A Novel Blockchain-based Trust Model for Cloud Identity Management

Secure and reliable management of identities has become one of the greatest challenges facing cloud computing today, mainly due to the huge number of new cloud-based applications generated by this model, which means more user accounts, passwords, and personal information to provision, monitor, and secure. Currently, identity federation is the most useful solution to overcome the aforementioned issues and simplify the user experience by allowing efficient authentication mechanisms and use of identity information from data distributed across multiple domains. However, this approach creates considerable complexity in managing trust relationships for both the cloud service providers and their clients. Poor management of trust in federated identity management systems brings with it many security, privacy and interoperability issues, which contributes to the reluctance of organizations to move their critical identity data to the cloud. In this paper, we aim to address these issues by introducing a novel trust and identity management model based on the Blockchain for cloud identity management with security and privacy improvements

Privacy and Security for Smart Metering System with Fault Controlling Technique

Smart Metering (SM) is an important and essential element of the upcoming energy network. The importance of smart metering is that it interconnects smart grid elements and functions among a two way communication network. The target is to support an economically efficient sustainable power system with high quality and security. To achieve this objective, advanced smart metering functions might include automated meter readings, distributed energy storage, distributed energy resource management, as well as further energy efficiency mechanisms such as real time optimizations for load shifting and scheduling. In existing system the information transmission security, privacy, meter reading observation between network and client then data transmission monitoring system which can be controlled through Wireless Area Network (WAN). However the information transmission observation system has not economical for fault dominant technique. In proposed system, whole system will be monitored, controlled, data have been secured and also effective load scheduling can be provided for this system too. EB line faults such as short circuit, over voltage and under voltage are monitored and controlled through WAN. It improves the protection and privacy of information transmission between network and client. DOI: 10.17762/ijritcc2321-8169.15037

VisTAS:Blockchain-based Visible and Trusted Remote Authentication System

The information security domain focuses on security needs at all levels in a computing environment in either the Internet of Things, Cloud Computing, Cloud of Things, or any other implementation. Data, devices, services, or applications and communication are required to be protected and provided by information security shields at all levels and in all working states. Remote authentication is required to perform different administrative operations in an information system, and Administrators have full access to the system and may pose insider threats. Superusers and administrators are the most trusted persons in an organisation. “Trust but verify” is an approach to have an eye on the superusers and administrators. Distributed ledger technology (Blockchain-based data storage) is an immutable data storage scheme and provides a built-in facility to share statistics among peers. Distributed ledgers are proposed to provide visible security and non-repudiation, which securely records administrators’ authentications requests. The presence of security, privacy, and accountability measures establish trust among its stakeholders. Securing information in an electronic data processing system is challenging, i.e., providing services and access control for the resources to only legitimate users. Authentication plays a vital role in systems’ security; therefore, authentication and identity management are the key subjects to provide information security services. The leading cause of information security breaches is the failure of identity management/authentication systems and insider threats. In this regard, visible security measures have more deterrence than other schemes. In this paper, an authentication scheme, “VisTAS,” has been introduced, which provides visible security and trusted authentication services to the tenants and keeps the records in the blockchain

The future of data privacy and security concerns in Internet of things

A global, immersive, invisible, ambient network computing environment built through the continued proliferation of smart sensors, cameras, software, databases,and massive data centers in a world-spanning information fabric known as the Internet of Things. The idea is to live in connected world. Altogether varieties of connected objects from smart home appliances like televisions, laundry machines,thermostats, refrigerators to Industrial Internet of Things (IIoT) and Internet of Medical Things (IoMT) are going to conserve the potential of IoT connectivity in all paces of future smart world. However, it has high importance to preserve adherence of enormous benefits of IoT connectivity, which might lead to unseen security and privacy issues and vulnerabilities that will cause various malicious attacks including waterhole, ransomware, eavesdropping, and others to exploit the potential of smart objects. This paper will present and forecast advanced concepts for end-to end security and privacy issues in a highly distributed, heterogeneous and dynamic network of IoT devices, which may reveal a holistic approach of device identification, authentication, and management, security, and privacy concerns

Secure Distributed Databases Using Cryptography

The computational encryption is used intensively by different databases management systems for ensuring privacy and integrity of information that are physically stored in files. Also, the information is sent over network and is replicated on different distributed systems. It is proved that a satisfying level of security is achieved if the rows and columns of tables are encrypted independently of table or computer that sustains the data. Also, it is very important that the SQL - Structured Query Language query requests and responses to be encrypted over the network connection between the client and databases server. All this techniques and methods must be implemented by the databases administrators, designer and developers in a consistent security policy.databases, encryption, cryptography, digital signature

HadoopSec: Sensitivity-aware Secure Data Placement Strategy for Big Data/Hadoop Platform using Prescriptive Analytics

Hadoop has become one of the key player in offeringdata analytics and data processing support for any organizationthat handles different shades of data management. Consideringthe current security offerings of Hadoop, companies areconcerned of building a single large cluster and onboardingmultiple projects on to the same common Hadoop cluster.Security vulnerability and privacy invasion due to maliciousattackers or inner users are the main argument points in anyHadoop implementation. In particular, various types of securityvulnerability occur due to the mode of data placement in HadoopCluster. When sensitive information is accessed by anunauthorized user or misused by an authorized person, they cancompromise privacy. In this paper, we intend to address theapproach of data placement across distributed DataNodes in asecure way by considering the sensitivity and security of theunderlying data. Our data placement strategy aims to adaptivelydistribute the data across the cluster using advanced machinelearning techniques to realize a more secured data/infrastructure.The data placement strategy discussed in this paper is highlyextensible and scalable to suit different sort of sensitivity/securityrequirements

HadoopSec: Sensitivity-aware Secure Data Placement Strategy for Big Data/Hadoop Platform using Prescriptive Analytics

Hadoop has become one of the key player in offeringdata analytics and data processing support for any organizationthat handles different shades of data management. Consideringthe current security offerings of Hadoop, companies areconcerned of building a single large cluster and onboardingmultiple projects on to the same common Hadoop cluster.Security vulnerability and privacy invasion due to maliciousattackers or inner users are the main argument points in anyHadoop implementation. In particular, various types of securityvulnerability occur due to the mode of data placement in HadoopCluster. When sensitive information is accessed by anunauthorized user or misused by an authorized person, they cancompromise privacy. In this paper, we intend to address theapproach of data placement across distributed DataNodes in asecure way by considering the sensitivity and security of theunderlying data. Our data placement strategy aims to adaptivelydistribute the data across the cluster using advanced machinelearning techniques to realize a more secured data/infrastructure.The data placement strategy discussed in this paper is highlyextensible and scalable to suit different sort of sensitivity/securityrequirements