess many complex degrees of freedom such as amplitude, phase, polarization, large bandwidth, nonlinear transformations, quantum properties of photons, and multiplexing that can be combined in many ways to make information encryption more secure and more difficult to attack. This roadmap article presents an overview of the potential, recent advances, and challenges of optical security and encryption using free space optics. The roadmap on optical security is comprised of six categories that together include 16 short sections written by authors who have made relevant contributions in this field. The first category of this roadmap describes novel encryption approaches, including secure optical sensing which summarizes double random phase encryption applications and flaws [Yamaguchi], the digital holographic encryption in free space optical technique which describes encryption using multidimensional digital holography [Nomura], simultaneous encryption of multiple signals [Perez-Cabre], asymmetric methods based on information truncation [Nishchal], and dynamic encryption of video sequences [Torroba]. Asymmetric and one-way cryptosystems are analyzed by Peng. The second category is on compression for encryption. In their respective contributions, Alfalou and Stern propose similar goals involving compressed data and compressive sensing encryption. The very important area of cryptanalysis is the topic of the third category with two sections: Sheridan reviews phase retrieval algorithms to perform different attacks, whereas Situ discusses nonlinear optical encryption techniques and the development of a rigorous optical information security theory. The fourth category with two contributions reports how encryption could be implemented at the nano- or micro-scale. Naruse discusses the use of nanostructures in security applications and Carnicer proposes encoding information in a tightly focused beam. In the fifth category, encryption based on ghost imaging using single-pixel detectors is also considered. In particular, the authors [Chen, Tajahuerce] emphasize the need for more specialized hardware and image processing algorithms. Finally, in the sixth category, Mosk and Javidi analyze in their corresponding papers how quantum imaging can benefit optical encryption systems. Sources that use few photons make encryption systems much more difficult to attack, providing a secure method for authentication.

Photon-Counting Security Tagging and Verification Using Optically Encoded QR Codes

We propose an optical security method for object authentication using photon-counting encryption implemented with phase encoded QR codes. By combining the full phase double-random-phase encryption with photon-counting imaging method and applying an iterative Huffman coding technique, we are able to encrypt and compress an image containing primary information about the object. This data can then be stored inside of an optically phase encoded QR code for robust read out, decryption, and authentication. The optically encoded QR code is verified by examining the speckle signature of the optical masks using statistical analysis. Optical experimental results are presented to demonstrate the performance of the system. In addition, experiments with a commercial Smartphone to read the optically encoded QR code are presented. To the best of our knowledge, this is the first report on integrating photon-counting security with optically phase encoded QR codes.

Full-phase photon-counting double-random-phase encryption.

We investigate a full-phase-based photon-counting double-random-phase encryption (PC-DRPE) method. A PC technique is applied during the encryption process, creating sparse images. The statistical distribution of the PC decrypted data for full-phase encoding and amplitude-phase encoding are derived, and their statistical parameters are used for authentication. The performance of the full-phase PC-DRPE is compared with the amplitude-based PC-DRPE method. The PC decrypted images make it difficult to visually authenticate the input image; however, advanced correlation filters can be used to authenticate the decrypted images given the correct keys. Initial computational simulations show that the full-phase PC-DRPE has the potential to require fewer photons for authentication than the amplitude-based PC-DRPE.

Three-dimensional integral imaging displays using a quick-response encoded elemental image array

Mobile devices are a ubiquitous technology, and many researchers are trying to implement three-dimensional (3D) displays on mobile devices for a variety of applications. We investigate a method to store compressed and encrypted elemental images (EIs) used for 3D integral imaging displays in multiple quick-response (QR) codes. This approach allows user friendly access, readout, and 3D display with mobile devices. We first compress the EIs and then use double-random-phase encryption to encrypt the compressed image and store this information in multiple QR codes. The QR codes are then scanned using a commercial Smartphone to reveal the encrypted information, which can be decrypted and decompressed. We also introduce an alternative scheme by applying photon counting to each color channel of the EIs prior to the aforementioned compression and encryption scheme to generate sparsity and nonlinearity for improved compression and security. Experimental results are presented to demonstrate both 3D computational reconstruction and optical 3D integral imaging display with a Smartphone using EIs from the QR codes. This work utilizing compressed QR encoded EIs for secure integral imaging displays using mobile devices may enable secure 3D displays with mobile devices.

Compact and field-portable 3D printed shearing digital holographic microscope for automated cell identification

We propose a low-cost, compact, and field-portable 3D printed holographic microscope for automated cell identification based on a common path shearing interferometer setup. Once a hologram is captured from the portable setup, a 3D reconstructed height profile of the cell is created. We extract several morphological cell features from the reconstructed 3D height profiles, including mean physical cell thickness, coefficient of variation, optical volume (OV) of the cell, projected area of the cell (PA), ratio of PA to OV, cell thickness kurtosis, cell thickness skewness, and the dry mass of the cell for identification using the random forest (RF) classifier. The 3D printed prototype can serve as a low-cost alternative for the developing world, where access to laboratory facilities for disease diagnosis are limited. Additionally, a cell phone sensor is used to capture the digital holograms. This enables the user to send the acquired holograms over the internet to a computational device located remotely for cellular identification and classification (analysis). The 3D printed system presented in this paper can be used as a low-cost, stable, and field-portable digital holographic microscope as well as an automated cell identification system. To the best of our knowledge, this is the first research paper presenting automatic cell identification using a low-cost 3D printed digital holographic microscopy setup based on common path shearing interferometry.

Security authentication with a three-dimensional optical phase code using random forest classifier

An object with a unique three-dimensional (3D) optical phase mask attached is analyzed for security and authentication. These 3D optical phase masks are more difficult to duplicate or to have a mathematical formulation compared with 2D masks and thus have improved security capabilities. A quick response code was modulated using a random 3D optical phase mask generating a 3D optical phase code (OPC). Due to the scattering of light through the 3D OPC, a unique speckle pattern based on the materials and structure in the 3D optical phase mask is generated and recorded on a CCD device. Feature extraction is performed by calculating the mean, variance, skewness, kurtosis, and entropy for each recorded speckle pattern. The random forest classifier is used for authentication. Optical experiments demonstrate the feasibility of the authentication scheme.

Augmented reality three-dimensional object visualization and recognition with axially distributed sensing.

An augmented reality (AR) smartglass display combines real-world scenes with digital information enabling the rapid growth of AR-based applications. We present an augmented reality-based approach for three-dimensional (3D) optical visualization and object recognition using axially distributed sensing (ADS). For object recognition, the 3D scene is reconstructed, and feature extraction is performed by calculating the histogram of oriented gradients (HOG) of a sliding window. A support vector machine (SVM) is then used for classification. Once an object has been identified, the 3D reconstructed scene with the detected object is optically displayed in the smartglasses allowing the user to see the object, remove partial occlusions of the object, and provide critical information about the object such as 3D coordinates, which are not possible with conventional AR devices. To the best of our knowledge, this is the first report on combining axially distributed sensing with 3D object visualization and recognition for applications to augmented reality. The proposed approach can have benefits for many applications, including medical, military, transportation, and manufacturing.

Double-random-phase encryption with photon counting for image authentication using only the amplitude of the encrypted image

We present a photon-counting double-random-phase encryption technique that only requires the photon-limited amplitude of the encrypted image for decryption. The double-random-phase encryption is used to encrypt an image, generating a complex image. Photon counting is applied to the amplitude of the encrypted image, generating a sparse noise-like image; however, the phase information is not retained. By not using the phase information, the encryption process is simplified, allowing for intensity detection and also less information to be recorded. Using a phase numerically generated from the correct encryption keys together with the photon-limited amplitude of the encrypted image, we are able to decrypt the image. Moreover, nonlinear correlation algorithms can be used to authenticate the decrypted image. Both amplitude-based and full-phase encryption using the proposed method are investigated. Preliminary computational results and performance evaluation are presented.

Multidimensional Optical Sensing and Imaging System (MOSIS): From Macroscales to Microscales

Multidimensional optical imaging systems for information processing and visualization technologies have numerous applications in fields such as manufacturing, medical sciences, entertainment, robotics, surveillance, and defense. Among different three-dimensional (3-D) imaging methods, integral imaging is a promising multiperspective sensing and display technique. Compared with other 3-D imaging techniques, integral imaging can capture a scene using an incoherent light source and generate real 3-D images for observation without any special viewing devices. This review paper describes passive multidimensional imaging systems combined with different integral imaging configurations. One example is the integral-imaging-based multidimensional optical sensing and imaging systems (MOSIS), which can be used for 3-D visualization, seeing through obscurations, material inspection, and object recognition from microscales to long range imaging. This system utilizes many degrees of freedom such as time and space multiplexing, depth information, polarimetric, temporal, photon flux and multispectral information based on integral imaging to record and reconstruct the multidimensionally integrated scene. Image fusion may be used to integrate the multidimensional images obtained by polarimetric sensors, multispectral cameras, and various multiplexing techniques. The multidimensional images contain substantially more information compared with two-dimensional (2-D) images or conventional 3-D images. In addition, we present recent progress and applications of 3-D integral imaging including human gesture recognition in the time domain, depth estimation, mid-wave-infrared photon counting, 3-D polarimetric imaging for object shape and material identification, dynamic integral imaging implemented with liquid-crystal devices, and 3-D endoscopy for healthcare applications.

Cell identification using single beam lensless imaging with pseudo-random phase encoding.

In this Letter, we propose a novel compact optical system for automated cell identification. Our system employs pseudo-random encoding of the light modulated by the cells under inspection to capture the unique opto-biological signature of the micro-organisms by an image sensor and without using a microscope objective lens to magnify the object beam. The proposed instrument can be fabricated using a compact light source, a thin diffuser, and an image sensor connected to computational hardware; thus, it can be compact and cost effective. Experiments are presented using the proposed system to identify and classify various micro-objects and demonstrate proof of concept. The captured opto-biological signature pattern can be attributed to the micro-objects morphology, size, sub-cellular complex structure, index of refraction, internal material composition, etc. Using the captured signature of the micro-object, we extract statistical features such as mean, variance, skewness, kurtosis, entropy, and correlation coefficients for cell identification using the random forest classifier. For comparison, similar identification experiments were repeated with a digital shearing interferometer. To the best of our knowledge, this is the first report on automated cell identification using the proposed approach.