Browsing by Author "Hossen, Md. Sagar"

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A Digital Data Hiding Technique with Missing Puzzle and Seek Algorithm
(IEEE, 2020-11) Islam, Md. Ashiqul; Tabassum, Tasfia; Hossen, Md. Sagar; Hossain, Shahed; Hossain, Mosharof; Jony, Anik Hassan
presently a day’s data dissemination over the world become progressively simpler because of quick web and advancement of various kind of technology, for this explanation individuals become increasingly stressed about their information security. For this nowadays people use steganography to make the information secure by hiding and blending the data that make them hard to perceive by hackers. For concealing mystery data in content and pictures, there exists a huge assortment of Steganography methods some are more mind-boggling than others and every one of them has particular solid and feeble focuses. We are looking for the calculation to discover the missing puzzle word which otherwise called mystery calculation by using seek algorithm. For improving the security of mystery message, the message is mixed utilizing onetime cushion plot before being covered and Figure content is at that point hidden in the spread. This is the most efficient data hiding security system and probably its increases the data security all over the world and maintain our privacy.
A Multi-layer Cryptosystem for Secure Data Transmission Using PRNG
(IEEE, 2020-12) Islam, Md. Ashiqul; Md. Shourov, Sarker; Hossen, Md. Sagar; Mridul, Aunik Hasan; Hasib, Md. Abdul; Jabiullah, Md. Ismail
Nowadays the usage of the Internet is developing day by day. One of the largest uses of the internet is to transfer data from different sources to different states. During data transfer over the internet, a major issues arises with data protection. When transferring data over the internet with security that is called data security. Two techniques are used in data protection. Cryptography and Steganography. In our proposed system Cryptography and Steganography are combine used for making the data more secure. The basic function of Cryptography is encryption and decryption. Here, the message is encrypted more than 4 Times. Basically in Cryptography method the secret message are encrypted with an encryption key. The sender uses the encryption key for sending a message. On the other hand, the receiver should know the encryption key for decrypting the message to get the original data. Instantly Steganography is the way to hides secret data using digital media cover such as Audio, Image and Video and Text. In our proposed system, Color Image has been used for embedding the secrete message. In the proposed technique mostly used random binary digit from multiple pixel instead of LSB technique after converting the stego image into a binary form. Before embedding the secret message the Robust Cryptography Algorithm Advanced Encryption Standard (AES) & Pseudorandom Number Generator (PRNG) has been used to encrypting the secret message and secure the confidential data from the unauthorized access.
A New Approach to Hiding Data in the Images Using Steganography Techniques Based on AES and RC5 Algorithm Cryptosystem
(IEEE, 2020-09) Hossen, Md. Sagar; Islam, Md. Ashiqul; Khatun, Tania; Hossain, Shahed; Rahman, Md. Mahfujur
In the new era of modern science and technology is developing day by day, data confidentiality is risky, all over the world and it increases rapidly. In this paper, a new approach to hiding the data using steganography techniques is proposed based on AES and RC5 algorithm cryptosystem. Steganography is the beauty of hiding secret data behind the digital images, videos, audios and text to cover the secret communication. A cryptosystem is the process which given our method more perfection. The visual quality of the cover image nice, no one can think about it how confidential data are transmitted using this method. This proposed method and algorithm capacity is highly flexible than other published algorithm. The AES and RC5 algorithm had no complexity and it looks like very well to hide the confidential data.
An Online E-Cash Scheme with Digital Signature Authentication Cryptosystem
(Springer, 2021-01-26) Islam, Md. Ashiqul; Hossen, Md. Sagar; Hossain, Mosharof; Nime, Jannati; Hossain, Shahed; Dutta, Mithun
This paper is intended to enlighten the curious minds on how to use cryptocurrency easily in our day-to-day life. What bitcoin really is? The relation between bank and the user, who has bitcoin, describes potential system design, basic payment method using cryptocurrency, the payment gateway and explains it in the simplest way, and finally the conclusion. Cryptocurrency is one type of digital virtual currencies that have not physically existed. This proposed research work is mainly focused on bitcoin, which is the decentralized digital currency, and it conducts peer-to-peer connection, to make it safe and secure than other digital currency types or hand cash. This paper has proposed an online E-cash scheme with a digital signature authentication cryptosystem that has the tendency to replace the traditional fiat currency, and bitcoin is used instead of the conventional currency and payment system. We can exchange bitcoin to E-cash and E-cash to bitcoin also. This system will find a new way to protect the users from unauthorized transactions in online and offline E-cash system.
An Online E-Cash Scheme with Digital Signature Authentication Cryptosystem
(Scopus, 2021) Islam, Md. Ashiqul; Hossen, Md. Sagar; Hossain, Mosharof; Nime, Jannati; Hossain, Shahed; Dutta, Mithun
This paper is intended to enlighten the curious minds on how to use crypto currency easily in our day-to-day life. What bit coin really is? The relation between bank and the user, who has bit coin, describes potential system design, basic payment method using crypto currency, the payment gateway and explains it in the simplest way, and finally the conclusion. Crypto currency is one type of digital virtual currencies that have not physically existed. This proposed research work is mainly focused on bitcoin, which is the decentralized digital currency, and it conducts peer-to-peer connection, to make it safe and secure than other digital currency types or hand cash. This paper has proposed an online E-cash scheme with a digital signature authentication cryptosystem that has the tendency to replace the traditional fiat currency, and bitcoin is used instead of the conventional currency and payment system. We can exchange bitcoin to E-cash and E-cash to bitcoin also. This system will find a new way to protect the users from unauthorized transactions in online and offline E-cash system.
Dark Tetrad of Personality, Cyberbullying, and Cybertrolling Among Young Adults
(IEEE, 2023-07-30) Hossen, Md. Sagar; Ahmad, Tohari; Croix, Ntivuguruzwa Jean De La
Our information is constantly under threat when transmitted through public networks. So, research to keep information secret has been carried out. Mainly, steganography, which consists of hiding data in digital media, receives much attention. Existing steganographic systems identified the need to improve performance by reducing a tradeoff between the peak signal-to-noise ratio (PSNR) and bits per pixel (BPP). In this paper, we propose a new steganographic scheme to embed the bits of secret messages in a digital image’s pixels. Our method expands the differences between the neighbouring pixels for secret data concealment. We group the pixels in blocks of size $1\times 3$, and two of the three pixels of the block are candidates to hold the secret bit. We also propose extracting the hidden data to validate our data concealment scheme. To extract the secret data, we also arrange the neighbouring pixels into blocks of three and use their differences, and a modulus function, based on pixels identified carrying the secret data based on the key generated during data concealment. To evaluate the performance of our scheme, we consider the PSNR and the BPP as metrics. The experimental results showed better performance over the existing methods with 68.7790 dB for the PSNR and 0.1562 BPP.
Data Security System for a Bank Based On Two Different Asymmetric Algorithms Cryptography
(Springer, 2021) Islam, Md. Ashiqul; Kobita, Aysha Akter; Hossen, Md. Sagar; Rumi, Laila Sultana; Karim, Rafat; Tabassum, Tasfia
Recently, a strong security system is very important for a safe banking system. To prevent hacking of important information of bank and client, a secure banking system is a must. This paper deals with a strong security system using a hash function and two different asymmetric algorithms (DSA and RSA) at a time, it will enhance data security. We are using RSA and DSA encryption algorithm to secure our system from unauthorized access. In RSA and DSA, we have to generate two keys called Public and Private Keys. If we use the signer’s private key for encryption, then we have to use the signer’s public key for decryption. The system will verify by confirmation and certificate and the sender will be sent an OTP via mobile phone of the receiver to confirm the authentication. This is the most efficient data security system to save the bank from hacktivism.
Data Security System for a Bank Based on Two Different Asymmetric Algorithms Cryptography
(Evolutionary Computing and Mobile Sustainable Networks. Lecture Notes on Data Engineering and Communications Technologies, Springer, 2020-08-01) Islam, Md. Ashiqul; Kobita, Aysha Akter; Hossen, Md. Sagar; Rumi, Laila Sultana; Karim, Rafat; Tabassum, Tasfia
Recently, a strong security system is very important for a safe banking system. To prevent hacking of important information of bank and client, a secure banking system is a must. This paper deals with a strong security system using a hash function and two different asymmetric algorithms (DSA and RSA) at a time, it will enhance data security. We are using RSA and DSA encryption algorithm to secure our system from unauthorized access. In RSA and DSA, we have to generate two keys called Public and Private Keys. If we use the signer’s private key for encryption, then we have to use the signer’s public key for decryption. The system will verify by confirmation and certificate and the sender will be sent an OTP via mobile phone of the receiver to confirm the authentication. This is the most efficient data security system to save the bank from hacktivism.
Digital Signature Authentication for a Bank Using Asymmetric Key Cryptography Algorithm and Token Based Encryption
(Springer, 2020-08-01) Karim, Rafat; Rumi, Laila Sultana; Islam, Md. Ashiqul; Kobita, Aysha Akter; Tabassum, Tasfia; Hossen, Md. Sagar
Nowadays security system is being with more important issues. In modern science, technology is updated day by day and we are getting insecure in our daily life. Through this project, a digital signature authentication security system has been designed to protect the bank from unauthorized access. In this paper, we are producing the most efficient and productive security system based on digital signature authentication using the asymmetric key cryptography algorithm and token-based encryption. In this project, we are using public and private keys for encryption and decryption data with the hash function and also provide digitally signed data, RSA algorithm to encrypt the data. The receiver will send a certificate and confirmation request to the sender to verify the certificate and the sender will send an OTP via phone through the Internet to authenticate the receiver. All of these works are producing a good and valuable security system in the banking sector.
Digital Signature Authentication Using Asymmetric Key Cryptography with Different Byte Number
(Springer, 2021) Hossen, Md. Sagar; Tabassum, Tasfia; Islam, Md. Ashiqul; Karim, Rafat; Rumi, Laila Sultana; Kobita, Aysha Akter
Nowadays, each and every system needs proper security. Only proper security can save important documents. There are different types of security systems that people use for safety. Digital Signature is one kind of a security system. Digital Signature is the public key primitive of different types of message authentication. Digital signature is one kind of technique that converts the handwritten signature in digital data. It is one kind of cryptographic value that is calculated from the data and a secret private key which is only known by the signer. In this paper, we want to make the digital signature more secure by using the ED25519 algorithm, which is an asymmetric algorithm. In this algorithm, the signature will be converted into different byte numbers, which will make the security system more strong.
Digital Signature Authentication Using Asymmetric Key Cryptography with Different Byte Number
(Springer, 2020-08-01) Hossen, Md. Sagar; Tabassum, Tasfia; Islam, Md. Ashiqul; Karim, Rafat; Rumi, Laila Sultana; Kobita, Aysha Akter
Nowadays, each and every system needs proper security. Only proper security can save important documents. There are different types of security systems that people use for safety. Digital Signature is one kind of a security system. Digital Signature is the public key primitive of different types of message authentication. Digital signature is one kind of technique that converts the handwritten signature in digital data. It is one kind of cryptographic value that is calculated from the data and a secret private key which is only known by the signer. In this paper, we want to make the digital signature more secure by using the ED25519 algorithm, which is an asymmetric algorithm. In this algorithm, the signature will be converted into different byte number, which will make the security system more strong.
E-commerce Merchant Fraud Detection using Machine Learning Approach
(Daffodil International University, 2022-06-20) Hasan, Fahim; Mondal, Sourov Kumar; Kabir, Md Rayhan; Al Mamun, Md Abdullah; Hossen, Md. Sagar; Rahman, Nur Salman
At present, e-commerce has become a global phenomenon. With the great achievement of ecommerce, many are cruel Promotional services are also increasing: with the aim of growing sales, spiteful marketers try to improve their target spectators by improving the outcomes of an illegal search using false travel, shopping, etc. In this report, we read about the problem of deception in major commerce platforms. First, we want to list the merchant fraud, the names of those who have previously committed fraud in the business will be marked on the list. And will train machines using machine learning approach. So that, if a merchant id is given in the system, it can detect whether the id is fraud or not. Our lesson here paper is predictable to hut light on the defense in contradiction of e-commerce fraud of active commerce platforms. In this research report, we proposed a machine learning model to analyze and identify merchant fraud. As a machine learning model, we choose the Random forests, decision tree and logistic regression algorithm for our model.
Examining The Risk Factors of Liver Disease
(Daffodil International University, 2022-06-20) Hossen, Md. Sagar; Haque, Imdadul; Sarkar, Puja Rani; Islam, Md. Ashiqul; Fahim, Wasik Ahmed; Fahim, ,Wasik Ahmmed; Khatun, Tania
Nowadays, Liver Disease (LD) is a very common clinical problem for human health and is related to morbidity and mortality. Nevertheless, an earlier prognosis of LD patients gets a scope to avoid, prior diagnosis and subsequent treatment. This research work attempts to implement a high qualified performer machine learning design to predict LD, the most wanted and unwanted risk factor of LD which could help physicians in classifying risky patients and create an analysis to restrict and control LD. The proposed research study has included all patients, who were identified as having liver diseases. Totally, 6 (six) machine learning algorithms such as Decision Tree(DT), Logistic Regression(LR), Multilayer Perceptron(MLP), Artificial Neural Network(ANN), Random Forest(RF), K Nearest Neighbor classifier(KNN) are selected to predict LD. The location underneath had been utilized to evaluate the accuracy among the six applied models. An overall total of 583 instances had been included in this scholarly research; of the 416 patients are affected by liver illness. The location which defines the receiver operating characteristic (AU ROC) of Logistic Regression, Decision Tree, Multilayer Perceptron, Random Forest, Artificial Neural Network, and K-Nearest Neighbor classifier with 10-fold-cross validation was performed. Furthermore, the reliability of LR, DT, MLP, RF, ANN and KNN with accuracy 72.89%, 81.32%, 60.24%, 86.14%, 75.61%, and 65.52%. The utilization of woodland which is certainly arbitrary within the medical setting may help doctors to detect and classify liver patients for major avoidance, surveillance, quick treatment, and management. LR, DT, MLP, RF, ANN, and KNN formulas are acclimatized to forecast and after analyzing the data set, an increased price of accuracy is achieved.
Hotel Review Analysis for the Prediction of Business Using Deep Learning Approach
(International Conference on Artificial Intelligence and Smart Systems (ICAIS), IEEE, 2021-04-12) Hossen, Md. Sagar; Jony, Anik Hassan; Tabassum, Tasfia; Islam, Md. Tanvir; Rahman, Md Mahfujur; Khatun, Tania
Sentiment analysis is a widely used topic in Natural Language Processing that allows identifying the opinions or sentiments from a given text. Social media is the scope for the customers to share their opinion over the products or services as part of customer reviews. Dissect this review has become an important factor for business analysis since online business is exponentially growing in today's techno-friendly competitive market. A large number of algorithms have been found in recent articles. Among those deep learning is an important approach. In the proposed methodology, long short-term memory (LSTM) and Gated recurrent units (GRUs) have been used to train the hotel review data where the accuracy rate of identifying customer opinion is 86%, and 84% respectively. The dataset is also tested by using Naïve Bayes, Decision Tree, Random Forest, and SVM. For Naïve Bayes obtains an accuracy of 75%, for Decision Tree obtains an accuracy of 71%, for Random Forest the accuracy is 82% and for SVM our accuracy result is 71%. Deep learning is used to obtain better business performance and also get the review from customers and also to predict the sentiment about customer review. Our algorithm works properly and gives better accuracy.
Machine Learning Based Image Classification of Papaya Disease Recognition
(2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA), IEEE, 2020-12-28) Islam, Md. Ashiqul; Islam, Md. Shahriar; Hossen, Md. Sagar; Emon, Minhaz Uddin; Keya, Maria Sultana; Habib, Ahsan
To help farmers and rural people of Bangladesh, many research works are proposed in the recent years to recognize the papaya diseases that takes a great deal of advantage in machine learning fields. This research is mainly required to support agriculture to make it highly effective and helpful particularly for papaya cultivation. The primary objective of this paper is to compare some algorithms for papaya disease recognition and identify the ailment by capturing image and classify them based on their diseases with an intelligent system. To overcome this advantage, the recognition of papaya diseases will mainly involve two challenges and those are detecting the disease and classifying the diseases based on their symptoms. The proposed system is presenting an online machine learning based papaya disease in which a person captures an image via mobile app and sends it to the system for disease detection and also compare some algorithms accuracy those are random forest, k-means clustering, SVC and CNN. The system process the images and will give feedback. This intelligent system can easily detect the diseases with a high accuracy of about 98.4% to predict the papaya diseases.
Performance Analysis of Breast Cancer
(2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA), IEEE, 2021-10) Khatun, Tania; Utsho, Md. Mahfuzur Rahman; Islam, Md. Ashiqul; Zohura, Mst. Fatematuz; Hossen, Md. Sagar; Rimi, Robaiya Akter; Anni, Sabiha Jannat
Nowadays, breast cancer is the most emerging disease among women both in developed as well as developing countries. Due to increased life prospects, increased urbanization, and the relinquishment of western societies, the rareness of breast cancer is supersizing in the developing world. Even it became a second popular cause of cancer that has already been announced. It's very hard to identify the early symptom of this type of cancer for reducing numerous death. Different methods of machine learning and data mining techniques are using for medical diagnosis. In this study, four machine-learning algorithms are applying to analyze breast cancer in the inflammation stage and dig up the most cabbalistic and non-cabbalistic risk factors. To analyze breast cancer data from the Coimbra dataset from the UCI machine learning repository to create accurate prediction models for breast cancer. For getting better performance and to get higher accuracy Naïve Bayes (NB), Random Forest (RF), Multilayer Perceptron (MLP), Simple Logistic Regression (SLR) are using to find out some higher accuracy sequentially 70%, 68%, 85%, and 75%. Among all the above algorithms a better accuracy was achieved using Multi-layer Perceptron. Linear Regression (LiR) models are applying to dig up the most cabbalistic and non-cabbalistic risk factors of breast cancer. These results will help the doctor to detect breast cancer easily in the early stage and take the necessary steps.
Risk Factor Prediction of Chronic Kidney Disease Based On Machine Learning Algorithms
(Scopus, 2020) Islam, Md. Ashiqul; Akter, Shamima; Hossen, Md. Sagar; Keya, Sadia Ahmed; Tisha, Sadia Afrin; Hossain, Shahed
Chronic kidney disease (CKD) is an increasing medical issue that declines the productivity of renal capacities and subsequently damages the kidneys. CKD is very common nowadays; cardiovascular infection and end-stage renal illness are two life threatening diseases that can be caused as after-effects of CKD. These are conceivably preventable through early recognizable conditions and treatment of people who are in danger. The expectation of medical problems is a very troublesome assignment. CKD is particularly one of the most lethal diseases in the clinical field. Before it becomes too late to recognize CKD forecast, to get rid of risks, the prediction of risk factor is a major necessary step in the immediate stage. In this research work six algorithms such as Naïve Bayes, Random forest, Simple logistic regression, Decision Stump, Linear regression model, simple linear regression model is used to predict the risk factors of CKD. Considering the orderly execution and investigations of these strategies, six algorithms give a superior and quicker characterization execution. Six individual algorithms are applied to the dataset and the best outcomes have been acquired through the classification of predicting risk factors.