Biblio

This paper proposes an intelligent functional architecture for an advanced launch site system that is composed of five parts: the intelligent technical area, the intelligent launching region, the intelligent flight and landing area, the intelligent command and control system, and the intelligent analysis assessment system. The five parts consist of the infrastructure, facilities, equipment, hardware and software and thus include the whole mission processes of ground and launch systems from flight articles' entry to launch. The architectural framework is designed for the intelligent elements of the parts. The framework is also defined as the interrelationship and the interface of the elements, including the launch vehicle and flight payloads. Based on the Internet of Things (IoT), the framework is integrated on four levels: the physical layer, the perception layer, the network layer, and the application layer. The physical layer includes the physical objects and actuators of the launch site. The perception layer consists of the sensors and data processing system. The network layer supplies the access gateways and backbone network. The application layer serves application systems through the middleware platform. The core of the intelligent system is the controller of the automatic control system crossing the four layers. This study builds the models of the IoT, cloud platform, middleware, integrated access gateway, and automatic control system for actual ground and launch systems. A formal approach describes and defines the architecture, models and autonomous control flows in the paper. The defined models describe the physical objects, intelligent elements, interface relations, status transformation functions, etc. The test operation and launch processes are connected with the intelligent system model. This study has been applied to an individual mission project and achieved good results. The architecture and the models of this study regulate the relationship between the elements of the intelligent system. The study lays a foundation for the architectural construction, the simulation and the verification of the intelligent systems at the launch site.

The internet-of-things (IoT) consists of embedded devices and their networks of communication as they form decentralized frameworks of ubiquitous computing services. Within such decentralized systems the potential for malicious actors to impact the system is significant, with far-reaching consequences. Hence this work addresses the challenge of providing IoT systems engineers with a framework to elicit privacy and security design considerations, specifically for indoor adaptive smart environments. It introduces a new ambient intelligence indoor adaptive environment framework (CORE) which leverages multiple forms of data, and aims to elicit the privacy and security needs of this representative system. This contributes both a new adaptive IoT framework, but also an approach to systematically derive privacy and security design requirements via a combined and modified OCTAVE-Allegro and Privacy-by-Design methodology. This process also informs the future developments and evaluations of the CORE system, toward engineering more secure and private IoT systems.

As most of the modern encryption algorithms are broken fully/partially, the world of information security looks in new directions to protect the data it transmits. The concept of using DNA computing in the fields of cryptography has been identified as a possible technology that may bring forward a new hope for hybrid and unbreakable algorithms. Currently, several DNA computing algorithms are proposed for cryptography, cryptanalysis and steganography problems, and they are proven to be very powerful in these areas. This paper gives an architectural framework for encryption & Generation of digital signature using DNA Cryptography. To analyze the performance; the original plaintext size and the key size; together with the encryption and decryption time are examined also the experiments on plaintext with different contents are performed to test the robustness of the program.