http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Debnath Bhattacharyya,Eali Stephen Neal Joshua,N.Thirupathi Rao 한국컴퓨터게임학회 2021 한국컴퓨터게임학회논문지 Vol.34 No.2
In the following years, technology has progressed in so many ways that it has provided the cyber society with a resource that only computers can excel at, such as the art of counterfeit of media, which was before unavailable. Deepfakes are a term used to describe this kind of deception. The majority of well-documented Deep Fakes are produced using Generative Adversarial Network (GAN) Models, which are essentially two distinct Machine Learning Models that perform the roles of attack and defence. These models create and identify deepfakes until they reach a point where the morphing no longer detects the deepfakes anymore. Using this algorithm/model, it is possible to discover and create new media that has a similar demographic to the training set, resulting in the development of the ideal Deep Fake media. Because the alterations are carried out utilising advanced characteristics, they cannot be seen with the human eye. However, it is completely feasible to develop an algorithm that can automatically identify this kind of tampering carried out via the internet. This not only enables us to broaden the scope of our search beyond a single media item, but also beyond a large library of mixed media. The more it learns, the better it becomes as artificial intelligence takes over in full force with automation. In order to create better deep fakes, new models are being developed all the time, making it more difficult to distinguish between genuine and morphing material.
Advanced Defensive Measures to Security Vulnerabilities of VPN Using IPsec
Debnath Bhattacharyya 보안공학연구지원센터 2008 보안공학연구논문지 Vol.5 No.2
Data security plays a crucial role in modern times most business is transacted over the internet and even to wireless devices. This paper presents the vulnerabilities found in VPN using IPsec and suggested a set of Policy as a Defensive measure. Such policy suggested applies to implementations of VPN that are directed through an IPsec concentrator and to all company’s employee, contractors, consultants, temporaries and other workers including all personnel affiliated with the third parties utilizing VPNs to access the company’s network
DFT processing for Image Data Hiding
Debnath Bhattacharyya,Ronnie Caytiles,Yvette Gelogo,Mi-Jeon Yang,Tai-hoon Kim 한국정보기술학회 2011 Proceedings of KIIT Conference Vol.2011 No.5
The discrete Fourier transform (DFT) is a specific kind of discrete transform, used in Fourier analysis. It transforms one function into another, which is called the frequency domain representation, or simply the DFT, of the original function. In this paper a novel technique, Discrete Fourier Transformation based Image Authentication has been proposed to authenticate an image and with its own application one can also transmit secret message or image over the network.
Hiding sensitive information in JPEG
Debnath Bhattacharyya,Ronnie Caytiles,Yvette Gelogo,Minkyu Choi,Tai-hoon Kim 한국정보기술학회 2011 Proceedings of KIIT Conference Vol.2011 No.5
Nowadays, the number data thieves and hackers have increased. There is a need to design a system that enables the internet users to exchange their secret and private data safely across the internet. Steganography is the science of hiding information. Whereas the goal of cryptography is to make data unreadable by a third party, the goal of steganography is to hide the data from a third party. The propose Steganography method hides files in a JPEG image. This paper describes the methods used by the application of this kind of Steganography.
Spatial Features Analysis of Automatically Annotated Images
Debnath Bhattacharyya,Tai-hoon Kim 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.11
In this paper, a new method for spatial features based image retrieval is proposed. These are the features specifying location of an image segment in an image and relative spatial location between two image segments etc. Spatial feature adds extra capability of the system in addition to texture, color and shape based object recognition system. Heuristic and semantic features of the image segments are identified from low level color, texture descriptors and directly stored into the image database and easily retrieved also. Position of image segments in the image is detected and stored in the image database that will be accessed for retrieval process later. Object ontology is used to determine the spatial relation between heuristics. These spatial relations and corresponding concept are identified and stored. Spatial rank between two segments will be calculated and stored along with segment ids. Spatial rank is calculated by a new technique. Proper concepts are associated with image segment based on ontology based spatial relation.
Smart Health Advisory System Using IoT
Debnath Bhattacharyya 사단법인 미래융합기술연구학회 2018 아시아태평양융합연구교류논문지 Vol.4 No.2
The Internet of Things (IoT) gives Associate in nursing temperate and new life to the human services field. It conjointly incorporates a quick advancement of the many fields. However a ton of fundamental necessities are existing for human wellbeing inside the field of Medical. One among the higher approach the specialists are skilled to and rapidly appropriate to utilize the pertinent patient data's and together with the patient case history. Through the net of Things, staggeringly enhances the standard of information and in this way the patient care inside the Medical field. Along these lines, web of Things offers Associate in Nursing real stage to interconnect the every one of the assets. Relate in nursing metaphysics based for the most part computerizing style procedure for good medications and physical wellbeing framework abuse IoT. Semantics and metaphysics components helps the PCs notwithstanding the understanding the indications and restorative assets. In this way, cosmology instrument makes a recovery methodology and reconfigure medicinal assets steady with patient's particular necessities apace and more than once.
Image Retrieval Process Based on Relevance Feedback and Ontology Using Decision Tree
Debnath Bhattacharyya,Dipankar Hazra,Tai-hoon Kim 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.10
In this paper, another strategy for immediate features based image recovery is proposed. Image database is developed with low level texture features got from Gray Level Co- Occurrence Matrix (GLCM) and measurable techniques for Tamura. Semantic level inquiries from the user mapped to the low level peculiarities at recovery time to recover the required images. Images with more than one moderate features can be recovered by utilizing intersection of images recovered by each of the queried feature. Artificial Neural Network (ANN) is utilized as a part of the following steps in the wake of accepting user inputs. In spite of the fact that semantics are utilized as search key as a part of the beginning steps, low level features are utilized as a part of the ANN based searching in later steps. Back propagation Algorithm is utilized as a part of learning step. This ANN based relevance feedback technique enhances accuracy of immediate feature based image retrieval method. Decision tree (DT) can likewise be connected in relevance feedback stage. Decision tree is framed in training stage and images will be tested by of the decision tree. Relation storing ontology related information is utilized as a part of every phase of retrieval procedure to evacuate ambiguities identified with synonyms and hypernym-homonym sets.