The rapid advancement of digital media technologies has given rise to DeepFake videos, synthetic ... more The rapid advancement of digital media technologies has given rise to DeepFake videos, synthetic content generated using deep learning algorithms that can convincingly mimic real individuals' appearances and actions. This presents a significant challenge in maintaining digital content integrity, as DeepFakes pose threats to information veracity, security, and public trust. Addressing this challenge necessitates robust detection methods that not only accurately identify DeepFakes but also ensure transparency and understandability in their operations. This study introduces DeepExplain, a new approach that combine convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, augmented with explainability features to enhance the detection of DeepFakes. Utilizing the comprehensive DeepFake Detection Challenge (DFDC) dataset, DeepExplain demonstrates superior accuracy and balanced performance across essential metrics such as recall, precision, and area under the receiver operating characteristic (AUROC) curve. Crucially, by integrating explainability mechanisms like Gradientweighted Class Activation Mapping (Grad-CAM) and SHapley Additive exPlanations (SHAP) values, DeepExplain not only identifies DeepFakes but also provides insights into the decision-making process, fostering trust and facilitating broader understanding. The findings underscore the potential of explainable and transparent AI solutions in combating the evolving threat of DeepFakes, highlighting important directions for future research and practical applications in digital media verification and security. Povetek: Študija predstavlja DeepExplain, metodo za zaznavanje DeepFake vsebin, ki združuje CNN in LSTM omrežja z mehanizmi razložljivosti. DeepExplain dosega visoko točnost na DFDC podatkovnem naboru, vključuje pa tudi Grad-CAM in SHAP za večjo transparentnost in razumevanje odločitev modela.
Among all cancers, pancreatic cancer has a very poor prognosis. Early diagnosis, as well as succe... more Among all cancers, pancreatic cancer has a very poor prognosis. Early diagnosis, as well as successful treatment, are difficult to achieve. As the death rate is increasing at a rapid rate (47,050 out of 57650 cases), it is of utmost importance for medical experts to diagnose PC at earlier stages. The application of Deep Learning (DL) techniques in the medical field has revolutionized so much in this era of technological advancement. An analysis of clinical proteomic tumor data provided by the Clinical Proteome Tumor Analysis Consortium Pancreatic Ductal Adenocarcinoma (CPTAC-PDA) at the National Cancer Institute was used to demonstrate an innovative deep learning approach in this study. This includes a) collection of data b) preprocessed using CLAHE and BADF techniques for noise removal and image enhancement, c) segmentation using UNet++ for segmenting regions of interest of cancer. Followed by, d) feature extraction using HHO based on CNN and e) feature selection using HHO based on BOVW for extracting and selecting features from the images. Finally, these are subject to the f) classification stage for better analysis using the VGG16 network. Experimental results are carried out using various state-of-art models over various measures in which the proposed model outperforms with better accuracy:0.
A Modified Shape Feature Extraction Technique For Image Retrieval
Semantic based Image retrieval is an emerging research area and is currently the mainstay in vari... more Semantic based Image retrieval is an emerging research area and is currently the mainstay in variety of applications or domains. In recent times, there exists a lot of gap between the high level semantics and low level features. The process of Features extraction is Application-specific or options are limited. In this paper, we propose a new Modified Shape Descriptor (MSD) feature extraction technique which is used as descriptive feature to discriminate Objects in an image database. In Object recognition after initial Pre-processing, feature extraction is the next crucial step which determines the efficiency of the technique or method. In our approach, a test image is taken from the database, which is then divided into 8x8 Blocks each; shape structure is detected using edge detection technique with Threshold method to generate the shape feature vector. Then, texton-based texture, color features are extracted using the existing Multi-texton Histogram (MTH) method. To form the final d...
Journal of Information Technology Management (JITM), 2023
Extracting sentiments from the English-Telugu code-mixed data can be challenging and is still a r... more Extracting sentiments from the English-Telugu code-mixed data can be challenging and is still a relatively new research area. Data obtained from the Twitter API has to be in English-Telugu code-mixed language. That data is free-form text, noisy, lexicon borrowings, codemixed, phonetic typing and misspelling data. The initial step is language identification and sentiment class labels assigned to each tweet in the dataset. The second step is the data normalization task, and the final step is classification, which can be achieved using three different methods: lexicon, machine learning, and deep learning. In the lexicon-based approach, tokenize each tweet with its language tag. If the language tag is in Telugu, transliterate the roman script into native Telugu words. Words are verified with TeluguSentiWordNet, and the Telugu sentiments are extracted, and English SentiWordNets are used to extract sentiments from the English tokens. In this paper, the aspect-based sentiment analysis approach is suggested and used with normalized data. In addition, deep learning and machine learning techniques are applied to extract sentiment ratings, and the results are compared to prior work.
Authentication of symmetric cryptosystem using anti-aging controller-based true random number generator
Applied Nanoscience, 2021
In today’s digital world, data protection is extremely important. Every company’s data is a valua... more In today’s digital world, data protection is extremely important. Every company’s data is a valuable asset, so it’s important to ensure that it's secured from outside threats. Information security is not only an effective but also a necessary element to protect data from unauthorized access. The confidentiality of any communication system is strengthening with the help of random number generators along with some analog circuitry. This type of analog models demands more power and area. So analog circuit-based hardware Random Number Generators (RNG) are least preferred over digital RNGs. To improve the security every industry depends on the one-time password (OTP). Which gives the security but generation of the OTP is very easy. Random number generator is used for the generation of OTP. Similarly, hacking such OTP is easier than creating them. This paper introduces the Anti-Aging controller TRNG, a highly stable high-performance random number generator Anti-Aging Cryptographically Secured True Random Number Generator (AACTRNG). Implementation of this work can be done by using TANNER EDA Tools and ModelSim-Altera 6.4a (Quartus-II 9.0) used for the simulation to retrieve random numbers.
image searching is a necessity. Content-Based Image Retrieval (CBIR) is an approach for image ret... more image searching is a necessity. Content-Based Image Retrieval (CBIR) is an approach for image retrieval. With User interaction included in CBIR with Relevance Feedback (RF) techniques, the results are obtained by giving more number of iterative feedbacks for large databases is not an efficient method for realtime applications. So, we propose a new approach which converges rapidly and can aptly be called as Navigation Pattern-Based Relevance Feedback (NPRF) with User-based interaction mode. We combined NPRF with RF techniques with three concepts viz., query Re-weighting (QR), Query Expansion (QEX) and Query Point Movement (QPM). By using, these three techniques efficient results are obtained by giving a small number of feedbacks. The efficiency of the proposed method with results is proved by calculating Precision, Recall and Evaluation measures.
A new method using a highly efficient filter algorithm for the restoration of images that are ver... more A new method using a highly efficient filter algorithm for the restoration of images that are very highly corrupted by high density salt and pepper noise is proposed in this paper. The proposed method restores the image by processing the values of the pixels having 0 or 255 and copying the processed result in new image’s corresponding pixel. Initially the new resulting image is to be assigned with noisy image. When all the pixel values in the selected window are 0’s and 255’s, the pixel value of the new image is replaced by the median of the pixel values that are processed before the present pixel gets processed. The proposed algorithm provides much better results than the Median Filter (MF), Modified Decision Based Unsymmetric Trimmed Median Filter (MDBUTMF) which shows better results than Decision Based Algorithm (DBA), Modified Decision Based Algorithm (MDBA) and Progressive Switched Median Filter (PSMF).The Proposed method of noise removal is tested against color and gray images...
International Journal of Recent Trends in Engineering and Research, 2017
Declaration of 86 percent of currency notes as illegal tender in just a blink of time on eve of 8... more Declaration of 86 percent of currency notes as illegal tender in just a blink of time on eve of 8th November 2016 mandated the creation of immediate interruption in daily lives. The chaos was created in every strata of the society whether upper, middle, or lower. Where some welcome the move as it was seen for curbing black money, many are suffering by this movement. But the supreme suffers of this move were the informal sector of India economy, where cashless transaction are minimal. Informal sectors of India Economy include 106 activities like agriculture, worker in construction, local transport, community services and small workshops like shoe makes and garment makers (International Conference of Labour Statistics (2003), rural populations and the urban poor and middle class. This paper aimed at reviewing the general implication of demonetization on people.
A Novel Block-Cipher Mechanism for Information Security in Cloud System
2016 IEEE 6th International Conference on Advanced Computing (IACC), 2016
Digital information is precious asset in modern period as everything is offered in digital mode. ... more Digital information is precious asset in modern period as everything is offered in digital mode. A prime concern for digital data is to guard it from getting seep out to eavesdropper. In this regard many cryptosystems were explored to prevent data from disclosure. In this paper, we explore a new cryptosystem that is implemented in three stages on plain text blocks. Our method applies simple operations on them based on keys that are constructed randomly. Our approach achieves the following three goals. Firstly it creates high defense cryptosystem. Second, it offers low complex encryption and decryption systems. Finally all actions are randomly done that avoids tediousness and stands firm for the assailant to break it.
International Journal of Advanced Computer Science and Applications, 2013
In Internet, Multimedia and Image Databases image searching is a necessity. Content-Based Image R... more In Internet, Multimedia and Image Databases image searching is a necessity. Content-Based Image Retrieval (CBIR) is an approach for image retrieval. With User interaction included in CBIR with Relevance Feedback (RF) techniques, the results are obtained by giving more number of iterative feedbacks for large databases is not an efficient method for realtime applications. So, we propose a new approach which converges rapidly and can aptly be called as Navigation Pattern-Based Relevance Feedback (NPRF) with User-based interaction mode. We combined NPRF with RF techniques with three concepts viz., query Re-weighting (QR), Query Expansion (QEX) and Query Point Movement (QPM). By using, these three techniques efficient results are obtained by giving a small number of feedbacks. The efficiency of the proposed method with results is proved by calculating Precision, Recall and Evaluation measures.
International Journal of Innovative Technology and Exploring Engineering, 2019
Chatbot is a program which provides human conversation using Artificial Intelligence (AI). Chatbo... more Chatbot is a program which provides human conversation using Artificial Intelligence (AI). Chatbots are designed to work as VIRTUAL ASSISTANTS (VA). They themselves provide a platform for the promotions of the Products and Services online. All Higher Educational Institutes provide the complete information through their internet sites for students, which admits the use of social nets such as Facebook, WhatsApp, and College websites. Total-in-All, in any website, searching functionality is required to search for any information and it includes Social Media Applications like Facebook and WhatsApp regular response are utilized. Therefore, Chatbot is an effective auto-response system, and also an instant messaging platform. In this paper, AICMS an AI-Based CollegeBot management system for professional Engineering college system provide the auto-response to student queries about the college basic information, class timetables, examination schedules related to academics. Many Queries about...
International Journal of Electrical and Computer Engineering (IJECE), 2020
Twitter sentiment analysis is one of the leading research fields. Most of the researchers were co... more Twitter sentiment analysis is one of the leading research fields. Most of the researchers were contributed to twitter sentiment analysis in English tweets, but few researchers focus on the multilingual twitter sentiment analysis. Some challenges are hoping for the research solutions in multilingual twitter sentiment analysis. This study presents the implementation of sentiment analysis in multilingual twitter data and improves the data classification up to the adequate level of accuracy. Twitter is the sixth leading social networking site in the world. Active users for twitter in a month are 330 million. People can tweet or re-tweet in their languages and allow users to use emoji’s, abbreviations, contraction words, miss spellings, and shortcut words. The best platform for sentiment analysis is twitter. Multilingual tweets and data sparsity are the two main challenges. In this paper, the MLTSA algorithm gives the solution for these two challenges. MLTSA algorithm divides into two pa...
The rapid advancement of digital media technologies has given rise to DeepFake videos, synthetic ... more The rapid advancement of digital media technologies has given rise to DeepFake videos, synthetic content generated using deep learning algorithms that can convincingly mimic real individuals' appearances and actions. This presents a significant challenge in maintaining digital content integrity, as DeepFakes pose threats to information veracity, security, and public trust. Addressing this challenge necessitates robust detection methods that not only accurately identify DeepFakes but also ensure transparency and understandability in their operations. This study introduces DeepExplain, a new approach that combine convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, augmented with explainability features to enhance the detection of DeepFakes. Utilizing the comprehensive DeepFake Detection Challenge (DFDC) dataset, DeepExplain demonstrates superior accuracy and balanced performance across essential metrics such as recall, precision, and area under the receiver operating characteristic (AUROC) curve. Crucially, by integrating explainability mechanisms like Gradientweighted Class Activation Mapping (Grad-CAM) and SHapley Additive exPlanations (SHAP) values, DeepExplain not only identifies DeepFakes but also provides insights into the decision-making process, fostering trust and facilitating broader understanding. The findings underscore the potential of explainable and transparent AI solutions in combating the evolving threat of DeepFakes, highlighting important directions for future research and practical applications in digital media verification and security. Povetek: Študija predstavlja DeepExplain, metodo za zaznavanje DeepFake vsebin, ki združuje CNN in LSTM omrežja z mehanizmi razložljivosti. DeepExplain dosega visoko točnost na DFDC podatkovnem naboru, vključuje pa tudi Grad-CAM in SHAP za večjo transparentnost in razumevanje odločitev modela.
Among all cancers, pancreatic cancer has a very poor prognosis. Early diagnosis, as well as succe... more Among all cancers, pancreatic cancer has a very poor prognosis. Early diagnosis, as well as successful treatment, are difficult to achieve. As the death rate is increasing at a rapid rate (47,050 out of 57650 cases), it is of utmost importance for medical experts to diagnose PC at earlier stages. The application of Deep Learning (DL) techniques in the medical field has revolutionized so much in this era of technological advancement. An analysis of clinical proteomic tumor data provided by the Clinical Proteome Tumor Analysis Consortium Pancreatic Ductal Adenocarcinoma (CPTAC-PDA) at the National Cancer Institute was used to demonstrate an innovative deep learning approach in this study. This includes a) collection of data b) preprocessed using CLAHE and BADF techniques for noise removal and image enhancement, c) segmentation using UNet++ for segmenting regions of interest of cancer. Followed by, d) feature extraction using HHO based on CNN and e) feature selection using HHO based on BOVW for extracting and selecting features from the images. Finally, these are subject to the f) classification stage for better analysis using the VGG16 network. Experimental results are carried out using various state-of-art models over various measures in which the proposed model outperforms with better accuracy:0.
A Modified Shape Feature Extraction Technique For Image Retrieval
Semantic based Image retrieval is an emerging research area and is currently the mainstay in vari... more Semantic based Image retrieval is an emerging research area and is currently the mainstay in variety of applications or domains. In recent times, there exists a lot of gap between the high level semantics and low level features. The process of Features extraction is Application-specific or options are limited. In this paper, we propose a new Modified Shape Descriptor (MSD) feature extraction technique which is used as descriptive feature to discriminate Objects in an image database. In Object recognition after initial Pre-processing, feature extraction is the next crucial step which determines the efficiency of the technique or method. In our approach, a test image is taken from the database, which is then divided into 8x8 Blocks each; shape structure is detected using edge detection technique with Threshold method to generate the shape feature vector. Then, texton-based texture, color features are extracted using the existing Multi-texton Histogram (MTH) method. To form the final d...
Journal of Information Technology Management (JITM), 2023
Extracting sentiments from the English-Telugu code-mixed data can be challenging and is still a r... more Extracting sentiments from the English-Telugu code-mixed data can be challenging and is still a relatively new research area. Data obtained from the Twitter API has to be in English-Telugu code-mixed language. That data is free-form text, noisy, lexicon borrowings, codemixed, phonetic typing and misspelling data. The initial step is language identification and sentiment class labels assigned to each tweet in the dataset. The second step is the data normalization task, and the final step is classification, which can be achieved using three different methods: lexicon, machine learning, and deep learning. In the lexicon-based approach, tokenize each tweet with its language tag. If the language tag is in Telugu, transliterate the roman script into native Telugu words. Words are verified with TeluguSentiWordNet, and the Telugu sentiments are extracted, and English SentiWordNets are used to extract sentiments from the English tokens. In this paper, the aspect-based sentiment analysis approach is suggested and used with normalized data. In addition, deep learning and machine learning techniques are applied to extract sentiment ratings, and the results are compared to prior work.
Authentication of symmetric cryptosystem using anti-aging controller-based true random number generator
Applied Nanoscience, 2021
In today’s digital world, data protection is extremely important. Every company’s data is a valua... more In today’s digital world, data protection is extremely important. Every company’s data is a valuable asset, so it’s important to ensure that it's secured from outside threats. Information security is not only an effective but also a necessary element to protect data from unauthorized access. The confidentiality of any communication system is strengthening with the help of random number generators along with some analog circuitry. This type of analog models demands more power and area. So analog circuit-based hardware Random Number Generators (RNG) are least preferred over digital RNGs. To improve the security every industry depends on the one-time password (OTP). Which gives the security but generation of the OTP is very easy. Random number generator is used for the generation of OTP. Similarly, hacking such OTP is easier than creating them. This paper introduces the Anti-Aging controller TRNG, a highly stable high-performance random number generator Anti-Aging Cryptographically Secured True Random Number Generator (AACTRNG). Implementation of this work can be done by using TANNER EDA Tools and ModelSim-Altera 6.4a (Quartus-II 9.0) used for the simulation to retrieve random numbers.
image searching is a necessity. Content-Based Image Retrieval (CBIR) is an approach for image ret... more image searching is a necessity. Content-Based Image Retrieval (CBIR) is an approach for image retrieval. With User interaction included in CBIR with Relevance Feedback (RF) techniques, the results are obtained by giving more number of iterative feedbacks for large databases is not an efficient method for realtime applications. So, we propose a new approach which converges rapidly and can aptly be called as Navigation Pattern-Based Relevance Feedback (NPRF) with User-based interaction mode. We combined NPRF with RF techniques with three concepts viz., query Re-weighting (QR), Query Expansion (QEX) and Query Point Movement (QPM). By using, these three techniques efficient results are obtained by giving a small number of feedbacks. The efficiency of the proposed method with results is proved by calculating Precision, Recall and Evaluation measures.
A new method using a highly efficient filter algorithm for the restoration of images that are ver... more A new method using a highly efficient filter algorithm for the restoration of images that are very highly corrupted by high density salt and pepper noise is proposed in this paper. The proposed method restores the image by processing the values of the pixels having 0 or 255 and copying the processed result in new image’s corresponding pixel. Initially the new resulting image is to be assigned with noisy image. When all the pixel values in the selected window are 0’s and 255’s, the pixel value of the new image is replaced by the median of the pixel values that are processed before the present pixel gets processed. The proposed algorithm provides much better results than the Median Filter (MF), Modified Decision Based Unsymmetric Trimmed Median Filter (MDBUTMF) which shows better results than Decision Based Algorithm (DBA), Modified Decision Based Algorithm (MDBA) and Progressive Switched Median Filter (PSMF).The Proposed method of noise removal is tested against color and gray images...
International Journal of Recent Trends in Engineering and Research, 2017
Declaration of 86 percent of currency notes as illegal tender in just a blink of time on eve of 8... more Declaration of 86 percent of currency notes as illegal tender in just a blink of time on eve of 8th November 2016 mandated the creation of immediate interruption in daily lives. The chaos was created in every strata of the society whether upper, middle, or lower. Where some welcome the move as it was seen for curbing black money, many are suffering by this movement. But the supreme suffers of this move were the informal sector of India economy, where cashless transaction are minimal. Informal sectors of India Economy include 106 activities like agriculture, worker in construction, local transport, community services and small workshops like shoe makes and garment makers (International Conference of Labour Statistics (2003), rural populations and the urban poor and middle class. This paper aimed at reviewing the general implication of demonetization on people.
A Novel Block-Cipher Mechanism for Information Security in Cloud System
2016 IEEE 6th International Conference on Advanced Computing (IACC), 2016
Digital information is precious asset in modern period as everything is offered in digital mode. ... more Digital information is precious asset in modern period as everything is offered in digital mode. A prime concern for digital data is to guard it from getting seep out to eavesdropper. In this regard many cryptosystems were explored to prevent data from disclosure. In this paper, we explore a new cryptosystem that is implemented in three stages on plain text blocks. Our method applies simple operations on them based on keys that are constructed randomly. Our approach achieves the following three goals. Firstly it creates high defense cryptosystem. Second, it offers low complex encryption and decryption systems. Finally all actions are randomly done that avoids tediousness and stands firm for the assailant to break it.
International Journal of Advanced Computer Science and Applications, 2013
In Internet, Multimedia and Image Databases image searching is a necessity. Content-Based Image R... more In Internet, Multimedia and Image Databases image searching is a necessity. Content-Based Image Retrieval (CBIR) is an approach for image retrieval. With User interaction included in CBIR with Relevance Feedback (RF) techniques, the results are obtained by giving more number of iterative feedbacks for large databases is not an efficient method for realtime applications. So, we propose a new approach which converges rapidly and can aptly be called as Navigation Pattern-Based Relevance Feedback (NPRF) with User-based interaction mode. We combined NPRF with RF techniques with three concepts viz., query Re-weighting (QR), Query Expansion (QEX) and Query Point Movement (QPM). By using, these three techniques efficient results are obtained by giving a small number of feedbacks. The efficiency of the proposed method with results is proved by calculating Precision, Recall and Evaluation measures.
International Journal of Innovative Technology and Exploring Engineering, 2019
Chatbot is a program which provides human conversation using Artificial Intelligence (AI). Chatbo... more Chatbot is a program which provides human conversation using Artificial Intelligence (AI). Chatbots are designed to work as VIRTUAL ASSISTANTS (VA). They themselves provide a platform for the promotions of the Products and Services online. All Higher Educational Institutes provide the complete information through their internet sites for students, which admits the use of social nets such as Facebook, WhatsApp, and College websites. Total-in-All, in any website, searching functionality is required to search for any information and it includes Social Media Applications like Facebook and WhatsApp regular response are utilized. Therefore, Chatbot is an effective auto-response system, and also an instant messaging platform. In this paper, AICMS an AI-Based CollegeBot management system for professional Engineering college system provide the auto-response to student queries about the college basic information, class timetables, examination schedules related to academics. Many Queries about...
International Journal of Electrical and Computer Engineering (IJECE), 2020
Twitter sentiment analysis is one of the leading research fields. Most of the researchers were co... more Twitter sentiment analysis is one of the leading research fields. Most of the researchers were contributed to twitter sentiment analysis in English tweets, but few researchers focus on the multilingual twitter sentiment analysis. Some challenges are hoping for the research solutions in multilingual twitter sentiment analysis. This study presents the implementation of sentiment analysis in multilingual twitter data and improves the data classification up to the adequate level of accuracy. Twitter is the sixth leading social networking site in the world. Active users for twitter in a month are 330 million. People can tweet or re-tweet in their languages and allow users to use emoji’s, abbreviations, contraction words, miss spellings, and shortcut words. The best platform for sentiment analysis is twitter. Multilingual tweets and data sparsity are the two main challenges. In this paper, the MLTSA algorithm gives the solution for these two challenges. MLTSA algorithm divides into two pa...
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