Crypto Steganography using linear algebraic equation

Demand of information security is increasing day by day with the exponential growth of Internet. The content of message is kept secret in cryptography, where as steganography message is embedded into the cover image. In this paper a system is developed in which cryptography and steganography are used as integrated part along with newly developed enhanced security model. In cryptography the process of encryption is carried out using symmetric block ciphers with linear algebraic equation to encrypt a message [1] and the obtained cipher text is hidden in to the cover image which makes the system highly secured. Least Significant Bit (LSB) technique is used for message hiding which replaces the least significant Bits of pixel selected to the hide the information. A large number of commercial steganographic programs use LSB as the method of choice for message hiding in 24-bit,8bit-color images, and gray scale images. It is observed from the simulation study that both methods together enhance security significantly

Computing Symmetric Block Cipher Using Linear Algebraic Equation.

In this paper, a pair of symmetric block ciphers has been developed for encryption and decryption of text file. The characters in the file are represented by the ASCII codes. A substitution table and a reverse substitution table are formed by using a key. The process of encryption and decryption is carried by using linear algebraic equations. However, the cryptanalysis has been discussed for establishing the strength of the algorithm. Result and analysis exhibits that the current algorithm works well and more secured to break the cipher

The internet of things: Insights into the building blocks, component interactions, and architecture layers

This paper deals with the internet of things (IoT) which has become a promising and vibrant technology to build power full smart systems to monitor and analyze various real time operating systems. In recent years a wide range of IoT applications have been developed. To understand the IoT concept, this paper studies the insights into the four building blocks of IoT (Things, Gateways, Network infrastructure, and Cloud infrastructure), three main components of IoT (The Things with Networked Sensors and Actuators, Raw Information and Processed Data Stores, and Analytical and Computing Engines) along with architecture layers (Three Layer, Five Layer, Six Layer, Seven Layer, Cloud, and FOG). The interaction between three components of IoT is also presented. The main contribution of this paper is that it summarizes the IoT, IoT building blocks, components and their interactions along with architecture layers systematically

Smart cities in India: Features, policies, current status, and challenges

Smart cities are the modern urban concepts that are essential for people to have quality life. It is the conceptual view of grouping various technologies to attain smart and sustainable practices. This paper proposes the smart city definitions based on the general approach and the 3-C concept that defines the core character of the smart city. Moreover, this paper also presents a comprehensive study on the smart city concept in the view of India focusing on the features, selection and evaluation criteria, and policies. Besides these, present status, and challenges in the view of smart city in Indian context is also discussed

Analyzing MRI scans to detect glioblastoma tumor using hybrid deep belief networks

Abstract Glioblastoma (GBM) is a stage 4 malignant tumor in which a large portion of tumor cells are reproducing and dividing at any moment. These tumors are life threatening and may result in partial or complete mental and physical disability. In this study, we have proposed a classification model using hybrid deep belief networks (DBN) to classify magnetic resonance imaging (MRI) for GBM tumor. DBN is composed of stacked restricted Boltzmann machines (RBM). DBN often requires a large number of hidden layers that consists of large number of neurons to learn the best features from the raw image data. Hence, computational and space complexity is high and requires a lot of training time. The proposed approach combines DTW with DBN to improve the efficiency of existing DBN model. The results are validated using several statistical parameters. Statistical validation verifies that the combination of DTW and DBN outperformed the other classifiers in terms of training time, space complexity and classification accuracy

Brain MRI Image Classification for Cancer Detection Using Deep Wavelet Autoencoder-Based Deep Neural Network

Technology and the rapid growth in the area of brain imaging technologies have forever made for a pivotal role in analyzing and focusing the new views of brain anatomy and functions. The mechanism of image processing has widespread usage in the area of medical science for improving the early detection and treatment phases. Deep neural networks (DNN), till date, have demonstrated wonderful performance in classification and segmentation task. Carrying this idea into consideration, in this paper, a technique for image compression using a deep wavelet autoencoder (DWA), which blends the basic feature reduction property of autoencoder along with the image decomposition property of wavelet transform is proposed. The combination of both has a tremendous effect on sinking the size of the feature set for enduring further classification task by using DNN. A brain image dataset was taken and the proposed DWA-DNN image classifier was considered. The performance criterion for the DWA-DNN classifier was compared with other existing classifiers such as autoencoder-DNN or DNN, and it was noted that the proposed method outshines the existing methods

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Leveraging Business Performance through Information Systems

The changing economic scenario and competitive corporate culture demands the needs for technology based solutions to various strategic and operational problems. Keeping the pace of growth firms deploy their resources with the aid of information systems, business intelligence, and knowledge Management. In the entire process of executing the value chain IT and IS are of paramount importance. This paper highlights the substantial impact of IS as different levels of the Organization. The authors also reflect the Effectiveness of Value Chain with the influence of IS as a support activity. Keywords: IS, Business Intelligence, Knowledge Management, Value Chai

Blockchain technology for security issues and challenges in IoT

The internet of things (IoT) enabled a common operating picture (COP) across the various applications of modern day living. The COP is achieved through the advancements seen in wireless sensor network devices that were able to communicate through the network thereby exchanging information and performing various analysis. In IoT, the exchange of information and data authentication is only done through the central server there by leading to the security and privacy concerns. Chances of device spoofing, false authentication, less reliability in data sharing could happen. To address such security and privacy concerns, a central server concept is eliminated and blockchain (BC) technology is introduced as a part of IoT. This paper elaborates the possible security and privacy issues considering the component interaction in IoT and studies how the distributed ledger based blockchain (DL-BC) technology contribute to it. Applications of BC with respect to focused sectors and category were clearly studied here. Various challenges specific to IoT and IoT with BC were also discussed to understand blockchain technology contribution