A Design Methodology of an Embedded Motion-Detecting Video Surveillance System

Malaysia urbanization rate has been growing fast due to rapid development and modernization (Economy Planning Unit, 2015) (World Bank, 2015). With the fast growing urban population, the property crimes associated also rises at an alarming rate (United Nations Human Settlements Program, 2007) ( Mohit Mohammad Abdul, Elsawahli H. Mohamed Hassan, 2015) (Ministry of Home Affairs, 2015). Video surveillance system is one of the trusted and efficient security systems to protect people and property against criminal (Varij Ken, 2015). Three problems and issues regarding current video surveillance system are functionality, flexibility and efficiency. The aim of this project is to design and develop an embedded motion detecting video surveillance system and to produce a functioning prototype as the final result to solve these problems. In order to achieve the aim of this project, three objectives are set to be attained. These objectives are to design and develop a motion detection algorithm based on OpenCV library functions using camera as sensor, to process and execute the algorithm using an embedded micro-computer and to compare its processing performance with a PC and to enable wireless user alert using LAN and internet connection. The first objective is achieved as the motion detection algorithm designed and developed based on background subtraction method using camera sensor and openCV library function is proven to functioning well in detecting for motion changes. The algorithm performs successfully both in BeagleBone Black module and PC and is able to deliver outputs required for embedded motion detection video surveillance system. The second objective is achieved as BeagleBone Black (BBB) module, a micro-computer embedded system is used as main processor for the embedded motion-detecting video surveillance system. The BBB module is able to process and execute the motion detection algorithm designed with image processing functions from OpenCV library. The third objective is achieved as embedded motion-detecting video surveillance system is equipped with wireless user alert function using local area network and internet connection. The system is able to send real-time alert to the user via email attached with the image captured and detected as a threat by the syste

Challenges on the interaction of models and policy for pandemic control.

The COVID-19 pandemic has seen infectious disease modelling at the forefront of government decision-making. Models have been widely used throughout the pandemic to estimate pathogen spread and explore the potential impact of different intervention strategies. Infectious disease modellers and policymakers have worked effectively together, but there are many avenues for progress on this interface. In this paper, we identify and discuss seven broad challenges on the interaction of models and policy for pandemic control. We then conclude with suggestions and recommendations for the future

The Huawei and Snowden Questions

This open access book answers two central questions: firstly, is it at all possible to verify electronic equipment procured from untrusted vendors? Secondly, can I build trust into my products in such a way that I support verification by untrusting customers? In separate chapters the book takes readers through the state of the art in fields of computer science that can shed light on these questions. In a concluding chapter it discusses realistic ways forward. In discussions on cyber security, there is a tacit assumption that the manufacturer of equipment will collaborate with the user of the equipment to stop third-party wrongdoers. The Snowden files and recent deliberations on the use of Chinese equipment in the critical infrastructures of western countries have changed this. The discourse in both cases revolves around what malevolent manufacturers can do to harm their own customers, and the importance of the matter is on par with questions of national security. This book is of great interest to ICT and security professionals who need a clear understanding of the two questions posed in the subtitle, and to decision-makers in industry, national bodies and nation states

A Survey and Evaluation of Android-Based Malware Evasion Techniques and Detection Frameworks

Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware. Adversaries are constantly in charge of employing innovative techniques to avoid or prolong malware detection effectively. Past studies have shown that malware detection systems are susceptible to evasion attacks where adversaries can successfully bypass the existing security defenses and deliver the malware to the target system without being detected. The evolution of escape-resistant systems is an open research problem. This paper presents a detailed taxonomy and evaluation of Android-based malware evasion techniques deployed to circumvent malware detection. The study characterizes such evasion techniques into two broad categories, polymorphism and metamorphism, and analyses techniques used for stealth malware detection based on the malware’s unique characteristics. Furthermore, the article also presents a qualitative and systematic comparison of evasion detection frameworks and their detection methodologies for Android-based malware. Finally, the survey discusses open-ended questions and potential future directions for continued research in mobile malware detection