Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
Browse
12 results
Search Results
Item Restraining add-on's behavior in private browsing(2012) Bapat, A.D.; Pais, A.R.In this paper we address the privacy issues of add-on mechanism supported by browser in private mode. The add-ons enjoy unrestrained access to user sensitive information at all times. This freedom can be misused to create add-ons with malicious intent of violating privacy of the browser. We have designed and implemented an add-on which performs this task in private mode of the browser. This is a clear violation of the goals of private browsing. Mozilla lacks privacy ensuring mechanism against add-ons at browser level. So we have modified the source code of Mozilla Firefox to prevent such behavior of an add-on. It involves runtime monitoring of add-on?s behavior in private mode and notify/block suspicious ones. We have been able to prevent such add-on?s activity using our mechanism. Copyright 2012 ACM.Item Privacy and trust in cloud database using threshold-based secret sharing(2013) Dutta, R.; Annappa, B.In today's cloud computing scenario, privacy of data and trust on the service provider have become a major issue and concern. Achieving trust and preserving the privacy of data stored in third-party cloud databases has emerged as a key research area. To achieve this, several different techniques have been proposed based on cryptography, auditing by a third party, etc. Secret sharing schemes have also been considered to address these issues of trust and privacy in databases by various researchers. In this paper, we propose a technique of using a well-known threshold-based visual secret sharing scheme to address the issue of privacy and trust in cloud databases and database-as-a-service offerings. We consider data records with at least one prime attribute and propose an indexing technique for the secret shares of records in a large database based on some properties of the secret sharing technique. Our technique is aimed at minimizing storage overhead of secret shares as well as high speed upload and retrieval of data. We discuss the results obtained from our implementation. Our implementation using Hadoop Distributed File System (HDFS) with Matlab shows that this technique minimizes storage overhead due to secret shares and ensures high speed data upload and retrieval. © 2013 IEEE.Item Hierarchical homomorphic encryption based privacy preserving distributed association rule mining(Institute of Electrical and Electronics Engineers Inc., 2014) Rana, S.; Santhi Thilagam, P.Privacy is an important issue in the field of distributed association rule mining, where multiple parties collaborate to perform mining on the collective data. The parties do not want to reveal sensitive data to other parties. Most of the existing techniques for privacy preserving distributed association rule mining suffer from weak privacy guarantees and have a high computational cost involved. We propose a novel privacy preserving distributed association rule mining scheme based on Paillier additive homomorphic cryptosystem. The experimental results demonstrate that the proposed scheme is more efficient and scalable compared to the existing techniques based on homomorphic encryption. © 2014 IEEE.Item A Privacy Preserved Data Mining Approach Based on k-Partite Graph Theory(Elsevier, 2015) Bhat, T.P.; Karthik, C.; Chandrasekaran, K.Traditional approaches to data mining may perform well on extraction of information necessary to build a classification rule useful for further categorisation in supervised classification learning problems. However most of the approaches require fail to hide the identity of the subject to whom the data pertains to, and this can cause a big privacy breach. This document addresses this issue by the use of a graph theoretical approach based on k-partitioning of graphs, which paves way to creation of a complex decision tree classifier, organised in a prioritised hierarchy. Experimental results and analytical treatment to justify the correctness of the approach are also included. © 2015 The Authors.Item An efficient framework and access control scheme for cloud health care(Institute of Electrical and Electronics Engineers Inc., 2016) Saravana, N.; Rajya Lakshmi, G.V.; Annappa, B.Cloud computing is being a potential role in providing services for utilizing a huge data in various application, as it is ubiquitous. In emerging growth of Cloud services been focused on security issues and optimal data storage used by consumers. Eventually, the Cloud storage is the best way to keep essential business data secure and accessible. Along with that, there are few important feature been considered. i.e( file versioning, automatic sync,collaboration tools, security File Encryption). In our research article, the framework is designed for real-time Healthcare business application to be achieved all the essential features with Inter-Cloud data storage.To do additionally, has been implemented and tested by an efficient CP-ABE (Cipher Policy-Attribute Based Encryption) algorithm for secure data transmission. Outcomes were powerful in a such way that can be promised in a designed framework developed in Python 3 in Charm-Cryptography. © 2015 IEEE.Item Generating Privacy-Preserved Recommendation Using Homomorphic Authenticated Encryption(Institute of Electrical and Electronics Engineers Inc., 2017) Shanu, P.K.; Chandrasekaran, K.Online service providers started to providepersonalized recommendation to the users by collecting userprivate sensitive data. Traditionally the user private data isencrypted using a symmetric encryption algorithm beforestoring it in the cloud to provide another layer of security fordata at rest. It makes users' data secure from third parties, butnot the service provider. We propose a method that generatesrecommendations using homomorphically encrypted data in aprivacy preserved manner to provide protection against serviceprovider. We also verify the correctness of computations doneby a third parties and the service provider over encrypteddata using homomorphic authenticators and some securecryptographic protocols. © 2016 IEEE.Item An enhanced secure authentication scheme with user anonymity in mobile cloud computing(Institute of Electrical and Electronics Engineers Inc., 2017) Madhusudhan, R.; Suvidha, K.S.With the rapid growth and development in cloud computing and mobility, mobile cloud computing has emerged and becomes the trend of future generation computing paradigm. Cloud offers infrastructure, platform and software services to mobile users through mobile network. The key issues in mobile cloud computing are security and privacy. While analysing security and privacy issues in mobile cloud computing, three aspects should be considered they are: mobile terminal, mobile network and the cloud. To address the key issues in mobile cloud computing, we proposed an authentication scheme which will provide security to the messages exchanged between mobile user and the cloud server. Lee at al. have proposed authentication scheme for roaming service in global mobility networks in 2016. In this paper we have reviewed Lee et al.'s scheme and proved that their scheme is vulnerable to replay attack, man in the middle attack and impersonation attack. Moreover their scheme fails to preserve user anonymity, provides no local password verification and could not achieve perfect forward secrecy. Hence an enhanced secure authentication scheme with user anonymity in mobile cloud computing is proposed. Furthermore, the security analysis of the proposed scheme is also presented in this paper. © 2017 IEEE.Item Attacks on Android-Based Smartphones and Impact of Vendor Customization on Android OS Security(Springer Science and Business Media Deutschland GmbH, 2020) Kumar, S.; Kittur, L.J.; Pais, A.R.Smartphones are ubiquitous today, and they contain a large amount of personal and sensitive information. It is, therefore, essential to secure the underlying operating system. Android is the dominant operating system among the smartphone market; therefore, it is critical to uphold the security standards of Android. Android smartphone manufacturers and third-party custom ROM developers modify the operating system heavily to differentiate themselves among the competitors. The modifications done by the Smartphone manufacturers and third-party custom ROM developers posses a threat to the smartphone user’s privacy and make the Android OS vulnerable to advanced persistent threat (APT) attacks. This paper demonstrates that Smartphone manufacturers and third-party custom ROM developers can bypass Android’s security mechanisms and breach the user’s privacy without getting detected by the user by modifying parts of Android OS except for the kernel. In particular, this paper shows methods by which APT attacks can be performed on the Android 10’s Camera subsystem to capture pictures from the camera and upload them to a remote server without the user’s knowledge. © 2020, Springer Nature Switzerland AG.Item Towards a Federated Learning Approach for NLP Applications(Springer Science and Business Media Deutschland GmbH, 2021) Prabhu, O.S.; Gupta, P.K.; Shashank, P.; Chandrasekaran, K.; Divakarla, D.Traditional machine learning involves the collection of training data to a centralized location. This collected data is prone to misuse and data breach. Federated learning is a promising solution for reducing the possibility of misusing sensitive user data in machine learning systems. In recent years, there has been an increase in the adoption of federated learning in healthcare applications. On the other hand, personal data such as text messages and emails also contain highly sensitive data, typically used in natural language processing (NLP) applications. In this paper, we investigate the adoption of federated learning approach in the domain of NLP requiring sensitive data. For this purpose, we have developed a federated learning infrastructure that performs training on remote devices without the need to share data. We demonstrate the usability of this infrastructure for NLP by focusing on sentiment analysis. The results show that the federated learning approach trained a model with comparable test accuracy to the centralized approach. Therefore, federated learning is a viable alternative for developing NLP models to preserve the privacy of data. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Recent Advancements and Challenges in FinTech(Institute of Electrical and Electronics Engineers Inc., 2023) Girish, K.K.; Bhowmik, B.The rapid advancement of technology in recent years has brought about numerous changes in various industries, and the financial sector is no exception. The rise of financial technology (FinTech) has disrupted traditional banking and financial services by offering more convenient, accessible, and personalized services to customers. Contrarily, financial services have become more efficient, cost-effective, and secure with FinTech, enabling people to manage their finances with just a few clicks, even on their smartphones. FinTech has also created new opportunities for financial inclusion, making it possible for people who were previously unbanked or underbanked to access financial services. Despite its many benefits, the rise of FinTech has also brought about several challenges. This paper gives an overview of FinTech, its progress, and its importance. Following this, significant challenges of FinTech are highlighted to ensure its long-term success and continued growth. The recent literature shows the way how it is transforming our perceptions. © 2023 IEEE.