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Secure Decentralization: Examining the Role of Blockchain in Network Security
Blockchain generation has emerged as a novel answer for securing decentralized networks. This technology, which was first created for use in crypto currencies, has received enormous interest in recent years because of its capability for boosting protection in various industries and community protection. The essential precept at the back of block chain technology is the decentralization of statistics garage and control. In a decentralized network, no central authority may control the statistics. Rather, the facts are shipped amongst multiple nodes, making it immune to tampering and single factors of failure. One of the most important advantages of blockchain in community protection is its capacity to offer cozy and transparent communication amongst community customers. Through cryptographic techniques, block chain can affirm the identities of network participants and ensure the authenticity of records trade. This feature is extraordinarily valuable in preventing unauthorized access and facts manipulation. 2024 IEEE. -
Secure framework of authentication mechanism over cloud environment
Cloud computing offers a cost effective virtual infrastructure management along with storage and application-oriented services to its customers. This innovation quickly turns into a generally very widely accepted worldview for conveying administrations through web. In this way, this administration expert provider must be offer the trust and information security, on the grounds that there is a most vital and profitable and most delicate information in extremely secure using cryptographic techniques to secure the data in cloud. So for ensure the privacy of essential information, it must be secured utilizing encryptions algorithms and afterward transferring to cloud. This paper presents a novel technique for electronic distributed computing administrations utilizing two-variable validation (2FA) access control framework. The prime target of the projected framework is to guarantee a optimal security for all the actors involved in the component design of proposed authentication system. Furthermore, property based control in the framework likewise authorize cloud servers to maximum the access to those clients with the same arrangement of properties while saving client privacy. At long last, we additionally do a reproduction to show the practicability of our proposed framework. The assessment work is done by utilizing expense of communication, data transfer capacity and proficiency of the framework as an execution metric. Springer International Publishing AG 2017. -
Secure IBS Scheme for Vehicular Ad Hoc Networks
Vehicular Ad hoc Networks (VANET) havedrastically grown in recent years since they provide a better and more secure driving experience. Due to its characteristics, it is vulnerable to many security attacks. Even though many authentication schemes are proposed, their overheads are high. Hence, this study proposes a new Identity-Based Signature (IBS) for authentication with privacy-preservation. It supports secure communications with additional security features. It requires less overhead since it uses XOR operations and one-way hash functions for the signing and verification process. When the proposed schemes performance is compared to the recent schemes, it is observed that the proposed approach is more efficient in computation and communication. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Secure Identity Based Authentication for Emergency Communications
The Vehicular Ad Hoc Network (VANET) offers secure data transmission between vehicles with the support of reliable authorities and RSUs. RSUs are fully damaged in emergency scenarios like natural catastrophes and are unable to provide the needed services. Vehicles in this scenario must communicate safely without RSUs. Hence, this study suggests a secure and reliable identity-based authentication technique for emergency scenarios. To provide secure vehicle-to-vehicle communication without RSUs, ECC-based IBS is utilized. Additionally, it offers security features like message integrity, privacy protection, and authentication. It is also resistant to attacks depending on authentication and privacy. The proposed technique performs efficiently with less communication and computing cost when its performance is compared with recent schemes. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Secure magnetic resonance image transmission and tumor detection techniques
The transmission of important medical diagnostic, MRI (Magnetic Resonance Imaging) images are vulnerable to third party hackers who does spoofing and they are able to introduce faulty and noisy data that damage the transmission data, which hinders the proper medical diagnostics, research and credibility of labs and doctors, there is a clear lack of awareness and lack of proper security measures taken in transmission of MRI images in the present labs, hospitals and research centers. This project is helpful to reduce the problem of secure transmission of medical images. There are many algorithms which can be applied to these medical images. This project is helpful to provide good security to medical images during transmission. Tumor detection or prediction in medical science is a very complex and expensive job, which is not yet been addressed properly and no proper graphical user interface exists in an open source environment. This project is dedicated to analyze the best tumor detection from an MRI brain image after several segmentation methods such as K-means Clustering and Watershed segmentation. Security is realized considering various techniques for encryption and decryption of the image. The encryption technique finally selected after the survey was based on Rivest, Shamir & Adleman [RSA] algorithm. 2016 IEEE. -
Secure multi-party computation protocol using asymmetric encryption
Privacy preservation is very essential in various real life applications such as medical science and financial analysis. This paper focuses on implementation of an asymmetric secure multi-party computation protocol using anonymization and public-key encryption where all parties have access to trusted third party (TTP) who (1) doesn't add any contribution to computation (2) doesn't know who is the owner of the input received (3) has large number of resources (4) decryption key is known to trusted third party (TTP) to get the actual input for computation of final result. In this environment, concern is to design a protocol which deploys TTP for computation. It is proposed that the protocol is very proficient (in terms of secure computation and individual privacy) for the parties than the other available protocols. The solution incorporates protocol using asymmetric encryption scheme where any party can encrypt a message with the public key but decryption can be done by only the possessor of the decryption key (private key). As the protocol works on asymmetric encryption and packetization it ensures following: (1) Confidentiality (Anonymity) (2) Security (3) Privacy (Data). 2014 IEEE. -
Secured Cloud Computing for Medical Database Monitoring Using Machine Learning Techniques
A growing number of people are calling on the health-care industry to adopt new technologies that are becoming accessible on the market in order to improve the overall quality of their services. Telecommunications systems are integrated with computers, connectivity, mobility, data storage, and information analytics to make a complete information infrastructure system. It is the order of the day to use technology that is based on the Internet of Things (IoT). Given the limited availability of human resources and infrastructure, it is becoming more vital to monitor chronic patients on an ongoing basis as their diseases deteriorate and become more severe. A cloud-based architecture that is capable of dealing with all of the issues stated above may be able to provide effective solutions for the health-care industry. With the purpose of building software that would mix cloud computing and mobile technologies for health-care monitoring systems, we have assigned ourselves the task of designing software. Using a method devised by Higuchi, it is possible to extract stable fractal values from electrocardiogram (ECG) data, something that has never been attempted previously by any other researcher working on the development of a computer-aided diagnosis system for arrhythmia. As a result of the results, it is feasible to infer that the support vector machine has attained the best classification accuracy attainable for fractal features. When compared to the other two classifiers, the feed forward neural network model and the feedback neural network model, the support vector machine excels them both. Furthermore, it should be noted that the sensitivity of both the feed forward neural network and the support vector machine yields results that are equivalent in quality (92.08% and 90.36%, respectively). 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Secured Electronic Transactions Using Visual Encryption: An E-Commerce Instance
The developments in the information technology has led the modern world to rely on the internet for digital information. People around the world depend on the internet for every information from general information to sharing confidential data over the network. Technology has grown so wide that even all the transactions are happening through online platforms. Along with this, there has been a rise in the security threats of the user's confidential data which are shared by the users while buying goods online. To maintain the security there are many authentication techniques available today like OTP, CAPTCHA etc. These security measures taken till now have been adequate till the present day but over time the hackers would find out ways to attack. Data breaches and hacking of user data would increase day by day if preventive measures are not taken time to time. This project focuses on providing security to the user's confidential data with a two way authentication technique. The aim of the project is to include one more security level to the existing online transaction system. The visual cryptographic method is used along with the OTP generating system. 2018 IEEE. -
Securing International Law Against Cyber Attacks through Blockchain Integration
Cyber-attacks have become a growing concern for governments, organizations, and individuals worldwide. In this paper, we explore the use of blockchain technology to secure international law against cyber-attacks. We discuss the advantages of blockchain technology in providing secure and transparent data storage and transmission, and how it can enhance the security of international law. We also review the current state of international law regarding cyber-attacks and the need for a robust and effective legal framework to address cyber threats. The study proposes a blockchain-based approach to secure international law against cyber-attacks. We examine the potential of blockchain technology in providing a decentralized and tamper-proof database that can record and track the implementation of international laws related to cyber-attacks. We also discuss how smart contracts can be utilized to automate compliance with international laws and regulations related to cybersecurity. The study also discusses the challenges and limitations of using blockchain technology to secure international law against cyber-attacks. These include the need for interoperability between different blockchain networks, the high energy consumption of blockchain technology, and the need for international cooperation in implementing and enforcing international laws related to cybersecurity. Overall, this study provides a comprehensive overview of the potential of blockchain technology in securing international law against cyber-attacks. It highlights the need for a robust legal framework to address cyber threats and emphasizes the importance of international cooperation in implementing and enforcing international laws related to cybersecurity. 2023 IEEE. -
Securing medical images using encryption and LSB steganography
Medical imaging plays a vital role in the healthcare industry. Due to the advancements in the healthcare industry medical images are being transferred between geographically spread regions. As the medical images are transmitted through public networks several security challenges may arise such as authentication, integrity, and confidentiality. In this paper, the research focus is on preserving the confidentiality and integrity of the medical images. In general, integrity and confidentiality can be achieved by encryption (a piece of cryptography). To incorporate one more layer of security, steganography is applied to the medical image. In this paper, a one-time pad encryption algorithm is used to encrypt the medical image, then the encrypted image is implanted into a cover image to give a stego image making the system more resilient to the attacker. Further in this paper, the above said method is being implemented using MATLAB and the experimental results are compared with hiding the medical image using LSB steganography without encryption (one layer of security). Various formats of medical images have been taken into consideration such as DICOM, TIFF, BMP, and JPEG. Results show that the combination of encryption and steganography performs better than applying only steganography, concerning MSE and PSNR values. 2021 IEEE -
Securing Provenance Data with Secret Sharing Mechanism: Model Perspective
Elicitation about the genesis of an entity is referred to as provenance. With regards to data objects and their relationships the same is termed as data provenance. In majority of the instances, provenance data is sensitive and a small variation or adjustment leads to change in the entire chain of the data connected. This genesis needed to be secured and access is granted for authorized party. Individual control in preserving the privacy of data is common scenario and there are a good number of approaches with respect to cryptography. We propose a unique model, wherein the control of the data is available with multiple bodies however not with one; and when an access has to be granted for a genuine purpose, all the bodies holding their share will have to agree on a common platform. Combining these shares in a peculiar pattern allows the grant for accessing data. The method of allocating control to multiple bodies and allowing grant based on combining stakes is called as secret sharing mechanism. Division of the shares can be drawn from visual encryption approach. It provides transparencies for a given input message. This paper throws light on a framework associated to securing provenance via secret sharing security notion. 2019 IEEE. -
Securing the Digital Realm: Unmasking Fraud in Online Transactions Using Supervised Machine Learning Techniques
A key component of contemporary banking systems and e-commerce platforms is identifying fraud in online transactions. Traditional rule-based techniques are insufficient for preventing sophisticated fraud schemes because of the increasing complexity and number of expanding online transactions. This research study examines the development of fraud detection methods, emphasizing data analytics and machine learning (ML) models. The study also focuses on the fact that developing efficient fraud detection systems requires continuous observation, data preprocessing, feature selection, and testing of models. Seven ML models, Logistic Regression (LR), Decision Trees (DT), k-Nearest Neighbors (kNN), Nae Bayes (NB), Support Vector Machine (SVM), Random Forests (RF), and Extreme Gradient Boosting (XGBoost) are considered for classifying the dataset into fraudulent or not. During the experimentation study, it was observed that XGBoost yielded the highest accuracy of 99% when compared to other models. Users can determine which features significantly influence the model's predictions by using XGBoost's feature significance insights. Additionally, XGBoost provides integrated support for managing missing values in data, negating the requirement for imputation and other preprocessing procedures. Due to these, it performed better. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Securing Trust in the Connected World: Exploring IoT Security for Privacy in Connected Environments
This abstract delves into IoT security measures to ensure privacy in connected environments. It examines encryption, authentication, access control, and data privacy techniques. Key considerations include end-to-end security, vulnerability mitigation, regulatory compliance, and user trust. By addressing these challenges, trust can be established in the connected world, enabling the widespread adoption of IoT technologies while safeguarding user privacy. 2024 IEEE. -
Security and Privacy in Internet of Things (IoT) Environments
Although the proliferation of IoT devices has led to unparalleled ease of use and accessibility, it has also raised serious privacy and safety issues. Using a systematic approach that incorporates security and privacy modelling, data analysis, and empirical trials, this study provides a deep dive into the topic of IoT security and privacy. Our results show how crucial it is to take precautions against 'Information Disclosure' by using strong encryption and authorization protocols. The need to protect against 'Unencrypted Data' vulnerabilities is further emphasized by vulnerability analysis. Encryption (AES-256) and other access control rules fare very well in the assessment of security systems. Furthermore, 'Homomorphic Encryption' is identified as a potential strategy to protecting user privacy while retaining data usefulness based on our review of privacy preservation strategies. A more secure and privacyaware IoT environment may be fostered thanks to the findings of this study, which have ramifications for the industry, government, consumers, and academics. Addressing the ever-evolving security and privacy issues in the IoT will need a future focus on cutting-edge security mechanisms, privacy-preserving technology, regulatory compliance, user-centric design, multidisciplinary cooperation, and threat intelligence sharing. 2024 IEEE. -
Security Aspects for Mutation Testing in Mobile Applications
Due to the increase in the number of Android Platform Devices, there are more and more applications being developed across various domains. It is interesting to see the involvement of bugs/crashes even in the deployed applications even though it has been through various test phases. Unit tests are essential in a well-trusted testing environment; however, it does not guarantee that the range of test caries every component of the application. This writes up discusses the overview of mutation testing method concerning Android Applications. Even though mutation testing is found out to be very effective in other applications, it is not that easy to implement the same for an Android Developed Application because of additional resources it would hold. Further, various measures for mutation testing are discussed with types of mutant operators, tools etc. The current studies of mutation analysis mainly focus on testing all the functionalities irrespective of the resource usage. However, the target of the future mutation tests must be also to evaluate the efficiency of the applications under the same test cases. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Security Intensification using Blockchain coupled with Internet of Things: Proposal, Challenges and Anatomization
Internet of things is an important part of our day-to-day life where all things are connected in the network with the internet. The number of devices linked to the network grows steadily each day in recent years. The innovation in the manufacturing industry also the reason for the production of different devices that uses various technologies to make a possible connection between the devices. Even though the Internet of Things has been developing and demonstrating its potential in recent years, its security when connected to the internet is in doubt. Blockchain is a disruptive technology that provides security to their network without tampering with the data in the network. Researchers and experts have recommended using the blockchain to address security vulnerabilities in the Internet of Things. In this paper, we have analyzed some of the issues which are occurring while integrating blockchain into the Internet of things. The major issues were discussed and which will be helpful to move towards the research direction to solve those problems. 2022 IEEE. -
Segment Anything Model (SAM) to Segment lymphocyte from Blood Smear Images
Automated lymphocyte segmentation from smear images plays an important role in disease diagnosis and monitoring, aiding in the assessment of immune system function and pathology detection. This study proposes an approach for lymphocyte segmentation utilizing Segment Anything Model (SAM) which is a deep learning model. Our method leverages a pre trained SAM architecture and fine-tunes it on a custom dataset comprising smear images containing lymphocytes. The pretrained model's ability of versatile segmentation combined with fine-tuning on the specific dataset enhances its performance in accurately identifying lymphocyte boundaries. We evaluate the proposed approach on a diverse set of smear images, demonstrating its effectiveness in segmenting lymphocytes with impressive IOU score and Dice Score. SAM deep learning model, fine-tuned on custom datasets, holds promise for robust and efficient lymphocyte segmentation from blood smear images. 2024 IEEE. -
Segmentation and Recognition of E. coli Bacteria Cell in Digital Microscopic Images Based on Enhanced Particle Filtering Framework
Image processing and pattern recognitions play an important role in biomedical image analysis. Using these techniques, one can aid biomedical experts to identify the microbial particles in electron microscopy images. So far, many algorithms and methods are proposed in the state-of-the-art literature. But still, the exact identification of region of interest in biomedical image is a research topic. In this paper, E. coli bacteria particle segmentation and classification is proposed. For the current research work, the hybrid algorithm is developed based on sequential importance sampling (SIS) framework, particle filtering, and Chan–Vese level set method. The proposed research work produces 95.50% of average classification accuracy. 2019, Springer Nature Singapore Pte Ltd. -
Segmentation of ancient and historical gilgit manuscripts
The Gilgit manuscripts belong to fifth century A.D. and are oeuvre of texts which deal with Buddhist work. It is one of the oldest manuscripts in the world and is considered to be a milestone in the history of Buddhist works in India. It is a collection of both official and unofficial Buddhist works which are believed to have helped in the evolution of many literatures including Chinese, Japanese, and Sanskrit. Since this manuscript is almost seventeen centuries old it has not been able to fully decipher the text yet. It has been laminated by the National Archives of India which proves it is one of the most important literatures concerning India. In this paper, we perform character- based image segmentation on Gilgit manuscript in order to simplify and to better identify character in the image of the manuscript. The employed method gives an accuracy of nearly 87%. Springer India 2016. -
Segmentation technique for medical image processing: A survey
Segmentation is one of the popular and efficient technique in context to medical image analysis. The purpose of the segmentation is to clearly extract the Region of Interest from the medical images. The main focus of this paper is to review and summarize an efficient segmentation method. While doing the comparison study on segmentation methods using the Support Vector Machine, K-Nearest Neighbors, Random Forest and the Convolutional Neural Network for medical image analysis identifies that Convolutional Neural Network works efficiently for doing in-depth analysis. The Convolutional Neural Network can be used as segmentation technique for achieving the high accuracy on medical image analysis. 2017 IEEE.