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During the COVID‐19 pandemic, the United States released the CDC‐issued vaccination card to document the status of immunizations. It eventually was used as a verification system to allow patrons to safely access public venues. This is/was apparently a simple printed piece of paper with minimal security features which made it an easy target for counterfeiters with little expertise required. Those unvaccinated who wished to enter areas that required proof of the COVID‐19 vaccine were soon finding alternative illegal methods to do so which led to public health concerns. This research was divided into two parts. Part A aimed to forensically identify the security features with a video spectral comparator and a stereomicroscope. Ten "known" blank cards were collected directly from dispensaries that administered the vaccine and 68 "unknowns" from individuals who received the COVID‐19 vaccine. Part B aimed to evaluate the authentication systems employed by countries outside the United States to propose a model on how the vaccination card could be improved and what security features should be included for future instances requiring proof of immunization. The results revealed the CDC document was produced with minimal security features making the document prone to counterfeiting. Furthermore, based on the information collected from other countries' vaccination certificates, it is recommended to develop a dual authentication system, with digital and printable aspects, that contains a QR code linked to a database. Other security features may include a non‐optical brightener substrate, security fibers, a watermarked logo, offset printing, and a geographical color‐coded system. [ABSTRACT FROM AUTHOR]

As the importance of reliable multimedia content increases in today's society, image forensics is a growing field of research. The act of copying and pasting specific parts of an image, known as copy‐move forgery, may be utilized for illegal or unethical purposes. Just as with other vision‐related technologies, the accuracy of forensic analysis depends on having an appropriate image representation. Most existing feature extraction techniques do not accurately reflect the underlying image content leading to reduced performance. In this article, to detect the copy‐move forgery attack, the Generic Radial Harmonic Fourier Moment (GRHFM) is proposed for reliable and distinctive image representation. The algorithm has the ability to effectively manipulate the distribution of zeros to emphasize certain image regions. Additionally, the relationships between complex exponentials and trigonometric functions are exploited to efficiently compute and easily implement the transform kernels. The efficacy of the algorithm is illustrated through experiments on dense‐domain‐based matching patterns. Experimental results on five benchmarking databases prove the effectiveness of the proposed approach compared with the state‐of‐the‐art methods. According to the average scores, the proposed method demonstrates superior accuracy in overall localization performance. The F1 score, precision, and recall percentage values obtained are 92.5, 95.44, and 91.96, respectively. Robustness experiments on more challenging attacks are also conducted on FAU dataset. Results show that the proposed framework satisfies invariance to the various image variations, and thus an enhanced robustness compared to the previous methods. Moreover, the advantage of reasonable computational cost implies its potential use in real‐world forensic applications. [ABSTRACT FROM AUTHOR]

Copy‐move forgeries are a conceptual sort of image retouching that involves duplicating a portion of an image and moving it to a different position within the original image, whether by modifying the duplicated part or just moving it altogether. To identify cloned portions that have been reproduced into the same digitized image, the suggested hybrid features in this article combine using the Hessian and Raw patch features on gray‐level images. Using a suggested model that combines patch features built on key points detected by the Hessian detector on gray‐level image, localization of duplicated and pasted portions of the manipulated image were found. After using the combined features in the matching step, the parallelism condition was applied together with the random sample consensus method to eliminate mismatches. Two databases, GRIP and the image manipulation dataset (IMD), were used for the detection and characterization, and the empirical findings show that the approach was successful in achieving an F1 score 100% for the GRIP database. Additionally, with the IMD database, it produced a 92.13% F1 score. The proposed method was also shown to be effective by obtaining high F1 scores in images where noise, JPEG compression, and scaling attacks were applied to make forgery detection difficult. [ABSTRACT FROM AUTHOR]

The utilization of handwritten electronic signatures has expanded in various application scenarios, leading to an increased demand for identification. Unlike handwriting signatures, handwritten electronic signatures offer the advantage of extracting dynamic feature data, including writing pressure, velocity, and acceleration. In this study, the Fourier transform was employed to extract 18 characteristics from the time domain and frequency domain of writing pressure, velocity, and acceleration. The experimental findings revealed distinguishable differences between genuine signatures and random forgeries in writing pressure. However, no statistically significant differences were observed in writing velocity and writing acceleration. Moreover, significant differences were detected in most characteristics when comparing genuine signatures with freehand imitation forgeries and tracing imitation forgeries. The canonical discriminant analysis was performed between the genuine and Non‐genuine signatures; the cross‐validation estimated the discriminating power of these characteristics with a satisfactory result. The study proposed a new approach to analyzing handwritten electronic signatures using time‐domain and frequency‐domain characteristics and demonstrated its effectiveness in the examination. [ABSTRACT FROM AUTHOR]

The quality of counterfeit items has increased dramatically, with modern global manufacturing being able to duplicate the materials, construction, and visual features of items. Detection of fraudulent coinage can parallel authentication of food, beverages, and manufactured goods by studying product‐inherent features. Counterfeit detection is performed by comparing an Example group with a Questioned group. A model is developed for both groups using standard tests on individual pieces. Coin weight is used here as an illustration. The model should also follow the natural science of the system. In this case, the manufacturing process variation is known and steady, and the underlying distribution is known or can be determined from authentic pieces. The proposed detection method uses testing of many individual pieces, then using reverse‐quality‐engineering methods to identify possible sources. This strategy looks at the variation between individual pieces to determine the process capability of a machine, assembly line, or plant to create product consistency for a manufacturer. Fraudulent items may be manufactured within specification, but demonstrate a manufacturing process capability different than that of the authentic manufacturer. In this report, we examine the model previously reported and use reconstruction techniques to re‐create the evidence set to validate the model, increase model accuracy, and confirm the conclusion previously reached, showing that the Questioned set is likely over 37% non‐conforming by weight. In this case, the decision outcome of the analysis was improved by using additional methods not included in the modeling software package originally used. [ABSTRACT FROM AUTHOR]

Document forgery is a significant issue in Korea, with around ten thousand cases reported every year. Analyzing paper plays a crucial role in examining questionable documents such as marketable securities and contracts, which can aid in solving criminal cases of document forgery. Paper analysis can also provide essential insights in other types of criminal cases, serving as an important clue for solving cases such as the source of a blackmail letter. The papermaking process generates distinct forming fabric marks and formations, which are critical features for paper classification. These characteristics are observable under transmitted light and are created by the forming fabric pattern and the distribution of pulp fibers, respectively. In this study, we propose a novel approach for paper identification based on hybrid features. This method combines texture features extracted from images converted using the gray‐level co‐occurrence matrix (GLCM) approach and a convolutional neural network (CNN), with another set of features extracted by the CNN using the same images as input. We applied the proposed method to classification tasks for seven major paper brands available in the Korean market, achieving an accuracy of 97.66%. The results confirm the applicability of this method for visually inspecting paper products and demonstrate its potential for assisting in solving criminal cases involving document forgery. [ABSTRACT FROM AUTHOR]

The advancements in Image editing techniques produce realistic‐looking artificial images with ease. These images can easily circumvent the forensic systems making the authentication process more tedious and difficult. To overcome this problem, we introduce a modern convolutional neural network (CNN) named ForensicNet, inspired by the recent developments in computer vision. The three major contributions of our CNNs are inverted bottleneck, separate downsampling layers, and using depth‐wise convolutions for mixing information in the spatial dimension. The inverted bottlenecks help improve accuracy and reduce network parameters/FLOPs. The separate downsampling layers help converge the network. The normalization layers also help stabilize training whenever the spatial resolution is changed. The depth‐wise convolution is a grouped convolution where the number of groups and channels are the same. The experiments show that ForensicNet outperforms the state‐of‐the‐art methods by a large margin. [ABSTRACT FROM AUTHOR]

Counterfeiting of banknotes remains a severe threat to economic security and social stability. The characterization of banknote has mainly relied on the assessment of various security features applied to the surface of the note. However, the surface features are easy to forge and contain insufficient information to discover the source. In this paper, a novel approach for banknote characterization has been proposed by employing spectral‐domain optical coherence tomography (SD‐OCT) that can provide structural and optical features. Three groups of counterfeit Chinese 100 Yuan banknotes produced by different printing manners and one group of authentic banknotes were examined by SD‐OCT without any sample preparation and four distinct areas were selected for imaging. High‐resolution tomographic and three‐dimensional (3D) volumetric OCT images were obtained and a set of features were first revealed to characterize the banknotes qualitatively and quantitatively. The results demonstrated that SD‐OCT was effective to detect and classify different types of counterfeit banknotes and could potentially be used to link counterfeit banknotes to their sources in a fast, simple and nondestructive manner. [ABSTRACT FROM AUTHOR]

With recent advancements in image processing and printing technology, home printers have improved in performance and grown more widespread. As such, they have been increasingly used in counterfeiting and forgery. Most counterfeit bills in Korea have been created using home scanners and printers. The identification of printer model is thus necessary to rapidly track down criminals and solve crimes. Household printers can be largely divided into inkjet and laser printers. These two types of printers print halftone textures instead of continuous images. This study proposed a technique of printer classification based on halftone textures that can be observed in printed documents. Since halftone textures are expressed as periodic lattices, the images were transformed via FFT, which is highly effective at expressing periodicity. ResNet, known for its superior gradient flow, was used for training. The experiment was conducted on 12 color laser jets and 2 inkjets. Scans of bills printed by each printer were used, and halftone texture analysis was performed on these images for printer model classification. Each image was cropped into several parts; one of the cropped parts was analyzed. The analysis showed that laser printers could be 100% distinguished from inkjet printers. An accuracy of 98.44% was achieved in make classification. When 50 cropped images were used instead of a single image, the technique achieved 100% accuracy in model classification. The proposed technique is non‐destructive; it offers high accessibility and efficiency as it can be performed using a scanner alone, without requiring additional optical equipment. [ABSTRACT FROM AUTHOR]

The excessive prescription of benzodiazepines is putting more people at risk of dependence on these drugs and is exacerbating the fatal overdose toll of opioids. A rapid and sensitive SERS method has been developed for trace detection of select benzodiazepines in low‐dosage suspect counterfeit tablets, capsules, and injectable solutions using two different portable handheld Raman spectrometers equipped with either a 785‐nm laser or a 1064‐nm laser. A total of 169 samples and blanks were examined using five handheld Raman spectrometers, which provided data set of 729 examinations. The extraction/SERS procedures yielded true positive rates above 90% for alprazolam, diazepam, and midazolam using the 1064‐nm device and yielded true positive rates above 95% for alprazolam, clonazepam, diazepam, estazolam, midazolam, and temazepam using the 785‐nm device; however, the extraction/SERS procedures yielded true positive rates below 60% for lorazepam and triazolam. The minimum concentration (Cmin) of the benzodiazepine standards that reproducibly yielded a positive match ranged from 1 to 10 μg/ml using the 1064‐nm laser device and from 0.5 to 50 μg/ml using the 785‐nm laser device. For the analysis of authentic and suspect counterfeit tablets containing these benzodiazepines, the measured Cmin ranged between 10 and 15 µg per tablet or capsule for 1064‐nm laser device and 1–100 µg per tablet or capsule for 785‐nm laser device. The developed methods are simple, rapid, and ideal for screening suspect benzodiazepine‐containing pharmaceutical products at satellite laboratories located within or near international mail facilities and express courier hubs. [ABSTRACT FROM AUTHOR]

Traditional pollen preparation techniques provide clear residues for pollen identification; however, such methods are time‐consuming, requiring repeated centrifugation, heating, and digestion with high‐concentration hazardous chemicals. Tobacco leaves can effectively trap environmental pollen due to hairy surface and terpene‐rich exudates. A new tobacco sample processing method was developed by using different extraction chemistry with surfactant. Marlboro Gold cigarettes were employed as model samples for method development. Parameters critical for pollen extraction, which include number of cigarette sticks used, extraction solution, and extraction temperature, were optimized. By using 1% dishwashing detergent to treat three cigarettes at room temperature, the improved method was able to recover sufficient pollen for microscopic analysis in three repeated centrifuge‐washing steps and omit hazardous chemicals involved in traditional methods. We focused on the pollen of common ragweed (Ambrosia artemisiifolia), a plant native to North America, as an indicator to differentiate genuine and counterfeit U.S. brand cigarettes. Results from analyzing randomly purchased genuine (authenticated by forensic examination) and known counterfeit Marlboro Gold provided by law enforcement revealed that a significant amount (39%) of Ambrosia were consistently present in all genuine samples, while counterfeit contained none or only trace count. Similar results were found in other counterfeit U.S. brand cigarettes (all seized in the U.S.) involved in this study as well. Lack of Ambrosia in cigarette strongly indicates the product was not originated in the United States. [ABSTRACT FROM AUTHOR]

This study describes the performance of handheld Raman devices for determining whether suspect pharmaceutical tablets declared to contain controlled substances were consistent with authentic (CWA) or not consistent with authentic (NCWA) tablets using a simple, rapid, field‐friendly method capable of being used by nonexperts. Twenty‐five authentic products and 84 known NCWA tablets were examined using three "parent" devices for a total of 327 analyses. On average, the parent devices yielded a true pass rate of 100%, a true fail rate of 98.4%, a false pass rate of 1.6%, and a false fail rate of 0%. The methods/libraries were then transferred to 13 identical "daughter" devices, which were used to examine 10 suspect finished dosage forms in duplicate (six known NCWA tablets and four authentic tablets) for a total of 260 measurements. On average, the daughter devices had a true pass rate of 100%, a true fail rate of 95.5%, a false pass rate of 4.5%, and a false fail rate of 0.0%. These data demonstrate that the parent–daughter electronic transfer method was successful, which permits the ability to develop methods in the laboratory that can be seamlessly pushed out to field devices. The methods can then be used to (i) prioritize samples for additional testing using other more time‐consuming laboratory‐based techniques needed to detect and quantify active ingredients and (ii) help support the interdiction of dangerous tablets at ports of entry, thereby preventing them from reaching the supply chain. [ABSTRACT FROM AUTHOR]

Disappearing inks can be used for forgeries in many fields. In this study, thymolphthalein indicator solution was prepared as a disappearing ink. A total of 54 different solutions containing thymolphthalein were prepared at six different concentrations and nine different pH values. Among the prepared solutions, 0.16 g/50 mL and 0.32 g/65 mL thymolphthalein at pH 14 were the optimum solutions that were not distinguishable from regular ink when applied to promissory note. Fountain pens were filled with the abovementioned ink solutions and applied to promissory notes for experimental purposes. After 40 h, ink residues were not visible on promissory notes written with the ink with the optimum pH (pH = 14) value. To decipher the entries that disappeared, an instrumental method (Video Spectral Comparator‐8000) and a chemical method (using NH3 vapor) were used, succeeded at 0.32 g/65 mL, but failed at 0.16 g/50 mL thymolphthalein. Therefore, NH3 had to be sprayed for 0.16 g/50 mL with negligible harm. [ABSTRACT FROM AUTHOR]

In this study, the stability and specificity of a counterfeit protection system (CPS) code were determined. This research involved an analysis of a counterfeit protection system code unit over time using the pattern location measurement method. We collected 379 sample sheets from 196 printers or photocopiers, covering 14 original brands, including 129 models. There was an interval of at least two months between the collections of samples from each machine. Four types of characteristics were established: CPS pattern unit, distance of the CPS unit, position of dots, size and shape of the dot. Except for the partial changes in the Xerox brand, no other brand exhibited changes over time. This implies that the CPS characteristics are stable. Meanwhile, no correlation was noted between the combinations of the characteristic systems in the collected samples, which implied strong specificity. [ABSTRACT FROM AUTHOR]

Abstract: Nowadays, surveillance systems are used to control crimes. Therefore, the authenticity of digital video increases the accuracy of deciding to admit the digital video as legal evidence or not. Inter‐frame duplication forgery is the most common type of video forgery methods. However, many existing methods have been proposed for detecting this type of forgery and these methods require high computational time and impractical. In this study, we propose an efficient inter‐frame duplication detection algorithm based on standard deviation of residual frames. Standard deviation of residual frame is applied to select some frames and ignore others, which represent a static scene. Then, the entropy of discrete cosine transform coefficients is calculated for each selected residual frame to represent its discriminating feature. Duplicated frames are then detected exactly using subsequence feature analysis. The experimental results demonstrated that the proposed method is effective to identify inter‐frame duplication forgery with localization and acceptable running time. [ABSTRACT FROM AUTHOR]

A prototype using simple mathematical treatment of the pen pressure data recorded by a digital pen movement recording device was derived. In this study, a total of 48 sets of signature and initial specimens were collected. Pearson's correlation coefficient was used to compare the data of the pen pressure patterns. From the 820 pair comparisons of the 48 sets of genuine signatures, a high degree of matching was found in which 95.4% (782 pairs) and 80% (656 pairs) had rPA > 0.7 and rPA > 0.8, respectively. In the comparison of the 23 forged signatures with their corresponding control signatures, 20 of them (89.2% of pairs) had rPA values < 0.6, showing a lower degree of matching when compared with the results of the genuine signatures. The prototype could be used as a complementary technique to improve the objectivity of signature examination and also has a good potential to be developed as a tool for automated signature identification. [ABSTRACT FROM AUTHOR]

This study presents a wavelet analysis of resultant velocity features belonging to genuine and forged groups of signature sample. Signatures of individuals were initially classified based on visual human perceptions of their relative sizes, complexities, and legibilities of the genuine counterparts. Then, the resultant velocity was extracted and modeled through wavelet analysis from each sample. The wavelet signal was decomposed into several layers based on maximum overlap discrete wavelet transform ( MODWT). Next, the zero crossing rate features were calculated from all the high wavelet sub-bands. A total of seven hypotheses were then tested using a two-way ANOVA testing methodology. Of these, four hypotheses were conducted to test for significance differences between distributions. In addition, three hypotheses were run to provide test for interaction between two factors of signature authentication versus perceived classification. The results demonstrated that both feature distributions belonging to genuine and forged groups of samples cannot be distinguished by themselves. Instead, they were significantly different under the influence of two other inherent factors, namely perceived size and legibility. Such new findings are useful information particularly in providing bases for forensic justifications in establishing the authenticity of handwritten signature specimens. [ABSTRACT FROM AUTHOR]

Digital image forgery detection is important because of its wide use in applications such as medical diagnosis, legal investigations, and entertainment. Copy-move forgery is one of the famous techniques, which is used in region duplication. Many of the existing copy-move detection algorithms cannot effectively blind detect duplicated regions that are made by powerful image manipulation software like Photoshop. In this study, a new method is proposed for blind detecting manipulations in digital images based on modified fractal coding and feature vector matching. The proposed method not only detects typical copy-move forgery, but also finds multiple copied forgery regions for images that are subjected to rotation, scaling, reflection, and a mixture of these postprocessing operations. The proposed method is robust against tampered images undergoing attacks such as Gaussian blurring, contrast scaling, and brightness adjustment. The experimental results demonstrated the validity and efficiency of the method. [ABSTRACT FROM AUTHOR]

The aims of this study were to determine if computer-measured dynamic features (duration, size, velocity, jerk, and pen pressure) differ between genuine and simulated signatures. Sixty subjects (3 equal groups of 3 signature styles) each provided 10 naturally written (genuine) signatures. Each of these subjects then provided 15 simulations of each of three model signatures. The genuine ( N = 600) and simulated ( N = 2700) signatures were collected using a digitizing tablet. MovAlyzeR® software was used to estimate kinematic parameters for each pen stroke. Stroke duration, velocity, and pen pressure were found to discriminate between genuine and simulated signatures regardless of the simulator's own style of signature or the style of signature being simulated. However, there was a significant interaction between style and condition for size and jerk (a measure of smoothness). The results of this study, based on quantitative analysis and dynamic handwriting features, indicate that the style of the simulator's own signature and the style of signature being simulated can impact the characteristics of handwriting movements for simulations. Writer style characteristics might therefore need to be taken into consideration as potentially significant when evaluating signature features with a view to forming opinions regarding authenticity. [ABSTRACT FROM AUTHOR]

Because of the rapidly increasing use of digital composite images, recent studies have identified digital forgery and filtering regions. This research has shown that interpolation, which is used to edit digital images, is an effective way to analyze digital images for composite regions. Interpolation is widely used to adjust the size of the image of a composite target, making the composite image seem natural by rotating or deforming. As a result, many algorithms have been developed to identify composite regions by detecting a trace of interpolation. However, many limitations have been found in detection maps developed to identify composite regions. In this study, we analyze the pixel patterns of noninterpolation and interpolation regions. We propose a detection map algorithm to separate the two regions. To identify composite regions, we have developed an improved algorithm using minimum filer, Laplacian operation and maximum filters. Finally, filtering regions that used the interpolation operation are analyzed using the proposed algorithm. [ABSTRACT FROM AUTHOR]

Seals have been frequently used to certify that individuals or organizations have authorized or approved a document that bears these impressions. Much attention has been focused on the detection of forged seal impressions to expose and prevent seal-related frauds. This paper describes an image-processing technique that detects seal impressions transferred from a genuine document to a target document using transcription media. The proposed method utilizes a three-dimensional (3-D) scanner to generate a pressure trace map of the suspect seal impression. After utilizing a noise-reduction algorithm to improve image quality, the pressure map is aligned with a 2-D image of the same seal impression. The pressure ratio, determined by comparing the pressure map and inked impression of a suspect seal, can be used to determine whether the seal is genuine or was transferred to the target document. The results show that the proposed technique successfully identified transcribed seal impressions with an error rate of <1%. [ABSTRACT FROM AUTHOR]

Evaluation of paper brightness in multipage documents is a practice of forensic document examiners when there is a question of a page insertion or substitution. This article demonstrates that occasional errors occur in the manufacturing process that affects the consistency of paper brightness. The inconsistency of paper brightness may therefore influence conclusions reached in authenticating documents. Reams of multipurpose paper, from 21 manufacturers, were examined. When assessing the individual pages of each package with an ultraviolet light, approximately 30% of the reams revealed differences in paper brightness. A study of the paper-manufacturing process was conducted to determine where variations originate. It is concluded that brightness differences occur when one incompatible roll of paper is mistakenly placed with others used for one production run. It was also determined that brightness variations (when present) are patterned throughout individual reams. When the authenticity of a document is in question, consideration of these findings is essential to assure an accurate assessment. [ABSTRACT FROM AUTHOR]

Disguised handwriting is problematic for forensic document examiners (FDEs) and attracts higher misleading and inconclusive rates on authorship opinions than does genuine writing (Found B, Rogers D, International Graphonomics Society, 2005). There are currently no published empirical data on FDEs’ expertise in distinguishing between natural and disguised writing behavior. This paper reports on the skill of FDEs for determining the writing process of 140 pairs of natural and disguised writings and compares their results with those of a control group of laypeople. A significant difference was found between the examiner and lay group. FDEs’ expertise is characterized by their conservatism, where FDEs express a higher proportion of inconclusive opinions (23.1% for FDEs compared to 8.4% for the control group). This leads to the FDEs expressing a smaller percentage of misleading responses when calling writings as either naturally written or disguised (4.3% for FDEs compared with 12.2% for the control group). [ABSTRACT FROM AUTHOR]

It has previously been shown that forensic document examiners (FDEs) have expertise in providing opinions about whether questioned signatures are genuine or simulated. This study extends the exploration of FDE expertise by evaluating the performance of eight FDEs and 12 control subjects at identifying signatures as either forgeries or the disguised writing of a specimen provider. Subject eye movements and response times were recorded with a Tobii 1750 eye tracker during the signature evaluations. Using a penalty scoring system, FDEs performed significantly better than control subjects ( t = 2.465, p = 0.024), with one FDE able to correctly call 13 of the 16 test stimuli (and three inconclusive calls). An analysis of eye movement search patterns by the subjects indicated that a very similar search strategy was employed by both groups, suggesting that visual inspection of signatures is mediated by a bottom up search strategy. However, FDEs spent greater than 50% longer to make a decision than the control group. The findings are suggestive that for some stimuli FDEs can discriminate between forgeries and disguises, and that this ability is due to a careful inspection and consideration of multiple features within a signature. [ABSTRACT FROM AUTHOR]

Describes use of high performance liquid chromatography analysis of ballpoint pen inks in determining whether a document was forged by backdating. Difference between absolute dating and relative dating; Use of an electrostatic detection device for the examination of the document's latent elements; Suggestion that it is possible to determine the relative age of entries written by ballpoint pen within a relatively short time scale, if storage and supporting material of the different samples are the same or at least similar.

Disappearing inks have been used in different fields, but it may be abused in forgery and counterfeiting. This research was conducted on the preparation of disappearing inks using different concentrations of thymolphthalein, phenolphthalein, and their mixture. The prepared inks were applied to different types of handwriting papers. It was found that the handwriting stability increased by increasing thymolphthalein, phenolphthalein, or alkali concentration, but in the case of using 4 mL of 1 normal (N) NaOH, the handwriting stability of phenolphthalein and its mixture inks decreased. Deciphering of the faded handwriting was evaluated by different methods; using optical deciphering, the faded handwriting did not respond to the different light sources. All the faded handwriting was visible when treated with alkaline solution. There was no change in the faded handwriting when heated to 100°C; phenolphthalein and mixture inks containing 0.5 mL of 1 N NaOH became red when only Azhar and Xerox papers were heated to 150°C. [ABSTRACT FROM AUTHOR]