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Prototyping and Testing of a Graphene-Oxide Tamper Evident Seal
Abstract
Structural Health Monitoring (SHM) technology has great unexplored potential in security applications. Specifically breakthroughs in graphene-oxide (GO) damage-detecting skins coupled with nonlinear, sparse signal processing techniques being used for SHM lend themselves to addressing the need for low-power remotely-readable tamper-evident seals. Assessing the integrity of a tamper-evident seal is inherently an SHM problem. In this case damage is caused by a human adversary, not the environment. This paper presents a novel architecture that leverages the tunable electrical properties of a GO-paper-based seal with a compressed-sensing (CS) acquisition protocol. This architecture allows the seal to characterize its integrity, while simultaneously providing an encrypted authentication feature making the seal difficult to counterfeit and/or spoof. The electrical properties of GO are sensitive to the traditional methods used to attack paper-based seals (mechanical lifting, solvents, heat/cold, steam). This property of GO allows us to determine if a seal has been tampered with simply by measuring its electrical properties. Specific areas of focus addressed by this work include the quantitative analysis of the encryption/authentication capabilities provided by CS, and methods for enhancing the detection of cracks/cuts propagating through the sensitive GO paper.
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In many applications of structural health monitoring (SHM) it is imperative or advantageous to have large sensor arrays in order to properly sense the state of health of the structure. Typically these sensor networks are implemented by placing a large number of sensors over a structure and running individual cables from each sensor back to a central measurement station. Data is then collected from each sensor on the network at a constant sampling rate regardless of the current timescales at which events are acting on the structure. These conventional SHM sensor networks have a number of shortfalls. They tend to have a large number of cables that can represent a single point of failure for each sensor as well as add significant weight and installation costs. The constant sampling rate associated with each sensor very quickly leads to large amounts of data that must be analyzed, stored, and possibly transmitted to a remote user. This leads to increased demands on power consumption, bandwidth, and size. It also taxes our current techniques for managing large amounts of data. For the last decade the goal of the SHM community has been to endow structures with the functionality of a biological nervous system. Despite this goal the community has predominantly ignored the biological nervous system as inspiration for building structural nervous systems, choosing instead to focus on experimental mechanics and simulation techniques. In this work we explore the use of a novel, bio-inspired, SHM skin. This skin makes use of distributed computing and asynchronous communication techniques to alleviate the scale of the data management challenge as well as reduce power. The system also periodically sends a ‘heat beat’ signal to provide state-of-health updates. This conductive skin was implemented using conductive ink resistors as well as with graphene-oxide capacitors.
We propose a public-key-based optical image cryptosystem for practical secure communications since conventional optical cryptosystems that use a symmetric algorithm are confronted by the problem of key delivery. The proposed system employs a hybrid architecture in which a double-random-phase encoding is used to cipher and decipher an image and an asymmetric algorithm is used for ciphering and deciphering the session key. To solve this problem of key delivery, the double-random-phase encoding algorithm is analyzed to establish a covert channel and therefore elucidate the phenomenon that the amplitude part of the ciphered image is less sensitive to quantization error than the other parts in the Fourier and output planes. The session key is then hidden in the covert channel setup in the ciphered image and extracted at the receiver side. Experimental results demonstrate that the amplitude parts in the Fourier and output planes are better suited to convey the session key because they enable reconstructed images with a higher visual quality to be obtained. (C) 2003 Society of Photo-Optical Instrumentation Engineers.
Results in compressed sensing describe the feasibility of reconstructing sparse signals using a small number of linear measurements. In addition to compressing the signal, do these measurements provide secrecy? This paper considers secrecy in the context of an adversary that does not know the measurement matrix used to encrypt the signal. We demonstrate that compressed sensing-based encryption does not achieve Shannon's definition of perfect secrecy, but can provide a computational guarantee of secrecy.
The compressed sensing (CS) paradigm unifies sensing and compression of sparse signals in a simple linear measurement step. Reconstruction of the signal from the CS measurements relies on the knowledge of the measurement matrix used for sensing. Generation of the pseudo-random sensing matrix utilizing a cryptographic key, offers a natural method for encrypting the signal during CS. This CS based encryption has the inherent advantage that encryption occurs implicitly in the sensing process - without requiring additional computation. Additionally, the robustness of recovery from compressed sensing, allows a new form of ldquorobust encryptionrdquo for multimedia data, wherein the signal is recoverable with high fidelity despite the introduction of additive noise in the encrypted data. In this paper, we examine the security and robustness of this CS based encryption method. The security implications are investigated by considering brute force and structured attacks. Robustness is characterized empirically. Our analysis and results indicate that the computational complexity of these attacks renders them infeasible in practice. In addition, the CS based encryption is found to have fair robustness against additive noise, making it a promising ldquorobust encryptionrdquo technique for multimedia.
Microscale supercapacitors provide an important complement to batteries in a variety of applications, including portable electronics. Although they can be manufactured using a number of printing and lithography techniques, continued improvements in cost, scalability and form factor are required to realize their full potential. Here, we demonstrate the scalable fabrication of a new type of all-carbon, monolithic supercapacitor by laser reduction and patterning of graphite oxide films. We pattern both in-plane and conventional electrodes consisting of reduced graphite oxide with micrometre resolution, between which graphite oxide serves as a solid electrolyte. The substantial amounts of trapped water in the graphite oxide makes it simultaneously a good ionic conductor and an electrical insulator, allowing it to serve as both an electrolyte and an electrode separator with ion transport characteristics similar to that observed for Nafion membranes. The resulting micro-supercapacitor devices show good cyclic stability, and energy storage capacities comparable to existing thin-film supercapacitors.
In this paper, we propose and study the use of alternating direction algorithms for several -norm minimization problems arising from sparse solution recovery in compressive sensing, including the basis pursuit problem, the basis-pursuit denoising problems of both unconstrained and constrained forms, as well as others. We present and investigate two classes of algorithms derived from either the primal or the dual forms of the -problems. The construction of the algorithms consists of two main steps: (1) to reformulate an -problem into one having partially separable objective functions by adding new variables and constraints; and (2) to apply an exact or inexact alternating direction method to the resulting problem. The derived alternating direction algorithms can be regarded as first-order primal-dual algorithms because both primal and dual variables are updated at each and every iteration. Convergence properties of these algorithms are established or restated when they already exist. Extensive numerical results in comparison with several state-of-the-art algorithms are given to demonstrate that the proposed algorithms are efficient, stable and robust. Moreover, we present numerical results to emphasize two practically important but perhaps overlooked points. One point is that algorithm speed should always be evaluated relative to appropriate solution accuracy; another is that whenever erroneous measurements possibly exist, the -norm fidelity should be the fidelity of choice in compressive sensing.
An improved method for the preparation of graphene oxide (GO) is described. Currently, Hummers' method (KMnO(4), NaNO(3), H(2)SO(4)) is the most common method used for preparing graphene oxide. We have found that excluding the NaNO(3), increasing the amount of KMnO(4), and performing the reaction in a 9:1 mixture of H(2)SO(4)/H(3)PO(4) improves the efficiency of the oxidation process. This improved method provides a greater amount of hydrophilic oxidized graphene material as compared to Hummers' method or Hummers' method with additional KMnO(4). Moreover, even though the GO produced by our method is more oxidized than that prepared by Hummers' method, when both are reduced in the same chamber with hydrazine, chemically converted graphene (CCG) produced from this new method is equivalent in its electrical conductivity. In contrast to Hummers' method, the new method does not generate toxic gas and the temperature is easily controlled. This improved synthesis of GO may be important for large-scale production of GO as well as the construction of devices composed of the subsequent CCG.
In this paper, compressive sensing is combined with a chaotic key based generation of measurement matrix to provide an effective encryption algorithm for multimedia security. Block-based compressive sensing provides a better way in the field of image and video transmission by reducing the memory requirements and complexity, where as multiple hypothesis prediction provides a competent way in improving PSNR during reconstruction of block based compressive sensed images and videos. The measurement matrix Φ place a crucial role in this compressive sensing and as well as in the reconstruction process. A possibility to generate secure measurement matrix using piecewise linear chaotic map (PWLCM) as the seed and then hiding initial condition, system parameter, number of iterations of PWLCM as the key enable the sender to incorporate room for encryption along with the compression in a single step. The above mentioned scheme provides high level of data security, reduced complexity, compression with a good reconstruction quality and beside all it reduce the burden of sending the measurement matrix along with the data which further reduces the complexity in over all compressive sensing framework.
The simple structure of compressed sensing allows its use not only for low-complexity compression but also for low-complexity encryption. Augmenting compressed sensing to secure information is based on using the sensing matrix as a symmetric encryption key. This imposes the requirement that the key is either preinstalled before deployment or is agreed over some secure communication channel. Both options are problematic when considering a wireless network comprised of nodes with limited resources that could be compromised. This paper proposes an encryption framework where the sensing matrix is established using wireless physical layer security and linear feedback shift register with corresponding m-sequences. Using a Rician fading channel, it is shown that the proposed framework generates valid compressed sensing matrices while preventing access from an eavesdropper in close proximity to one of the legitimate participants.
Executive Summary Tamper-indicating seals can have an important role to play in customs, nonproliferation, law enforcement, and counter-terrorism. Unfortunately, the tamper-indicating seals currently available, given how they are typically used, can be quickly and easily spoofed by almost anyone. High-tech electronic seals are not automatically better than simple mechanical seals, and are often worse. More reliable tamper detection is possible with greatly enhanced training for seal installers and inspectors, better seals, and a more thoughtful use of high-technology.
This article presents novel results concerning the recovery of signals from undersampled data in the common situation where such signals are not sparse in an orthonormal basis or incoherent dictionary, but in a truly redundant dictionary. This work thus bridges a gap in the literature and shows not only that compressed sensing is viable in this context, but also that accurate recovery is possible via an ℓ1-analysis optimization problem. We introduce a condition on the measurement/sensing matrix, which is a natural generalization of the now well-known restricted isometry property, and which guarantees accurate recovery of signals that are nearly sparse in (possibly) highly overcomplete and coherent dictionaries. This condition imposes no incoherence restriction on the dictionary and our results may be the first of this kind. We discuss practical examples and the implications of our results on those applications, and complement our study by demonstrating the potential of ℓ1-analysis for such problems.
Graphene is a rapidly rising star on the horizon of materials science and condensed-matter physics. This strictly two-dimensional material exhibits exceptionally high crystal and electronic quality, and, despite its short history, has already revealed a cornucopia of new physics and potential applications, which are briefly discussed here. Whereas one can be certain of the realness of applications only when commercial products appear, graphene no longer requires any further proof of its importance in terms of fundamental physics. Owing to its unusual electronic spectrum, graphene has led to the emergence of a new paradigm of 'relativistic' condensed-matter physics, where quantum relativistic phenomena, some of which are unobservable in high-energy physics, can now be mimicked and tested in table-top experiments. More generally, graphene represents a conceptually new class of materials that are only one atom thick, and, on this basis, offers new inroads into low-dimensional physics that has never ceased to surprise and continues to provide a fertile ground for applications.
Individual graphene oxide sheets subjected to chemical reduction were electrically characterized as a function of temperature and external electric fields. The fully reduced monolayers exhibited conductivities ranging between 0.05 and 2 S/cm and field effect mobilities of 2-200 cm2/Vs at room temperature. Temperature-dependent electrical measurements and Raman spectroscopic investigations suggest that charge transport occurs via variable range hopping between intact graphene islands with sizes on the order of several nanometers. Furthermore, the comparative study of multilayered sheets revealed that the conductivity of the undermost layer is reduced by a factor of more than 2 as a consequence of the interaction with the Si/SiO2 substrate.
Conventional approaches to sampling signals or images follow Shannon's theorem: the sampling rate must be at least twice the maximum frequency present in the signal (Nyquist rate). In the field of data conversion, standard analog-to-digital converter (ADC) technology implements the usual quantized Shannon representation - the signal is uniformly sampled at or above the Nyquist rate. This article surveys the theory of compressive sampling, also known as compressed sensing or CS, a novel sensing/sampling paradigm that goes against the common wisdom in data acquisition. CS theory asserts that one can recover certain signals and images from far fewer samples or measurements than traditional methods use.
Tamper indicating seals: practices, problems, and standards. In: World Customs Organization Security Meeting
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