The Internet of Things (IoT) and Internet of Everything (IoE) has driven the proliferation of processors into nearly every powered device around us: from thermostats to refrigerators to light bulbs. From a security perspective, IoT/IoE creates a new layer of signals and systems that can be exploited to access supporting network layers. Our research focuses on leveraging the analog side channels of IoT/IoE processors, for defensive purposes. We apply signal-processing and machine-learning techniques to collected RF emissions to detect if code running on the processor has been modified (i.e., corrupted or injected with malware). The paper describes our process for positioning a wide-bandwidth RF probe over the device under test (DuT). Classifiers are implemented for identifying the code running on the device. We demonstrate the ability to detect, identify, and isolate instructions based on signatures learned during initial DuT characterization. The probe is positioned to capture RF signals that support-vector machine (SVM) classifiers can accurately discriminate between instructions, rather than relying on raw power leakage. At this well-discriminated location, the signatures of each instruction are extracted by applying principal component analysis (PCA) to separate its signal into components (fetch, opcode, operands, and values). These signatures are used to identify instructions in the test code. Additionally, this paper discusses applying our methodology to blocks of code/algorithms using sequence learning algorithms. These techniques enable significant reduction in feature dimensions improving speed and accuracy of instruction level classification of low-SNR RF sidechannels.
Side-Channel Analysis (SCA) is an increasingly well-known method for non-invasively extracting information from unintended “side-channel” emissions given off by electronic devices. The common method for extracting side-channel information is via a near-field antenna probe placed in the vicinity (i.e., millimeters) of the target device. The antenna detects and amplifies the radio-frequency (RF) emissions given off by the device and transmits the information for analysis and testing. Side-channel attacks are most known for their utility in cryptanalytics; however, they can also be used to fingerprint devices or even determine the digital state of the system. In this work, characterization studies on a 1- GHz antenna using Riscure’s RF probe station are performed. For RF-SCA, the ultimate limits of signal sensitivity and frequency response are determined by the antenna characteristics. In addition, the effective source-receiver distance (SRD), cross-talk and spatial signal averaging at various SRDs have to be characterized for signal attenuation and normalization. From our testing, it appears that the Riscure probe has a peak frequency response at about 200 MHz. For example, the 418MHz antenna had multiple peaks at 130 MHz, 172 MHz, 213 MHz, and 370 MHz, as well as multiple less significant protrusions at higher frequencies. The BeeHive100C probe peaked at exactly 200 MHz but had a couple of side-lobes in the 600-800 MHz range. The Pharad 30-512 MHz antenna peaked at a slightly lower 193MHz, although, some response was observed in the 600-800 MHz range as in the other antennas. The Pharad 225-6000MHz antenna exhibited a similar peak but lesser roll-off and an elevated response at increased frequencies than its predecessor.
In this paper, we describe a narrow-bandwidth generation and detection of photoacoustic (PA) signals in biological specimens using frequency-domain photoacoustics. An intensity-modulated laser was used for PA generation, and a homodyne Michelson interferometer coupled to a lock-in amplifier was used for optical PA detection. The amplitude and phase of the PA signal were measured at the modulation frequency as the frequency was swept over the bandwidth of interest. A synthesized pulse response was obtained using time-domain reconstruction and the absorber map was estimated using k-space reconstruction methods. Experimental results obtained from 500-μm graphite rods embedded in tissue-mimicking phantoms and slide-mounted tissue samples are presented along with their respective time-domain and time-reversal reconstruction maps.
Globally, cancer is a major health issue as advances in modern medicine continue to extend the human life span. Breast cancer ranks second as a cause of cancer death in women in the United States. Photoacoustic (PA) imaging (PAI) provides high molecular contrast at greater depths in tissue without the use of ionizing radiation. In this work, we describe the development of a PA tomography (PAT) system and a rapid wavelength-cycling Alexandrite laser designed for clinical PAI applications. The laser produces 450 mJ/pulse at 25 Hz to illuminate the entire breast, which eliminates the need to scan the laser source. Wavelength cycling provides a pulse sequence in which the output wavelength repeatedly alternates between 755 nm and 797 nm rapidly within milliseconds. We present imaging results of breast phantoms with inclusions of different sizes at varying depths, obtained with this laser source, a 5-MHz 128-element transducer and a 128-channel Verasonics system. Results include PA images and 3D reconstruction of the breast phantom at 755 and 797 nm, delineating the inclusions that mimic tumors in the breast.
Patients with myopic vitreopathy (MV) and posterior vitreous detachment (PVD) see floaters, which often can degrade contrast sensitivity to a significant extent. The floaters are associated with irregularly shaped vitreous opacities. In contrast, asteroid hyalosis (AH), which is characterized by microscopic, spherical, white asteroid bodies (ABs) that move with vitreous displacement during eye movements, does not interfere significantly with vision. We hypothesize that the irregular surface of vitreous opacities associated with MV distinguish MV from AH and its smooth-surfaced ABs. A finite-element model was developed to characterize the light-scattering field of vitreous opacities in MV and AH. Vitreous opacities were modeled as spherical bodies and illuminated by a plane wave of light in the optical wavelength of 400-1000 nm. The model has provisions to add random perturbations to the spherical surfaces to vary light-scattering properties and mimic disturbances in vision from simple diffraction rings to more-complex patterns. Samples of ex vivo porcine vitreous (0.4-0.5 ml) were placed in a custom spectrophotometer and the static, light-scattering field of the sample was measured in the spectral range of 400-1000 nm with a resolution of 0.3 nm. Model solutions mimicking healthy vitreous and AH were experimentally validated using a laboratory optical apparatus. Model-based estimates of scattering cross-sections of calibrated gold nanoparticles were found to be in good agreement with experimental measurements. Simulation results potentially can complement experimental data to quantitatively characterize vitreous opacities and distinguish between structures that significantly impact vision, such as those due to myopic vitreopathy and aging, from those that have little impact, like ABs. Such techniques to determine the structural significance of vitreous opacification would be very useful in selecting patients for surgery as well as evaluating the efficacy of experimental therapies for floaters.
Staging of cancers and selection of appropriate treatment requires histological examination of multiple dissected lymph nodes (LNs) per patient, so that a staggering number of nodes require histopathological examination, and the finite resources of pathology facilities create a severe processing bottleneck. Histologically examining the entire 3D volume of every dissected node is not feasible, and therefore, only the central region of each node is examined histologically, which results in severe sampling limitations. In this work, we assess the feasibility of using quantitative photoacoustics (QPA) to overcome the limitations imposed by current procedures and eliminate the resulting under sampling in node assessments. QPA is emerging as a new hybrid modality that assesses tissue properties and classifies tissue type based on multiple estimates derived from spectrum analysis of photoacoustic (PA) radiofrequency (RF) data and from statistical analysis of envelope-signal data derived from the RF signals. Our study seeks to use QPA to distinguish cancerous from non-cancerous regions of dissected LNs and hence serve as a reliable means of imaging and detecting small but clinically significant cancerous foci that would be missed by current methods. Dissected lymph nodes were placed in a water bath and PA signals were generated using a wavelength-tunable (680-950 nm) laser. A 26-MHz, f-2 transducer was used to sense the PA signals. We present an overview of our experimental setup; provide a statistical analysis of multi-wavelength classification parameters (mid-band fit, slope, intercept) obtained from the PA signal spectrum generated in the LNs; and compare QPA performance with our established quantitative ultrasound (QUS) techniques in distinguishing metastatic from non-cancerous tissue in dissected LNs. QPA-QUS methods offer a novel general means of tissue typing and evaluation in a broad range of disease-assessment applications, e.g., cardiac, intravascular, musculoskeletal, endocrine-gland, etc.
We describe the ongoing development of laser systems for advanced photoacoustic imaging (PAI). We discuss the characteristics of these laser systems and their particular benefits for soft tissue imaging and next-generation breast cancer diagnostics. We provide an overview of laser performance and compare this with other laser systems that have been used for early-stage development of PAI. These advanced systems feature higher pulse energy output at clinically relevant repetition rates, as well as a novel wavelength-cycling output pulse format. Wavelength cycling provides pulse sequences for which the output repeatedly alternates between two wavelengths that provide differential imaging. This capability improves co-registration of captured differential images. We present imaging results of phantoms obtained with a commercial ultrasound detector system and a wavelength-cycling laser source providing ~500 mJ/pulse at 755 and 797 nm, operating at 25 Hz. The results include photoacoustic images and corresponding pulse-echo data from a tissue mimicking phantom containing inclusions, simulating tumors in the breast. We discuss the application of these systems to the contrast-enhanced detection of various tissue types and tumors.
Dental caries remain one of the most common oral diseases in the world. Current detection methods, such as dental
explorer and X-ray radiography, suffer from poor sensitivity and specificity at the earliest (and reversible) stages of the
disease because of the small size (< 100 microns) of early-stage lesions. We have developed a fine-resolution (480 nm),
ultra-broadband (1 GHz), all-optical photoacoustic imaging (AOPAI) system to image and detect early stages of tooth
decay. This AOPAI system provides a non-contact, non-invasive and non-ionizing means of detecting early-stage dental
caries. Ex-vivo teeth exhibiting early-stage, white-spot lesions were imaged using AOPAI. Experimental scans targeted
each early-stage lesion and a reference healthy enamel region. Photoacoustic (PA) signals were generated in the tooth
using a 532-nm pulsed laser and the light-induced broadband ultrasound signal was detected at the surface of the tooth
with an optical path-stabilized Michelson interferometer operating at 532 nm. The measured time-domain signal was
spatially resolved and back-projected to form 2D and 3D maps of the lesion using k-wave reconstruction methods.
Experimental data collected from areas of healthy and diseased enamel indicate that the lesion generated a larger PA
response compared to healthy enamel. The PA-signal amplitude alone was able to detect a lesion on the surface of the
tooth. However, time- reversal reconstructions of the PA scans also quantitatively depicted the depth of the lesion. 3D
PA reconstruction of the diseased tooth indicated a sub-surface lesion at a depth of 0.6 mm, in addition to the surface
lesion. These results suggest that our AOPAI system is well suited for rapid clinical assessment of early-stage dental
caries. An overview of the AOPAI system, fine-resolution PA and histology results of diseased and healthy teeth will be
presented.
NEMS are rapidly being developed for a variety of sensing applications as well as for exploring interesting regimes in fundamental physics. In most of these endeavors, operation of a NEMS device involves actuating the device harmonically around its fundamental resonance and detecting subsequent motion while the device interacts with its environment. Even though a single NEMS resonator is exceptionally sensitive, a typical application, such as sensing or signal processing, requires the detection of signals from many resonators distributed over the surface of a chip. Therefore, one of the key technological challenges in the field of NEMS is development of multiplexed measurement techniques to detect the motion of a large number of NEMS resonators simultaneously. In this work, we address the important and difficult problem of interfacing with a large number of NEMS devices and facilitating the use of such arrays in, for example, sensing and signal processing applications. We report a versatile, all-optical technique to excite and read-out a distributed NEMS array. The NEMS array is driven by a distributed, intensity-modulated, optical pump through the photothermal effect. The ensuing vibrational response of the array is multiplexed onto a single, probe beam as a high-frequency phase modulation. The phase modulation is optically down converted to a low-frequency, intensity modulation using an adaptive full -field interferometer, and subsequently is detected using a charge-coupled device (CCD) array. Rapid and single-step mechanical characterization of approximately 60 nominally identical, high-frequency resonators is demonstrated. The technique may enable sensitivity improvements over single NEMS resonators by averaging signals coming from a multitude of devices in the array. In addition, the diffraction-limited spatial resolution may allow for position-dependent read-out of NEMS sensor chips for sensing multiple analytes or spatially inhomogeneous forces.
A non-contact ultra-broadband photoacoustic (PA) / photothermal (PT) microscopy system has been developed to
characterize material properties of specimens using optical transduction techniques. PT microscopy exploits optical
changes induced by heat to highlight the presence of inhomogeneities such as defects, contaminants, inclusions, and
impurities in materials. A monochromatic light source (e.g., a pulsed and amplitude-modulated laser) typically is used to
create the PA effect. Heating the material produces a stress distribution that launches broadband ultrasonic emissions.
Measurement of the ultrasonic emissions can be used to compute material properties like density, elastic modulus,
anisotropy, etc. Sub-surface features can be detected using time-reversal and back-propagation techniques. In this work,
PT-induced refractive index changes as well as the PA effect are detected optically on a microscopic scale using a
Michelson-interferometer configuration. The system has a spatial resolution of ~600 nm with a detection bandwidth of 1
GHz and a displacement sensitivity of 1 pm per root Hz. Experimental results from thin films, coatings,
nanoelectromechanical systems (NEMS) and biological samples demonstrate the versatility of the system as a
nondestructive tool for material characterization.
Conventional photoacoustic imaging (PAI) employs light pulses to produce a photoacoustic (PA) effect and detects the
resulting acoustic waves using an ultrasound transducer acoustically coupled to the target tissue. The resolution of
conventional PAI is limited by the sensitivity and bandwidth of the ultrasound transducer. We have developed an all-optical
versatile PAI system for characterizing ex vivo and in vivo biological specimens. The system employs noncontact
interferometric detection of the acoustic signals that overcomes limitations of conventional PAI. A 532-nm pump
laser with a pulse duration of 5 ns excited the PA effect in tissue. Resulting acoustic waves produced surface
displacements that were sensed using a 532-nm continuous-wave (CW) probe laser in a Michelson interferometer with a
GHz bandwidth. The pump and probe beams were coaxially focused using a 50X objective giving a diffraction-limited
spot size of 0.48 μm. The phase-encoded probe beam was demodulated using a homodyne interferometer. The detected
time-domain signal was time reversed using k-space wave-propagation methods to produce a spatial distribution of PA
sources in the target tissue. Performance was assessed using PA images of ex vivo rabbit lymph node specimens and
human tooth samples. A minimum peak surface displacement sensitivity of 0.19 pm was measured. The all-optical PAI
(AOPAI) system is well suited for assessment of retinal diseases, caries lesion detection, skin burns, section less
histology and pressure or friction ulcers.
Quantitative photoacoustics is emerging as a new hybrid modality to investigate diseases and cells in human pathology and cytology studies. Optical absorption of light is the predominant mechanism behind the photoacoustic effect. Therefore, a need exits to characterize the optical properties of specimens and to identify the relevant operating wavelengths for photoacoustic imaging. We have developed a custom low-cost spectrophotometer to measure the optical properties of human axillary lymph nodes dissected for breast-cancer staging. Optical extinction curves of positive and negative nodes were determined in the spectral range of 400 to 1000 nm. We have developed a model to estimate tissue optical properties, taking into account the role of fat and saline. Our results enabled us to select the optimal optical wavelengths for maximizing the imaging contrast between metastatic and noncancerous tissue in axillary lymph nodes.
Conventional photoacoustic microscopy (PAM) employs light pulses to produce a photoacoustic (PA) effect and detects the resulting acoustic waves using an ultrasound transducer acoustically coupled to the target. The resolution of conventional PAM is limited by the sensitivity and bandwidth of the ultrasound transducer. We investigated a versatile, all-optical PAM (AOPAM) system for characterizing in vivo as well as ex vivo biological specimens. The system employs non-contact interferometric detection of PA signals that overcomes limitations of conventional PAM. A 532-nm pump laser with a pulse duration of 5 ns excites the PA effect in tissue. Resulting acoustic waves produce surface displacements that are sensed using a 532-nm continuous-wave (CW) probe laser in a Michelson interferometer with a 1- GHz bandwidth. The pump and probe beams are coaxially focused using a 50X objective giving a diffraction-limited spot size of 0.48 μm. The phase-encoded probe beam is demodulated using homodyne methods. The detected timedomain signal is time reversed using k-space wave-propagation methods to produce a spatial distribution of PA sources in the target tissue. A minimum surface-displacement sensitivity of 0.19 pm was measured. PA-induced surface displacements are very small; therefore, they impose stringent detection requirements and determine the feasibility of implementing an all-optical PAM in biomedical applications. 3D PA images of ex vivo porcine retina specimens were generated successfully. We believe the AOPAM system potentially is well suited for assessing retinal diseases and other near-surface biomedical applications such as sectionless histology and evaluation of skin burns and pressure or friction ulcers.
Quantitative ultrasound (QUS) estimates derived from power spectra of pulse-echo signals are sensitive to mi- crostructure and potentially can differentiate among tissues. However, QUS estimates do not provide molecular specificity. We investigated the feasibility of obtaining quantitative photoacoustic (QPA) estimates for sensi- tivity to microstructure and chromophores for tissue classification. QPA methods were tested using gel-based phantoms containing uniformly dispersed, black polyethylene spheres (1E5 particles/ml) with nominal mean diameters of 23.5, 29.5, 42.0, and 58.0 μm. A pulsed, 532-nm laser excited the photoacoustic (PA) response. A single-element, 34-MHz transducer with a 12-mm focal length was raster scanned over the phantom to acquire 3D PA data. Normalized power spectra were generated from the PA signals within 2079, moving (50% overlap), 1-mm-cube regions-of-interest (ROIs) to provide three QPA estimates: spectral slope (SS), spectral intercept (SI), and effective absorber size (EAS). SS and SI were computed using a linear-regression approximation to the normalized spectrum in the -6-dB band. EAS was computed by fitting the normalized spectrum in the -20-dB band to the multi-sphere analytical solution. All estimates were correlated with the size of particles dispersed in the phantoms. SS decreased while SI increased with an increase in particle size. EAS was correlated with nominal particle diameter, but particles aggregation and the finite bandwidth of the PAI system resulted in outliers. SS, SI, and EAS for the 23.5-μm-phantom were -0.14±-0.04 dB/MHz, 4.8±1.3 dB, and 25.4±6.3 μm, respectively; the corresponding values for the 58.0-μm phantom were -0.47±-0.03 dB/MHz, 15.6±0.9 dB, and 82.7±0.9 μm.
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