An Active Deception Defense Model Based on Address Mutation and Fingerprint Camouflage

The static and predictable characteristics of cyber systems give attackers an asymmetric advantage in gathering useful information and launching attacks.To reverse this asymmetric advantage,a new defense idea,called Moving Target Defense(MTD),has been proposed to provide additional selectable measures to complement traditional defense.However,MTD is unable to defeat the sophisticated attacker with fingerprint tracking ability.To overcome this limitation,we go one step beyond and show that the combination of MTD and Deception-based Cyber Defense(DCD)can achieve higher performance than either of them.In particular,we first introduce and formalize a novel attacker model named Scan and Foothold Attack(SFA)based on cyber kill chain.Afterwards,we develop probabilistic models for SFA defenses to provide a deeper analysis of the theoretical effect under different defense strategies.These models quantify attack success probability and the probability that the attacker will be deceived under various conditions,such as the size of address space,and the number of hosts,attack analysis time.Finally,the experimental results show that the actual defense effect of each strategy almost perfectly follows its probabilistic model.Also,the defense strategy of combining address mutation and fingerprint camouflage can achieve a better defense effect than the single address mutation.

Assessing target optical camouflage effects using brain functional networks:A feasibility study

Brain functional networks model the brain's ability to exchange information across different regions,aiding in the understanding of the cognitive process of human visual attention during target searching,thereby contributing to the advancement of camouflage evaluation.In this study,images with various camouflage effects were presented to observers to generate electroencephalography(EEG)signals,which were then used to construct a brain functional network.The topological parameters of the network were subsequently extracted and input into a machine learning model for training.The results indicate that most of the classifiers achieved accuracy rates exceeding 70%.Specifically,the Logistic algorithm achieved an accuracy of 81.67%.Therefore,it is possible to predict target camouflage effectiveness with high accuracy without the need to calculate discovery probability.The proposed method fully considers the aspects of human visual and cognitive processes,overcomes the subjectivity of human interpretation,and achieves stable and reliable accuracy.

Towards complex scenes: A deep learning-based camouflaged people detection method for snapshot multispectral images

Camouflaged people are extremely expert in actively concealing themselves by effectively utilizing cover and the surrounding environment. Despite advancements in optical detection capabilities through imaging systems, including spectral, polarization, and infrared technologies, there is still a lack of effective real-time method for accurately detecting small-size and high-efficient camouflaged people in complex real-world scenes. Here, this study proposes a snapshot multispectral image-based camouflaged detection model, multispectral YOLO(MS-YOLO), which utilizes the SPD-Conv and Sim AM modules to effectively represent targets and suppress background interference by exploiting the spatial-spectral target information. Besides, the study constructs the first real-shot multispectral camouflaged people dataset(MSCPD), which encompasses diverse scenes, target scales, and attitudes. To minimize information redundancy, MS-YOLO selects an optimal subset of 12 bands with strong feature representation and minimal inter-band correlation as input. Through experiments on the MSCPD, MS-YOLO achieves a mean Average Precision of 94.31% and real-time detection at 65 frames per second, which confirms the effectiveness and efficiency of our method in detecting camouflaged people in various typical desert and forest scenes. Our approach offers valuable support to improve the perception capabilities of unmanned aerial vehicles in detecting enemy forces and rescuing personnel in battlefield.

What If I Told You Camouflage is a Myth? Animal Coloration is Mainly A-biotic and not Biotic (Camouflage)

In the present article,the author posits that the perception that animals apparently display a strategy of avoiding detection by means of camouflage—i.e.,by disguising themselves in the natural colours of their environment—is not the actual case in nature but,rather,merely anecdotal.Animal coloration is mainly a-biotic(eco-physiological)and not biotic(camouflage).The contention regarding the absence of the phenomenon of camouflage among animals as a common evolutionary response is based on three arguments:(1)that reflecting the natural colours of the environment is linked to ecophysiology;(2)that predator and prey constitute“an evolutionary pair”and,accordingly,they know how to identify one another(in order to survive they employ different strategies,of which camouflage is not one of them);and (3)that the approach of relating animal camouflage to reflecting the colours of the environment is an anthropocentric one.Rather than the accepted biotic-ethological approach(colour camouflage),the present article suggests the recognition of a-biotic and eco-physiological conditions as a distinct research field,whose title“Reflection of environmental colours by animals”,along with this article,calls for eco-physiologists to demonstrate that this approach indeed offers a special contribution to the understanding of colouration in animals.

Dual Attribute Adversarial Camouflage toward camouflaged object detection

The object detectors can precisely detect the camouflaged object beyond human perception.The investigations reveal that the CNNs-based(Convolution Neural Networks)detectors are vulnerable to adversarial attacks.Some works can fool detectors by crafting the adversarial camouflage attached to the object,leading to wrong prediction.It is hard for military operations to utilize the existing adversarial camouflage due to its conspicuous appearance.Motivated by this,this paper proposes the Dual Attribute Adversarial Camouflage(DAAC)for evading the detection by both detectors and humans.Generating DAAC includes two steps:(1)Extracting features from a specific type of scene to generate individual soldier digital camouflage;(2)Attaching the adversarial patch with scene features constraint to the individual soldier digital camouflage to generate the adversarial attribute of DAAC.The visual effects of the individual soldier digital camouflage and the adversarial patch will be improved after integrating with the scene features.Experiment results show that objects camouflaged by DAAC are well integrated with background and achieve visual concealment while remaining effective in fooling object detectors,thus evading the detections by both detectors and humans in the digital domain.This work can serve as the reference for crafting the adversarial camouflage in the physical world.

A small-spot deformation camouflage design algorithm based on background texture matching

In order to solve the problem of poor fusion between the spots of deformation camouflage and the background,a small-spot deformation camouflage design algorithm based on background texture matching is proposed in this research.The combination of spots and textures improved the fusion of the spot pattern and the background.An adversarial autoencoder convolutional network was designed to extract background texture features.The image adversarial loss was added and the reconstruction loss was improved to improve the clarity of the generated texture pattern and the generalization ability of the model.The digital camouflage was formed by obtaining the mean value of the square area and replacing the main color.At the same time,the spots in the square area with a side length of 2 s were subjected to simple linear iterative clustering to form irregular small-spot camouflage.A dataset with a scale of 1050 was established in the experiment.The training results of three different loss functions were investigated.The results showed that the proposed loss function could enhance the generalization of the model and improve the quality of the generated texture image.A variety of digital camouflages with main colors and irregular small-spot camouflage were generated,and their efficiency was tested.On the one hand,intuitive evaluation was given by personnel observing the camouflage pattern embedded in the background and its contour map calculated by the canny operator.On the other hand,objective comparison result was formed by calculating the 4 evaluation indexes between the camouflage pattern and the background.Both results showed that the generated pattern had a high degree of fusion with the background.This model could balance the relationship between the spot size,the number of main colors and the actual effect according to actual needs.

A camouflage target detection method based on local minimum difference constraints

To address the problems of missing inside and incomplete edge contours in camouflaged target detection results,we propose a camouflaged moving target detection algorithm based on local minimum difference constraints(LMDC).The algorithm first uses the mean to optimize the initial background model,removes the stable background region by global comparison,and extracts the edge point set in the potential target region so that each boundary point(seed)grows along the center of the target.Finally,we define the minor difference constraints term,combine the seed path and the target space consistency,and calculate the attributes of each pixel in the potential target area to realize camouflaged moving target detection.The algorithm of this paper is verified based on a public data sofa video and test videos and compared with the five classic algorithms.The experimental results show that the proposed algorithm yields good results based on integrity,accuracy,and a number of objective evaluation indexes,and its overall performance is better than that of the compared algorithms.

RBC Membrane Camouflaged Semiconducting Polymer Nanoparticles for Near-Infrared Photoacoustic Imaging and Photothermal Therapy

Semiconducting conjugated polymer nanoparticles(SPNs)represent an emerging class of phototheranostic materi-als with great promise for cancer treatment.In this report,low-bandgap electron donoracceptor(DA)-conjugated SPNs with sur-face cloaked by red blood cell membrane(RBCM)are developed for highly e ective photoacoustic imaging and photothermal therapy.The resulting RBCM-coated SPN(SPN@RBCM)displays remarkable near-infrared light absorption and good photosta-bility,as well as high photothermal conver-sion e ciency for photoacoustic imaging and photothermal therapy.Particularly,due to the small size(<5 nm),SPN@RBCM has the advantages of deep tumor penetration and rapid clearance from the body with no appreciable toxicity.The RBCM endows the SPNs with prolonged systematic circulation time,less reticuloendothelial system uptake and reduced immune-recognition,hence improving tumor accumulation after intravenous injection,which provides strong photoacoustic signals and exerts excellent photothermal therapeutic e ects.Thus,this work provides a valuable paradigm for safe and highly e cient tumor pho-toacoustic imaging and photothermal therapy for further clinical translation.

Research on extraction and reproduction of deformation camouflage spot based on generative adversarial network model

The method of describing deformation camouflage spots based on feature space has some shortcomings,such as inaccurate description and difficult reproduction.Depending on the strong fitting ability of the generative adversarial network model,the distribution of deformation camouflage spot pattern can be directly fitted,thus simplifying the process of spot extraction and reproduction.The requirements of background spot extraction are analyzed theoretically.The calculation formula of limiting the range of image spot pixels is given and two kinds of spot data sets,forestland and snowfield,are established.Spot feature is decomposed into shape,size and color features,and a GAN(Generative Adversarial Network)framework is established.The effects of different loss functions on network training results are analyzed in the experiment.In the meantime,when the input dimension of generator network is 128,the balance between sample diversity and quality can be achieved.The effects of sample generation are investigated in two aspects.Subjectively,the probability of the generated spots being distinguished in the background is counted,and the results are all less than 20% and mostly close to zero.Objectively,the features of the spot shape are calculated and the independent sample T-test is applied to verify that the features are from the same distribution,and all the P-Values are much higher than 0.05.Both subjective and objective methods prove that the spots generated by this method are similar to the background spots.The proposed method can directly generate the desired camouflage pattern spots,which provides a new technical method for the deformation camouflage pattern design and camouflage effect evaluation.

MF-CFI:A fused evaluation index for camouflage patterns based on human visual perception

The evaluation index of camouflage patterns is important in the field of military application.It is the goal that researchers have always pursued to make the computable evaluation indicators more in line with the human visual mechanism.In order to make the evaluation method more computationally intelligent,a Multi-Feature Camouflage Fused Index(MF-CFI)is proposed based on the comparison of grayscale,color and texture features between the target and the background.In order to verify the effectiveness of the proposed index,eye movement experiments are conducted to compare the proposed index with existing indexes including Universal Image Quality Index(UIQI),Camouflage Similarity Index(CSI)and Structural Similarity(SSIM).Twenty-four different simulated targets are designed in a grassland background,28 observers participate in the experiment and record the eye movement data during the observation process.The results show that the highest Pearson correlation coefficient is observed between MF-CFI and the eye movement data,both in the designed digital camouflage patterns and largespot camouflage patterns.Since MF-CFI is more in line with the detection law of camouflage targets in human visual perception,the proposed index can be used for the comparison and parameter optimization of camouflage design algorithms.

Predator perception of detritus and eggsac decorations spun by orb-web spiders Cyclosa octotuberculata:Do they function to camouflage the spiders?

Camouflage is one of the most widespread and powerful strategies that animals use to make detection/recognition more difficult. Many orb-web spiders of the genus Cyclosa add prey remains, plant debris, moults, and/or eggsacs to their webs called web decorations. Web decorations resembling spider body colour pattern have been considered to camouflage the spider from predators. While this camouflage is obvious from a human＇s perspective, it has rarely been investigated from a predator＇s perspective. In this study, we tested the visibility of web decorations by calculating chromatic and achromatic contrasts of detritus and eggsae decorations built by Cyclosa octotubereulata, against four different backgrounds viewed by both bird （e.g., blue tits） and hymenopteran （e.g. wasps） predators. We showed that both juvenile and adult spiders on webs with detritus or egg-sac deco- rations were undetectable by both hymenopteran and bird predators over short and long distances. Our results thus suggest that decorating webs with detritus or eggsacs by C octotuberculata may camouflage the spiders from both hymenopteran and bird predators in their common habitats [Current Zoology 56 （3）： 379-387, 2010].

Study on the Camouflage-Protective and Dyeing Properties of Natural Dye Indigo

There are two major camouflage protections in modern military tactics:UV-protection and near infrared camouflage.However,not all natural and composite dyestuffs provide the mentioned properties.In this study,the cotton fabric was dyed with natural indigo and the natural indigo dyeing process was optimized.Green leaves were chosen as the simulating object,and the camouflage properties of the dyed cotton fabric were evaluated.It was observed that the dyed cotton fabric had good UV-protection and near-infrared camouflage properties.The UV-protection effect was strongly dependent on the absorption characteristics of natural indigo for UV radiation.The near infrared camouflage effect was mainly dependent on the reflection spectrum characteristics of natural indigo in the near infrared waveband.

Design of infrared camouflage cloak for underground silos

The temperature difference between the exposed surface of an underground silo and the surrounding soil surface is significant,which means a silo can be easily found by infrared detection.We designed an infrared camouflage cloak consisting of an imitative layer and an insulation layer for the silos.The imitative layer is used to imitate the thermal response of the soil to the surrounding environment.The insulation layer is used to weaken the impact of the internal temperature field of the silo on the lower boundary of the imitative layer.A silo model including surrounding soil and a soil model without silo were established,and the influences of the material and thickness of each layer on the infrared camouflage effect were analyzed.The results show that when using a silicone rubber containing alumina powder with a volume fraction of 3.18% as the imitative material,its thermal inertia is in consistent with that of the soil.Meanwhile,it was found that the thickness of the imitative layer doesn't need to be greater than its thermal penetration depth to achieve the infrared camouflage,and the absence of the insulation layer will cause hot spots on the silo surface in winter to weaken the camouflage effect.The optimized thicknesses of the imitative layer and the insulation layer are 22 cm and 4 cm re spectively.The simulations indicate that with the application of the cloak,the maximum value of the absolute values of the temperature differences between the average temperatures of the silo surface and the surrounding soil surface temperatures drops from 1,59℃ to 0.31℃ in summer and from 1.92℃ to 0.21℃ in winter.This designed cloak can achieve an all-weather and full-time passive infrared camouflage.

Comparison of skeletal, dental and soft tissue changes in young adults with Class II malocclusion, treated either by camouflage, fixed functional appliance or orthognathic surgery—A prospective study on Indian subjects

Introduction: Borderline Class II malocclusion due to deficient mandible can be treated either by orthodontic camouflage, fixed functional appliances or by orthodontics followed by surgical mandibular advancement. Methodology: A prospective study was designed on young adults with Class II malocclusion on account of a deficient mandible. A total of 45 subjects were divided into three groups of 15 individuals each. The patients were treated either by camouflage, fixed functional appliances or by orthognathic surgery. Pre and post treatment cephalograms were used to assess the skeletal, dental and soft tissue changes. Pre and post treatment profile photographs were assessed on a Visual Analogue Scale (VAS) by orthodontists, oral surgeons and laypersons. Results: Each group achieved a reduction in facial convexity, but the results obtained from the surgical group were more pronounced than the camouflage and the fixed functional group. Conclusion: The reduction in convexity in the camouflage group was by retracting the upper anteriors, which increases the nasolabial angle. In the fixed functional appliance a combination of skeletal and dentoalveolar changes can be observed. However the most appropriate reduction in profile convexity can be obtained by combined orthodontic and surgical treatment of malocclusion.

Orthodontic camouflage versus orthognathic surgery: A comparative analysis of long-term stability and satisfaction in moderate skeletal Class III

Objective: The purpose of this study was to compare long-term stability and satisfaction between orthodontic camouflage and orthognathic surgery in treatment of moderate skeletal Class III adults. Materials and Methods: A total of 25 adults females who had been treated with orthodontic camouflage for Class III malocclusions were recalled at least 3 years post-treatment to evaluate stability and satisfaction with treatment outcomes. The data were compared with similar data for long-term outcomes in 21 patients with the same Class III problems who had bimaxillary surgical correction. Results: In the camouflage patients, small mean changes in skeletal landmark positions occurred over the long term, although the changes were generally much smaller than in the surgery patients. Dental changes in the surgery group were more severe than those in the camouflage group. The camouflage patients reported fewer functional or temporomandibular joint problems than did the surgery patients. Both groups reported similar levels of overall satisfaction with treatment. Conclusion: The results suggest that both camouflage and surgical treatment in moderate skeletal Class III adults can achieve satisfactory outcomes and provide long-term stability. If patients do not readily accept surgery because of potential surgical complications or financial difficulties, camouflage treatment may be an effective alternative treatment.

A platform for initial testing of multiple camouflage patterns

The human visual system is still an important factor in military warfare;military personnel receive training on effective search strategies,and camouflage that can effectively conceal objects and personnel is a key component of a successful integrated survivability strategy.Previous methods of camouflage assessment have,amongst others,used psychophysics to generate distinctiveness metrics.However,the population from which the human observers are drawn is often not well defined,or necessarily appropriate.In this experiment we designed a new platform for testing multiple patterns based on a camouflaged object detection task,and investigate whether trained military observers perform better than civilians.We use a two-alternative forced choice paradigm,with participants searching images of woodland for a replica military helmet displaying Olive Green,Multi Terrain Pattern,US Marine Pattern or,as a conspicuous control,UN Peacekeeper Blue.Our data show that there is no difference in detection performance between the two observer groups but that there are clear differences in the effectiveness of the different helmet colour patterns in a temperate woodland environment.We conclude that when tasks involve very short stimulus presentation times,task-specific training has little effect on the success of target detection and thus this paradigm is particularly suitable for robust estimates of camouflage efficacy.

Improvement of VIS and IR camouflage properties by impregnating cotton fabric with PVB/IF-WS_(2)

In order to examine the possibility to improve its camouflage properties standard cotton fabric with camouflage print was impregnated with poly(vinyl butyral),PVB and fullerene-like nanoparticles of tungsten disulfide,PVB/IF-WS_(2).FTIR analysis excluded any possible chemical interaction of IF-WS_(2) with PVB and the fabric.The camouflage behavior of the impregnated fabric has been examined firstly in the VIS part of the spectrum.Diffuse reflection,specular gloss and color coordinates were measured for three different shades(black,brown and dark green).Thermal imaging was applied to examine the camouflage abilities of this impregnation in IR part of the spectrum.The obtained results show that PVB/IF-WS_(2) impregnation system induced enhacement of the materials camouflage properties,i.e.that IF-WS_(2) have a positive effect on spectrophotometric characteristics of the fabric.

Evaluation of infrared camouflage effectiveness via a multi-fractal method

This paper reports an alternative approach to the evaluation of infrared camouflage effectiveness via a multi-fractal method. By calculating multi-fractal spectra of the target region and the background regions in an infrared image, the spectrum shape features and the discrete Frechet distances among these spectra were used to analyze the camouflage effectiveness of the target qualitatively and quantitatively,and the correlation coefficients of the spectra were further used as the index of camouflage effectiveness.It was found that the camouflaged target had better camouflage effectiveness than the target without camouflage in the same one background, and the same one camouflaged target had different camouflage effectiveness in different backgrounds. On the whole, the target matching well with its background had high camouflage effectiveness value. This approach can expand the application of multi-fractal theory in infrared camouflage technology, which should be useful for the research of infrared camouflage materials, the design of camouflage patterns as well as the deployment of military equipment in battlefield.

A Reversible Data Hiding Algorithm Based on Image Camouflage and Bit-Plane Compression

Reversible data hiding in encrypted image(RDHEI)is a widely used technique for privacy protection,which has been developed in many applications that require high confidentiality,authentication and integrity.Proposed RDHEI methods do not allow high embedding rate while ensuring losslessly recover the original image.Moreover,the ciphertext form of encrypted image in RDHEI framework is easy to cause the attention of attackers.This paper proposes a reversible data hiding algorithm based on image camouflage encryption and bit plane compression.A camouflage encryption algorithm is used to transform a secret image into another meaningful target image,which can cover both secret image and encryption behavior based on“plaintext to plaintext”transformation.An edge optimization method based on prediction algorithm is designed to improve the image camouflage encryption quality.The reversible data hiding based bit-plane level compression,which can improve the redundancy of the bit plane by Gray coding,is used to embed watermark in the camouflage image.The experimental results also show the superior performance of the method in terms of embedding capacity and image quality.

Camouflage Therapy for Post-Inflammatory Hyperpigmentation on the Face Caused by Fixed Drug Eruption

Camouflage therapy has been used for permanent contour and pigmentary defects including telangiectasias, vitiligo, lentigines, nevi, atrophic scars and burn scars. The goal of the therapy is to provide new and innovative ways to normalize the appearance of patients with abnormalities. A variety of cosmetic techniques are used to assist these patients in making their irregularities as inconspicuous as possible. Post-inflammatory hyperpigmentation is a frustrating problem afflicting many dermatology patients, particularly on the face. Here we report a case of successful cosmetic camouflage using the theory of complementary colors of light in a patient with post-inflammatory hyperpigmentation of the face caused by fixed drug eruption. Our case report supports the idea that camouflage for patients with post-inflammatory hyperpigmentation on the face caused by fixed drug eruption improves their quality of life and also supports the idea that camouflage should be part of the after care for patients who have received patch testing.