This PDF file contains the front matter associated with SPIE Proceedings Volume 6982, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

Horizontal developments in communication systems have led to the emergence of new wireless technologies like WiMAX, 3G and 4G. These expansions can provide new opportunities for further advances and exciting applications in particular if we can integrate different technology standards into heterogeneous wireless networks. WiMAX and WiFi wireless networks are two examples of different standard technologies that cannot communicate with each other using existing protocols. These two standards differ in frequency, protocol and management mechanisms, and hence to construct a heterogeneous network using WiFi and WiMAX devices these differences need to be harmonised and resolved. Synchronization is the first step towards in such a process. In this paper we propose a private synchronization technique that enables WiFi and WiMAX devices to communicate with each other. Precise time synchronization in the micro second resolution range is required. The CPU clock is used as a reference for this private synchronization. Our private synchronization solution is based on interposing an extra thin layer between MAC and PHY layers in both WiFi and WiMAX. This extra thin layer will assign alternate synchronization and other duties to the two systems.

Existing Ad Hoc routing protocols are mostly based on efficiency-driven protocols. Malicious nodes can easily impair the performance of wireless ad hoc networks as a result of different actions such as packet dropping or black hole attacks without being detected. It is virtually impossible to find out these kinds of malicious before they attack, therefore it would be sensible to base detection of malicious nodes on post route discovery stage, i.e. when packets are transmitted on discovered routes. In this paper we shall review existing techniques for secure routing and propose to use credibility based route finding protocols. Each node would monitor its neighbors' pattern of delivering packets and regularly update their "credibility" according to certain criteria. The level of trust in any route will be based on the credits associated with the neighbor belonging to the discovered route. We shall evaluate the performance of the proposed scheme by modifying our simulation system so that each node has a dynamic changing "credit list" for its neighbors' behavior. We shall conduct a series of simulations with and without the proposed scheme and compare the results. We will demonstrate that the proposed mechanism is capable of isolating malicious nodes and thereby counteracting black hole attacks. We will discuss problems we encountered and our solutions. We would also further develop the protocol, to investigate the possibility of using the unique prime factorization theory to enable nodes acquiring more trust knowledge beyond its immediate neighborhood. Such an approach helps to further secure route-finding procedures.

WLAN networks are widely deployed and can be used for testbed and application developments in academic environments. This paper presents wireless positioning testbed and a related application implementation methodology as a case study. Nowadays state-of-the-art WLAN positioning systems achieve high location estimation accuracy. In designated areas the signal profile map can be designed and used for such a positioning. Coverage of WLAN networks is typically wider than the authorized areas and there might be network intrusion attempts from the vicinity areas such as parking lots, cafeterias, etc. In addition to conventional verification and authorization methods, the network can locate the user, verify if his location is in the authorized area and apply additional checks to find the violators.

This paper describes the concept of an intelligent high speed wireless ad-hoc network, which is currently being developed. The technology aims at, not replacing any of the existing standards, but aims to complement them in urban, military and hazardous environments. Known as Rhino, the technology is a platform independent, IP based network which will provide adequate bandwidth for real time video, audio and data traffic. The technology and specifications described in this paper are based on initial development of the technology.

An RFID-based mobile handheld inventory management system is proposed in this paper. Differing from the manual inventory management method, the proposed system works on the personal digital assistant (PDA) with an RFID reader. The system identifies electronic tags on the properties and checks the property information in the back-end database server through a ubiquitous wireless network. The system also provides a set of functions to manage the back-end inventory database and assigns different levels of access privilege according to various user categories. In the back-end database server, to prevent improper or illegal accesses, the server not only stores the inventory database and user privilege information, but also keeps track of the user activities in the server including the login and logout time and location, the records of database accessing, and every modification of the tables. Some experimental results are presented to verify the applicability of the integrated RFID-based mobile handheld inventory management system.

Malicious nodes are mounting increasingly sophisticated attacking operations on the Mobile Ad Hoc Networks (MANETs). This is mainly because the IP-based MANETs are vulnerable to attacks by various malicious nodes. However, the defense against malicious attack can be improved when a new layer of network architecture can be developed to separate true IP address from disclosing to the malicious nodes. In this paper, we propose a new algorithm to improve the defense against malicious attack (IDMA) that is based on a recently developed Assignment Router Identify Protocol (ARIP) for the clustering-based MANET management. In the ARIP protocol, we design the ARIP architecture based on the new Identity instead of the vulnerable IP addresses to provide the required security that is embedded seamlessly into the overall network architecture. We make full use of ARIP's special property to monitor gateway forward packets by Reply Request Route Packets (RREP) without additional intrusion detection layer. We name this new algorithm IDMA because of its inherent capability to improve the defense against malicious attacks. Through IDMA, a watching algorithm can be established so as to counterattack the malicious node in the routing path when it unusually drops up packets. We provide analysis examples for IDMA for the defense against a malicious node that disrupts the route discovery by impersonating the destination, or by responding with state of corrupted routing information, or by disseminating forged control traffic. The IDMA algorithm is able to counterattack the malicious node in the cases when the node lunch DoS attack by broadcast a large number of route requests, or make Target traffic congestion by delivering huge mount of data; or spoof the IP addresses and send forge packets with a fake ID to the same Target causing traffic congestion at that destination. We have implemented IDMA algorism using the GloMoSim simulator and have demonstrated its performance under a variety of operational conditions.

This paper aims to analyze the QoS performance of two main technology mechanisms, Multi-Protocol Label Switching (MPLS) and Differentiated Services (DS). The introduction of both mechanisms to support throughput and delay sensitive real-time media traffic will have an impact on critical applications with respect to QoS and traffic engineering. MPLS is a traffic forwarding mechanism that allows traffic to use multiple paths and DS is a mechanism that provides for aggregate traffic to be classified and conditioned at the edge of the network routers. The two modeled techniques and their performance will be evaluated with respect to their end-to-end delay. The QoS will be incorporated in both the MPLS and DS mechanisms while preserving the efficiencies of the backbone structure of the Internet, and also the performance is compared with the existing IP routing algorithms.

An advanced approach for adaptive nonlinear digital data processing is described in this article. Three primal computational structures referred to as Q-Measures, Q-Metrics, and Q-Aggregates are introduced and utilized in unison as highly adaptive data analysis handlers. The proposed approach relies on universal functionals using few parameters to characterize dynamic system behaviors in broad ranges of unconventional measure, metric, and aggregation spaces. We present this unique approach in application to real-valued signal processing tasks, with suitable optimization algorithms, so that the parameters of the proposed models can be tuned automatically. The new approach is tested on real data sets to enable applications in mobile communication systems and the experiments show promising results.

Steganography is the art of hiding information in a cover image so it is not readily apparent to a third party observer. There exist a variety of fractal steganographic methods for embedding information in an image. The main contribution of the previous work was to embed data by modifying the original, pre-existing image or embedding an encrypted datastream in an image. In this paper we propose a new fractal steganographic method. The fractal parameters of the image are altered by the steganographic data while the image is generated. This results in an image that is generated with the data already hidden in it and not added after the fact. We show that the input parameters of the algorithm, such as the type of fractal and number of iterations, will serve as a simple secret key for extracting the hidden information. We explain how the capacity of the image is affected by the variation of the parameters. We also demonstrate how standard steganographic detection algorithms perform against the generated images and analyze their capability to detect information hidden with this new technique

This paper presents a novel spatial data hiding scheme based on the Least Significant Bit insertion. The bitplane decomposition is obtained by using the (p, r) Fibonacci sequences. This decomposition depends on two parameters, p and r. Those values increase the security of the whole system; without their knowledge it is not possible to perform the same decomposition used in the embedding process and to extract the embedded information. Experimental results show the effectiveness of the proposed method.

For any given digital host image or audio file (or group of hosts) and any (block) transform domain of interest, we find an orthogonal set of signatures that achieves maximum sum-signal-to-interference-plus-noise ratio (sum- SINR) spread-spectrum message embedding for any fixed embedding amplitude values. We also find the sumcapacity optimal amplitude allocation scheme for any given total distortion budget under the assumption of (colored) Gaussian transform-domain host data. The practical implication of the results is sum-SINR, sumcapacity optimal multiuser/multisignature spread-spectrum data hiding in the same medium. Theoretically, the findings establish optimality of the recently presented Gkizeli-Pados-Medley multisignature eigen-design algorithm.

In this paper, we investigate the use of a family of transform domains in embedding hidden data.A new date hiding scheme that is based a pair of unmatched orthogonal transforms has been developed. The hidden message signal is transmitted via the residual channel of two different parameterized slant transforms. The properties of residual channel of parameterized slant transforms are characterized and performance of proposed scheme have been analyzed and simulated. We also discuss on the performance of the scheme and basis selection.

The ever-increasing Internet distribution of video content is echoed in ever-increasing efforts to devise systems balancing copyright protection and user rights. Watermarking is such an example: by persistently and imperceptibly associating some data with the host video, it offers at the same time a reliable and user-friendly solution for copyright infringement tracking. This paper takes a closer look at the apparent contradiction between watermarking (using the visual redundancy of the video to embed the data) and compression (eliminating the visual redundancy in order to speed up distribution and to alleviate storage requirements). In this respect, the viability of compressed domain watermarking is evaluated by analysing the visual effects of the MPEG-4 AVC stream alteration. The corpus consists of 10 video sequences of about 25 minutes each, coded at 256kbps and 64 kbps.

Full and partial encryption methods are important for subscription based content providers, such as internet and cable TV pay channels. Providers need to be able to protect their products while at the same time being able to provide demonstrations to attract new customers without giving away the full value of the content. If an algorithm were introduced which could provide any level of full or partial encryption in a fast and cost effective manner, the applications to real-time commercial implementation would be numerous. In this paper, we present a novel application of alpha rooting, using it to achieve fast and straightforward scalable encryption with a single algorithm. We further present use of the measure of enhancement, the Logarithmic AME, to select optimal parameters for the partial encryption. When parameters are selected using the measure, the output image achieves a balance between protecting the important data in the image while still containing a good overall representation of the image. We will show results for this encryption method on a number of images, using histograms to evaluate the effectiveness of the encryption.

Multimedia scrambling technologies ensure that multimedia content is only used by authorized users by transforming multimedia data into an unintelligible format. This paper introduces a new P-recursive sequence and two multimedia scrambling algorithms based on the P-recursive sequence. The P-recursive sequence is a more generalized sequence which can derive many well-known sequences such as the P-Fibonacci sequence, the P-Lucas sequence and P-Gray code. The algorithms can be used to scramble two or three dimensional multimedia data in one step. Electronic signatures, grayscale images and three-color-component images are all examples of 2-D and 3-D multimedia data which can utilize these algorithms. Furthermore, a security key parameter p may be chosen as different or the same values for each dimensional component of the multimedia data. Experiments show that the presented algorithms can scramble multimedia data at different levels of security by partially or fully encrypting multimedia data. They also have been demonstrated in the experiments to show good performance in known-plain text attack and common image attacks such as data loss, Gaussian noise, and Salt Pepper noise. The scrambled multimedia data can be completely reconstructed only by using the correct security keys.

Digital forensics investigator faces the challenge of reliability of forensic conclusions. Formal automatic analysis method is helpful to deal with the challenge. The finite state machine analysis method tries to determine all possible sequences of events that could have happened in a digital system during an incident. Its basic idea is to model the target system using a finite state machine and then explore its all possible states on the condition of available evidence. Timed mealy finite state machine is introduced to model the target system, and the formalization of system running process and evidence is presented to match the system running with possible source evidence automatically. Based on Gladyshev's basic reasoning method, general reasoning algorithms with multi strategies are developed to find the possible real scenarios. Case study and experimental results show that our method is feasible and adaptable to possible cases and takes a further step to practical formal reasoning for digital forensics.

This paper presents a novel model for the restoration of semitransparent blotches. It is based on two perception measures that describe a complicated object, like a semi-transparent blotch, on a complicated background, like textures in real-world images. Experimental results on archive photographs show that the proposed approach is able to achieve good results with a low computational effort and in a completely automatic way.

CCTV is used for an increasing number of purposes, and the new generation of digital systems can be tailored to serve a wide range of security requirements. However, configuration decisions are often made without considering specific task requirements, e.g. the video quality needed for reliable person identification. Our study investigated the relationship between video quality and the ability of untrained viewers to identify faces from digital CCTV images. The task required 80 participants to identify 64 faces belonging to 4 different ethnicities. Participants compared face images taken from a high quality photographs and low quality CCTV stills, which were recorded at 4 different video quality bit rates (32, 52, 72 and 92 Kbps). We found that the number of correct identifications decreased by 12 (~18%) as MPEG-4 quality decreased from 92 to 32 Kbps, and by 4 (~6%) as Wavelet video quality decreased from 92 to 32 Kbps. To achieve reliable and effective face identification, we recommend that MPEG-4 CCTV systems should be used over Wavelet, and video quality should not be lowered below 52 Kbps during video compression. We discuss the practical implications of these results for security, and contribute a contextual methodology for assessing CCTV video quality.

Among all existing biometric techniques, fingerprint-based identification is the oldest method, which has been successfully used in numerous applications. Fingerprint-based identification is the most recognized tool in biometrics because of its reliability and accuracy. Fingerprint identification is done by matching questioned and known friction skin ridge impressions from fingers, palms, and toes to determine if the impressions are from the same finger (or palm, toe, etc.). There are many fingerprint matching algorithms which automate and facilitate the job of fingerprint matching, but for any of these algorithms matching can be difficult if the fingerprints are overlapped or mixed. In this paper, we have proposed a new algorithm for separating overlapped or mixed fingerprints so that the performance of the matching algorithms will improve when they are fed with these inputs. Independent Component Analysis (ICA) has been used as a tool to separate the overlapped or mixed fingerprints.

This paper is concerned with face localization for visual speech recognition (VSR) system. Face detection and localization have got a great deal of attention in the last few years, because it is an essential pre-processing step in many techniques that handle or deal with faces, (e.g. age, face, gender, race and visual speech recognition). We shall present an efficient method for localization human's faces in video images captured on mobile constrained devices, under a wide variation in lighting conditions. We use a multiphase method that may include all or some of the following steps starting with image pre-processing, followed by a special purpose edge detection, then an image refinement step. The output image will be passed through a discrete wavelet decomposition procedure, and the computed LL sub-band at a certain level will be transformed into a binary image that will be scanned by using a special template to select a number of possible candidate locations. Finally, we fuse the scores from the wavelet step with scores determined by color information for the candidate location and employ a form of fuzzy logic to distinguish face from non-face locations. We shall present results of large number of experiments to demonstrate that the proposed face localization method is efficient and achieve high level of accuracy that outperforms existing general-purpose face detection methods.

Facial expressions are undoubtedly the most effective nonverbal communication. The face has always been the equation of a person's identity. The face draws the demarcation line between identity and extinction. Each line on the face adds an attribute to the identity. These lines become prominent when we experience an emotion and these lines do not change completely with age. In this paper we have proposed a new technique for face recognition which focuses on the facial expressions of the subject to identify his face. This is a grey area on which not much light has been thrown earlier. According to earlier researches it is difficult to alter the natural expression. So our technique will be beneficial for identifying occluded or intentionally disguised faces. The test results of the experiments conducted prove that this technique will give a new direction in the field of face recognition. This technique will provide a strong base to the area of face recognition and will be used as the core method for critical defense security related issues.

Poor quality can affect iris recognition accuracy. Feature information is an objective measure to evaluate the iris image quality. By combining Feature Information Measure (FIM), an occlusion measure and a dilation measure, a quality score is obtained that is well correlated with recognition accuracy. FIM is calculated as the distance between the distribution of iris features and a uniform distribution. Images of low contrast can appear to lack information from manual inspection, but actually perform well in iris recognition due to the presence of feature information. However, the FIM score for a low contrast image could be low. To adjust this affect, this paper developed an information based contrast invariant iris quality measure. For exhaustive comparison, CASIA 1.0, CASIA 2.0, ICE and WVU databases is used. In addition, the proposed method is compared to the convolution matrix, spectrum energy and Mexican hat wavelet approaches which represent a variety of approaches to iris quality measure. The experimental results show that the proposed quality measure is capable of predicting matching performance.

Iris recognition is an important method for identifying a person. Currently, most iris recognition methods are based on individual images. For non-cooperative user identification, video image based methods can provide more information. However, the iris image quality may vary from frame to frame. In this paper, we propose a real-time video based iris image processing method to eliminate the bad quality video image frames. It takes advantage of the correlations among video frames.

Iris segmentation is one of the most important steps in an iris recognition system. Its accuracy can directly affect the recognition accuracy. For non-cooperative users, the obtained images often do not have good quality. Under such conditions, the iris may be deformed, out-of-focus, or motion blurred. Sometimes, images do not have a valid iris. It is very challenging to segment the iris efficiently and accurately under a non-cooperative scenario. In this paper, we proposed a novel segmentation method that uses a coarse to fine approach to extract the iris region. The preliminary result shows the proposed method is efficient and accurate.

In this paper an adaptive feature-based approach to on-line signature verification is presented. Cryptographic techniques are employed to protect the extracted templates thus making impossible to derive the original biometric data from the stored information, as well as to generate multiple templates from the same original biometrics. Our approach allows to obtain, together with protection, also template cancelability thus guaranteeing user's privacy. The proposed authentication scheme is able to automatically adjust its parameters to the variability of each user's signature, thus obtaining a user adaptive system with enhanced performances with respect to a nonadaptive one. Experimental results show the effectiveness of our approach. Also the effects on the recognition performances when using the pen inclination features are investigated.

In mobile applications, computational complexity is an issue that limits sophisticated algorithms from being implemented on these devices. This paper provides an initial solution to applying pattern recognition systems on mobile devices by combining existing preprocessing algorithms for recognition. In pattern recognition systems, it is essential to properly apply feature preprocessing tools prior to training classification models in an attempt to reduce computational complexity and improve the overall classification accuracy. The feature preprocessing tools extended for the mobile environment are feature ranking, feature extraction, data preparation and outlier removal. Most desktop systems today are capable of processing a majority of the available classification algorithms without concern of processing while the same is not true on mobile platforms. As an application of pattern recognition for mobile devices, the recognition system targets the problem of steganalysis, determining if an image contains hidden information. The measure of performance shows that feature preprocessing increases the overall steganalysis classification accuracy by an average of 22%. The methods in this paper are tested on a workstation and a Nokia 6620 (Symbian operating system) camera phone with similar results.

Vast libraries of historic photographs are currently degrading due to the effects of semi-transparent water blotches. Most current restoration techniques involve heavy user interaction and are therefore too expensive to use for large quantities of images. This paper introduces the Localized Logarithmic Image Restoration Algorithm, which provides an automated system to restore the water blotches found in old photographs. The Algorithm utilizes a new localized image processing framework that allows it to improve upon existing restoration methods. This framework can be used for a variety of image processing applications. In the presented application of blotch removal, new logarithmic and statistical equations are introduced and used within the localized framework to complete the restoration. As shown by intensive computer simulations, the Algorithm produces enhanced results when compared to the existing automated algorithm. Improvements include superior edge removal around the blotch, better local contrast preservation, and expanded saturation reduction capabilities. In addition to the enhanced restoration quality of the results, the simulations are also promising with respect to computational time.

We introduce a novel method of splitting up color spaces into different components and then performing edge detection on individual color planes. The two general approaches taken for this are monochromatic and vector based. Also a new color space will be introduced in this paper, which is an improved version of the PCA algorithm. By analyzing the results of these algorithms we are able to determine which color space and edge detector is best suited for each algorithm. We test these methods using a number of well known edge detectors and color spaces. All the algorithms are tested on 17 different color images (12 natural, 5 synthetic). To analyze the results we use Pratt's Figure of Merit and Bovik's SSIM measures.

The technological efficiency and growing research in digital networks, devices, and transmission has made digital multi-media an increasingly popular alternative to conventional analog media. With the recent advancements in internet and multi-media technologies, the need for secured multimedia has increased exponentially. In this paper, we present a logical subband based novel secured multimedia system for digital images that could be used for both data hiding and cryptographic applications. It decomposes the cover into various integer valued sub-images that also provides the location map of flippable subband coefficients. Moreover, this approach enhances the capacity of data hiding system by a significant amount of data and simultaneously reduces the visible distortions that could occur in the image. In addition, this technique could also be employed for cryptographic applications, as this framework offers lossless recovery of the scrambled data and effective scrambling. Simulation results show that the proposed technique limits the changes to boundary regions of the image. Further, this approach can retrieve the embedded information without prior knowledge of the original unmarked image.

We present a fast massive information communication system for data collection from distributive sources such as cell phone users. As a very important application one can mention preventive notification systems when timely notification and evidence communication may help to improve safety and security through wide public involvement by ensuring easy-to-access and easy-to-communicate information systems. The technology significantly simplifies the response to the events and will help e.g. special agencies to gather crucial information in time and respond as quickly as possible. Cellular phones are nowadays affordable for most of the residents and became a common personal accessory. The paper describes several ways to design such systems including existing internet access capabilities of cell phones or downloadable specialized software. We provide examples of such designs. The main idea is in structuring information in predetermined way and communicating data through a centralized gate-server which will automatically process information and forward it to a proper destination. The gate-server eliminates a need in knowing contact data and specific local community infrastructure. All the cell phones will have self-localizing capability according to FCC E911 mandate, thus the communicated information can be further tagged automatically by location and time information.

Automated Explosive Detection Systems (EDS) utilizing Computed Tomography (CT) performs a series of X-ray scans of the luggage being checked, then various 2D projection images of the luggage are generated from the collected data set and sometimes 3D volumetric images of the luggage are generated in addition. Automatic explosives determination as to the presence of an explosive in the luggage is determined through extensive data manipulation of the 2D and 3D image sets, the results are then forwarded to a human interface for final review. The final determination as to whether the luggage contains an explosive and needs to be searched manually is performed by trained TSA (Transportation Security Administration) screeners following an approved TSA protocol. The TSA protocol has the screeners visually inspect the projection images and the renderings of the automated explosive results from detection to determine if the luggage needs to be suspected and consequently searched. Unlike conventional X-ray systems, the user interface for EDS systems are usually designed to display one bag at a time. However, in airport environments, there is usually more than one bag being processed. Therefore, segmentation is a crucial part of higher quality screening. If the screeners have to manually manipulate (zoom, pan, separate) the image, this increases overall screening time and decreases screener efficiency. This paper presents a novel image segmentation technique that is geared towards, though not exclusive to, automated explosive detection systems. The goal of this algorithm is to correctly separate each bag image to provide a higher quality screening process while reducing the overall screening time and luggage search rates.

As part of research conducted on the design of an efficient clutter covariance processor for DARPA's knowledge aided sensor signal processing expert reasoning (KASSPER) program a time-dual for information theory was discovered and named latency theory, this theory is discussed in this first of a multi-paper series. While information theory addresses the design of communication systems, latency theory does the same for recognition systems. Recognition system is the name given to the time dual of a communication system. A recognition system uses prior-knowledge about a signal-processor's input to enable the sensing of its output by a processing-time limited sensor when the fastest possible signal-processor replacement cannot achieve this task. A processor-coder is the time dual of a source coder. While a source coder replaces a signal-source to yield a smaller sourced-space in binary digits (bits) units a processor coder replaces a signal-processor to yield a smaller processing-time in binary operators (bors) units. A sensor coder is the time dual of a channel coder. While a channel coder identifies the necessary overhead-knowledge for accurate communications a sensor coder identifies the necessary prior-knowledge for accurate recognitions. In the second of this multipaper series latency theory is successfully illustrated with real-world knowledge aided radar.

In this second of a multi-paper series latency-information theory (LIT), the integration of information theory with its time dual, i.e., latency theory, is successfully applied to DARPA's knowledge aided sensor signal processing expert reasoning (KASSPER) program. LIT encapsulates the concept of the time dual of a lossy source coder, i.e., a lossy processor coder. A lossy processor coder is a replacement for a signal-processor. This lossy processor coder is faster, simpler to implement, and yields a better performance than the original signal-processor when the processor input appears in a highly compressed-decompressed lossy fashion. In particular, a lossy clutter covariance processor (CCP) architecture is investigated that has successfully replaced KASSPER's originally advanced lossless CCP and enabled its SAR imagery prior knowledge to be highly compressed-decompressed. This result is illustrated with a typical SAR image which is compresseddecompressed by a factor 8,172. Using this image and under severely taxing environmental disturbances outstanding detections are achieved with the lossy CCP. Furthermore, this result is derived with a lossy CCP that is at least five orders of magnitude faster and significantly simpler to implement than the corresponding lossless CCP whose SINR detection performance is nevertheless unsatisfactory. As a final comment it is also observed that LIT illuminates biological system studies since it provides a lossy mechanism that explains how outstanding detections may be arrived at by biological systems that use highly lossy compressed prior knowledge, e.g., when a human expertly detects a face seen only once before even though that face cannot be accurately described prior to such new viewing.

In this third of a multi-paper series the discovery of a space dual for the laws of motion is reported and named the laws of retention. This space-time duality in physics is found to inherently surface from a latency-information theory (LIT) that is treated in the first two papers of this multi-paper series. A motion-coder and a retention-coder are fundamental elements of a LIT's recognition-communication system. While a LIT's motion-coder addresses motion-time issues of knowledge motion, a LIT's retention-coder addresses retention-space issues of knowledge retention. For the design of a motion-coder, such as a modulation-antenna system, the laws of motion in physics are used while for the design of a retention-coder, such as a write/read memory, the newly advanced laws of retention can be used. Furthermore, while the laws of motion reflect a configuration of space certainty, the laws of retention reflect a passing of time uncertainty. Since the retention duals of motion concepts are too many to cover in a single publication, the discussion will be centered on the retention duals for Newton's Principia and the gravitational law, Coulomb's electrical law, Maxwell's equations, Einstein's relativity theory, quantum mechanics, and the uncertainty principle. Furthermore the retention duals will be illustrated with an uncharged and non-rotating black hole (UNBH). A UNBH is the retention dual of a vacuum since the UNBH and vacuum offer, from a theoretical perspective, the least resistance to knowledge retention and motion, respectively. Using this space-time duality insight it will be shown that the speed of light in a vacuum of c_M=2.9979 x 10⁸ meters/sec has a retention dual, herein called the pace of dark in a UNBH of c_R=6.1123 x 10⁶³ secs/m³ where 'pace' refers to the expected retention-time per retention-space for the 'dark' knowledge residing in a black hole.