Cover Objects Research Articles

Dual-layer security of image steganography based on IDEA and LSBG algorithm in the cloud environment

The architecture development of cloud computing technology is growing tremendously in recent times, which leads to improvement of scalability, accessibility and cost reduction measures in the IT sectors of all enterprises. In this service, the data storage without reviewing security policies and procedures is a challenging task and probabilities of extracting secret information by an unauthorized intervention are more. However, to prevent the breaches of security in the cloud service, the steganography art plays an essential role in the data communication medium to improve the security measures, and it is an indispensable technique for hiding the secret information into a cover object. This paper describes the implementation of new steganography method with International Data Encryption Standard Algorithm (IDEA) and Least Significant Bit Grouping (LSBG) algorithm for embedding the secret information into an original image and extracting the same. The result shows the improvement of data embedding capacity and reduces the issues related to data security by effective utilization of this new approach, which reveals the remarkable achievement of the combinational execution of steganography and cryptography technique. The IDEA and LSBG have some vital qualities such as data confidentiality, integrity verification, capacity and robustness, which are crucial factors to achieve successful implementation of steganography process in data security system. The effectiveness and properties of the stego image can be evaluated by some specific measures like mean squared error, root mean squared error, peak signal to noise ratio and structural similarity index matrix to analyse the image quality. The results show that the proposed technique outperforms the existing methodologies and resolves the data security problem in data transmission and storage system of cloud computing services.

Shortening the Cover for Fast JPEG Steganography

Recently, the most effective steganographic schemes for JPEG images are based on minimal distortion model with Syndrome-Trellis Codes (STCs) as the coding method. However, the execution time of STCs will be severely long for message embedding to the cover object of large size, which cannot meet the demand for real-time communication in a real-world application. According to the time complexity $O(2^{h}n)$ , it is suggested in the STCs to accelerate the embedding process by decreasing the constraint height $h$ . However, smaller $h$ corresponds to lower steganographic security. In this paper, we investigate the possibility of shortening the cover (reducing the length $n$ ) for speeding up the execution of STCs without weakening the steganographic security. After introducing some properties of cover selection with proofs, we propose several algorithms designed for JPEG images to construct a preferable shortened cover containing DCT coefficients of smaller costs as much as possible. The experimental results display the superiority of the proposed algorithm on the speed profit and the security when compared with the method of decreasing $h$ . With confidence, a JPEG image of arbitrary quality factor can be safely shortened to 1/4 of the original, and correspondingly the execution of STCs can be four times faster.

Superpixel based land cover classification of VHR satellite image combining multi-scale CNN and scale parameter estimation

Traditional classification methods, which use low-level features, have failed to gain satisfactory classification results of very high spatial resolution (VHR) remote sensing images. Even though per-pixel classification method based on convolutional neural network (CNN) (Per-pixel CNN) achieved higher accuracy with the help of high-level features, this method still has limitations. Per-superpixel classification method based on CNN (Per-superpixel CNN) overcomes the limitations of per-pixel CNN, however, there are still some scale related issues in per-superpixel CNN needed to be explored and addressed. Firstly, in order to avoid the misclassification of complex land cover objects caused by scale effect, the per-superpixel classification method combining multi-scale CNN (Per-superpixel MCNN) is proposed. Secondly, this paper analyzes how scale parameter of CNN impacts the classification accuracy and involves spatial statistics to pre-estimate scale parameter in per-superpixel CNN. This paper takes two VHR remote sensing images as experimental data, and employs two superpixel segmentation algorithms to classify urban and suburban land covers. The experimental results show that per-superpixel MCNN can effectively avoid misclassification in complex urban area compared with per-superpixel classification method combining single-scale CNN (Per-superpixel SCNN). Series of classification results also show that using the pre-estimated scale parameter can guarantee high classification accuracy, thus arbitrary nature of scale estimation can be avoided to some extent. Additionally, through discussion of the influence of accuracy evaluation method in CNN classification, it is stressed that random selection of ground truth validation points from study area is recommended and more responsibly other than using part of a reference dataset.

Use of data loggers to investigate temperature trends above and below cover objects used by plethodontid salamanders


 
 
 
 Amphibians utilize microhabitats to find refugia that will keep them functioning properly by regulating thermoregulatory behavior and for respiration. Microclimates of cover objects and the influence they may have in the selection of refugia by plethodontid salamanders are inherently difficult to study over long periods of time. Herein we provide a case study in which we used U23-003 HOBO Pro v2 2X Temperature Data Loggers to investigate temperature trends under and above cover objects selected by plethodontid salamanders in the field. Overall, data loggers were user-friendly for setup, deploymentt, and data offload and provided abundant data.
 
 
 

Small Manhole Cover Detection in Remote Sensing Imagery with Deep Convolutional Neural Networks

With the development of remote sensing technology and the advent of high-resolution images, obtaining data has become increasingly convenient. However, the acquisition of small manhole cover information still has shortcomings including low efficiency of manual surveying and high leakage rate. Recently, deep learning models, especially deep convolutional neural networks (DCNNs), have proven to be effective at object detection. However, several challenges limit the applications of DCNN in manhole cover object detection using remote sensing imagery: (1) Manhole cover objects often appear at different scales in remotely sensed images and DCNNs’ fixed receptive field cannot match the scale variability of such objects; (2) Manhole cover objects in large-scale remotely-sensed images are relatively small in size and densely packed, while DCNNs have poor localization performance when applied to such objects. To address these problems, we propose an effective method for detecting manhole cover objects in remotely-sensed images. First, we redesign the feature extractor by adopting the visual geometry group (VGG), which can increase the variety of receptive field size. Then, detection is performed using two sub-networks: a multi-scale output network (MON) for manhole cover object-like edge generation from several intermediate layers whose receptive fields match different object scales and a multi-level convolution matching network (M-CMN) for object detection based on fused feature maps, which combines several feature maps that enable small and densely packed manhole cover objects to produce a stronger response. The results show that our method is more accurate than existing methods at detecting manhole covers in remotely-sensed images.

Quaternion Security Using Modifying Vernam Cipher With Image Steganography

The Internet is the essential wellspring of data in the present life where it offers the trade of data to the clients.The exchange of such data prompts an incredible security danger. Cryptography and steganography are two issues in security systems. Cryptography jumbles the message to be incomprehensible While Steganography shroud the message To be invisible. Therefore, Encryption any private data before concealing in the cover object will provide twofold security. This paper presents a technique for disguise message with four levels of security where the message first encrypt using modifying vernam cipher, in which the initial key originate automatically from random pixel of camouflage cover and alter continuously along message length then embedded cipher message in grayscale cover image, after that encrypt this cover using modifying vernam cipher also then embedded it in RGB color cover image. The simulation consequence illustrates that the scheme provides better protection.

Ecological and zoological study of endemic Sri Lankan keelback (Balanophis ceylonensis): with implications for its conservations

The endemic Sri Lankan keelback (Balanophis ceylonensis) is a snake largely restricted to rainforests of the island. Based on an 11-years field survey covering 83 field sites and rescued specimens, we present an autecology of B. ceylonensis. We recorded 32 individuals of B. ceylonensis at 25 field sites. All snakes were found in 10 – 1000 m altitude range within or in close proximity of rainforests. This snake associated with canopy-shaded forest floor with sufficient leaf litter and a numerous other natural cover objects, and were active mostly during dusk. Our study indicated that B. ceylonensis is a rare species with a patchy distribution within the wet zone of southwestern Sri Lanka, and can be considered a rainforest specialist. The reproductive season spanned from November to February as evident by observations on copulation. The snake laid eggs in clutches of 3 – 4 underneath woody debris or inside the forest floor. Given its rarity, patchy distribution, and estimated extend of occurrence and area of occupancy, and continuing degradation of rainforests, we assessed the conservation status of B. ceylonensis as Endangered.

Multiscale Optimized Segmentation of Urban Green Cover in High Resolution Remote Sensing Image

The urban green cover in high-spatial resolution (HR) remote sensing images have obvious multiscale characteristics, it is thus not possible to properly segment all features using a single segmentation scale because over-segmentation or under-segmentation often occurs. In this study, an unsupervised cross-scale optimization method specifically for urban green cover segmentation is proposed. A global optimal segmentation is first selected from multiscale segmentation results by using an optimization indicator. The regions in the global optimal segmentation are then isolated into under- and fine-segmentation parts. The under-segmentation regions are further locally refined by using the same indicator as that in global optimization. Finally, the fine-segmentation part and the refined under-segmentation part are combined to obtain the final cross-scale optimized result. The green cover objects can be segmented at their specific optimal segmentation scales in the optimized segmentation result to reduce both under- and over-segmentation errors. Experimental results on two test HR datasets verify the effectiveness of the proposed method.

Hiding Data in Color Image Using Least Significant Bits of Blue Sector

Concealing the existence of secret hidden message inside a cover object is known as steganography, which is a powerful technique. We can provide a secret communication between sender and receiver using Steganography. In this paper, the main goal is for hiding secret message into the pixels using Least Significant Bit (LSB) of blue sector of the cover image. Therefore, the objective is by mapping technique presenting a model for hiding text in an image. In the model for proposing the secret message, convert text to binary also the covering (image) is divided into its three original colors, Red, Green and Blue (RGB) , use the Blue sector convert it to binary, hide two bits from the message in two bits of the least significant bits of blue sector of the image.

Information hiding with adaptive steganography based on novel fuzzy edge identification

The evolution in communication techniques has created wide threats for crucial information transfer through a communication channel. Covert communication with steganography is a skill of concealing secret information within cover object and hence shields the data theft over rapidly growing network. Recently, diverse steganography techniques using edge identification have been proposed in literature. Numerous methods however utilize certain pixels in the cover image for inserting edge information, resulting in significant deformation. The conventional edge detection method limits the deployment of edge detection in steganography as concealing the information would introduce some variations to the cover image. Hence inserting data in pixel areas recognized by existing conventional edge detection techniques like canny cannot ensure the recognition of the exact edge locations for the cover and stego images. In this paper, an Adaptive steganography method based on novel fuzzy edge identification is proposed. The method proposed is proficient of estimating the precise edge areas of a cover image and also ensures the exact edge location after embedding the secret message. Experimental results reveal that the technique has attained good imperceptibility compared to the Hayat Al-Dmour and Ahmed Al-Ani Edge XOR method in spatial domain.

Interspecific interactions are conditional on temperature in an Appalachian stream salamander community.

Differences in the rates of responses to climate change have the potential to disrupt well-established ecological interactions among species. In semi-aquatic communities, competitive asymmetry based on body size currently maintains competitive exclusion and coexistence via interference competition. Elevated temperatures are predicted to have the strongest negative effects on large species and aquatic species. Our objectives were to evaluate the interaction between the effects of elevated temperatures and competitor identity on growth and habitat selection behavior of semi-aquatic salamanders in stream mesocosms. We observed interference competition between small and large species. Elevated temperatures had a negative effect on the larger species and a neutral effect on the smaller species. At elevated temperatures, the strength of interference competition declined, and the smaller species co-occupied the same aquatic cover objects as the larger species more frequently. Disruptions in competitive interactions in this community may affect habitat use patterns and decrease selection for character displacement among species. Determining how biotic interactions change along abiotic gradients is necessary to predict the future long-term stability of current communities.

Novel Text Steganography Using Natural Language Processing and Part-of-Speech Tagging

The practice of transmitting secret data by using cover data is called steganography. At present, several versatile steganographic methods are available using different digital objects (e.g. image, audio, video, text, etc.) as cover to hide data. Accordingly, many methods of steganalysis have been explored to reveal statistical anomalies in stego object, through which presence of secret data can be detected. However, applications of steganography and steganalysis techniques are challenging when cover object is text, as text does not have any redundant bits. In this paper, an innovative text steganography approach is proposed which uses natural language text as cover as well as secret message. The concept of shared key is also used here, that holds the count of each parts-of-speech of secret message. This key is RSA encrypted and shared with communicative parties. Stego created by this method also is in natural language text. This method is successful as the stego keeps the original meaning of the text in gross which makes it robust and undetectable. It shows good result in capacity ratio; also, the similarity index has been assessed by Jaro–Winkler distance and Generalized Levenshtein distance.

Understandable Steganography

For hiding information in a digitalized object Steganography is an important technique. It is a special kind of scientific technique which involves the secret information communication inside suitable cover objects of multimedia like image files, audio or videos. The embedded data and its existence are hidden with the help of Steganography. It is a method of hiding data which has enormously improved the security level of confidential data with the help of special hiding mechanism and is considered as remarkable achievement in the computational power. The main aims of Steganography are; capacity of concealed data along with its robustness, lack of detection etc. These are some of the additional features which make it distinguishing from other older techniques like watermarking as well as cryptography. In this research paper, we have surveyed Steganography of digital images and cover the basic and key concepts. In spatial representation the development of image Steganographic methodology in the format of JPEG, along with that we will also debate on the modern developments as far as Steganography is concerned.For increasing Steganographic security, specifically used approaches are shortlisted and the developments made after investigations are also presented in this paper.

An Implementation of Text and Color Image Steganography Technique Using Cryptographic Algorithm

The craft of data stowing away has gotten much consideration in the ongoing years as security of data has turned into a major worry in this web time. As sharing of delicate data by means of a typical correspondence channel have become inevitable, Steganography techniques aimed at secretly hiding data in a multimedia carrier such as text, audio, image or video, without raising any suspicion of alteration to its contents. The original carrier is referred to as the cover object. In this paper, we proposed a mechanism of end user data security by means of image steganography technique using ECDH (Elliptic Curve Diffie–Hellman) algorithm for improving image quality while we hide data in image. Our proposed approach is simplified yet efficient algorithm that can be implemented for end user application that strictly enforces the data integrity over the communication channel. The performance of the proposed approach is measured in terms of time, memory, MSE and PSNR which was better improved from the previous approach in the similar parameters.

Hiding text in gray image using mapping technique

In order to hide the significant and secret message inside a cover object, Steganography is considered as one of the most used technique because of its strength. This paper presents a new steganography technique that it is difficult to discover or break by a third party. The ASCII Mapping Technique (AMT) is used to create an encoded table by mapping the text message and matching some bits with that of the cover image. The system saves the character parts matching and the location of which part of the pixels. Then change the related flag from zero to one the for matched locations so that they cannot be used again to strength the technique and make it more secure. The proposed technique was tested and showed low computational cost with effective performance to be used for multi-purpose applications.

Red imported fire ants (Solenopsis invicta) and seasonality influence community refuge use

Refuges are fundamental to animal ecology as refuge availability affects many levels of biological organization—from the behavior and physiology of individuals to the interspecific dynamics of a community. Although frequently studied in the context of predator–prey interactions, refuges may also mediate interspecific competition between native and invasive taxa given the role of refuges as a valuable resource. Because interspecific interactions (e.g., competition and predation) can be modulated by temporal and biotic (e.g., trophic level) factors, we used a manipulative approach to investigate community-wide refuge-use patterns in the context of two important ecological factors: invasive species and seasonality. We surveyed refuge (artificial cover object) use of ants and vertebrates in a forest community for 2 years, and we systematically suppressed an established invasive species (red imported fire ant, Solenopsis invicta) to examine its impact on community refuge use. Native Camponotus ants appeared to co-exist and share refuges with S. invicta, but we found evidence for a negative effect of S. invicta on vertebrate refuge use that was also influenced by season. Vertebrates were more abundant under refuges undergoing suppression of S. invicta, and they were less abundant under refuges during the fall (the season characterized by the highest occupancy of refuges by S. invicta). Thus, researchers must continue to examine the entire community and to incorporate the effects of season when assessing the impact of invasive species (e.g., at our site, a survey conducted only in the summer or only on native ants would have indicated a negligible effect of S. invicta on community refuge use).

Approach to the selection of the best cover image for information embedding in JPEG images based on the principles of the optimality

In the presented research, the decision support in order to increase the efficiency of providing confidentiality of information with the use of methods of digital steganography is considered. These methods allow one to secretly transmit confidential information using various digital objects. When hiding information with the use of steganography, digital images are often used, among which compressed JPEG images are of the greatest popularity. The efficiency of information embedding into JPEG images substantially depends on properties of the source image used as a container. Therefore, in the considered field of information security, the relevant problem is to provide the decision support about the choice of digital cover objects that are the most suitable for the transmitting of the given amount of information. In the given paper, we provide an approach to the support of the selection of the best cover image out of a number of JPEG images, based on the application of the principles of optimality. The implementation of the given approach with the reference to the popular method of embedding (JSteg) is given. The results of experiments show that the considered approach allows us to select such an image from a set of cover images, for which the best visual quality of embedding is provided.

Comparison of Relative Abundance and Microhabitat of Desmognathus organi (Northern Pygmy Salamander) and Desmognathus wrighti (Southern Pygmy Salamander) in North Carolina

There are currently no quantitative studies describing the habitat of Desmognathus organi (Northern Pygmy Salamander) and D. wrighti (Southern Pygmy Salamander). We investigated the relative abundance and microhabitat selection of Northern Pygmy Salamander and Southern Pygmy Salamander in 3 forest types of different elevations across the mountains of North Carolina during the summer of 2015. We conducted 2-h time-constrained searches at 4 sites in Picea rubens (Red Spruce) —Abies fraseri (Fraser Fir) forests, northern hardwood forests, and mountain cove forests for each species. We quantified microhabitat characteristics at each pygmy salamander location and at a corresponding random location 2–30 m away. We captured a total of 98 pygmy salamanders (D. organi = 41, D. wrighti = 57): 52 in spruce—fir forests, 26 in northern hardwood forests, and 20 in cove forests, and recorded 655 other salamanders representing 15 species. Relative abundance of pygmy salamanders was greater in spruce—fir forests than in cove forests, but was not significantly different between spruce—fir and northern hardwood forests. Microhabitat did not differ between Northern Pygmy Salamander and Southern Pygmy Salamander for any of the variables examined, except for soil moisture, which was greater at Northern Pygmy Salamander locations and may have been a spurious result. We observed pygmy salamanders almost exclusively beneath wood cover-objects, and size of cover objects did not differ from the size available in the surrounding environments. Total area of small-sized down woody debris (DWD) and total area of large-sized DWD were the only variables associated with the presence of pygmy salamanders, suggesting that pygmy salamanders avoid predation and interspecific competition by selecting sites that minimize encounters with larger salamanders.

A Review on Various Approaches of Image Steganography and Data Security

Images are used as the popular cover objects for steganography. A message is embedded in a digital image through an embedding algorithm, using the secret key. In this process image is divided into different regions for the detection of least significant bits available in different images. The no. of bits that can be utilized for image enhancement depend upon the pixel intensity the low intensity pixel utilizes less no. of bits and pixel having a high intensity utilized maximum bits in the process of hiding the image. The issue in this is security for prevention image from stegnalysis attack and the secret data is available in such a manner as it transmitted.in this paper a review on various approaches have been done that has been used for embedding of secret information behind the cover object.

A secure image steganography algorithm based on least significant bit and integer wavelet transform

The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio, or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits (LSBs) of the approximation coefficients of the integer wavelet transform (IWT) of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio (PSNR) and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error (MSE) and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation (NCC). The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. Furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.