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International Journal of Advanced Computer Science and Applications(IJACSA), 8(2), 2017 ; People are living in cities and villages based on their profession and their earnings. Those who have better earnings can live their live nicely. However, those who do not have good earnings are facing difficulties to survive their lives even for their basic necessities such as food and clothes. Government and limited charity organizations are trying to help them. In the Kingdom of Saudi Arabia few charity organizations placed few donation boxes around the city to collect donations on donor's ease, but it has become hard for them to monitor them regularly, which affect the donation condition. Involving the Internet of Technology (IoT) will give the donors' comfort and fast way to communicate with the charity, which will make the donation process efficient, easier and in well-organized as well. This paper presents a smart solution which is based on advanced technologies namely; Smart Charity (SC) that will help charity organizations, donators and needy people by involving IoT. SC working mechanism based on two folds, 1)Web-Based Application and 2)Android-based smart Application that will enable donors to donate through their mobiles anywhere and anytime, as well they can suggest the best time for them so the charity organization's representative can visit and collect the desired donations. SC will enable the charity organization to know the location of donors and needy people through GPS as well. In addition, SC introduces Smart Donation Box (SDB) concept by involving IoT, which will have the capability to communicate with charity organizations about its current status such as quarterly, half or fully filled. ; http://thesai.org/Downloads/Volume8No2/Paper_22-Internet_of_Things_IoT_Charity_Automation.pdf

To deliver more value to customers, companies are striving to offer more digital services, and the internet of things (IOT) is the main enabler to maximize such value. However, one of the major challenges companies are facing is digital service integration with other providers, where IoT platform is playing important role to achieve such integration opening door for interoperability within actors in the IoT ecosystem. There have been a little research addressing IoT platforms interoperability from business value perspective, considering technical and non-technical factors as selection criteria to adopt such platforms. This paper uses a case study as a method. To validate the suggested interoperability criteria, interviews were conducted for IoT platform providers and two things providers. It was observed that considering technical factors alone when selecting IoT platform make companies oversee the value technology add to their business as IoT platform is not only about technology but also about business model in which this platform will be operating and the company position and role in IoT ecosystem. The paper contributes by providing criteria to achieve interoperability for IoT platform from both technical and business aspects.

This study deployed desktop research methodology in seeking to understand the cybersecurity challenges confronting Internet of Things (IoT) and the mitigation mechanisms. Objects are no longer independent from each other; rather, connectivity through the power of the internet has connected them. IoT is no longer a new invention or innovation in the technology industry and human lives. The concept is widely used in different industries such as healthcare, food, finance, manufacturing, government, insurance, oil and gas, transportation, postal services, defence, and many more. These industries are using the ability of IoT to function optimally in facilitating different activities. Users of technology devices use IoT devices in homes, offices, and other places to increase productivity and efficiency daily. This article analyses the cybersecurity challenges of IoT and its mitigation mechanisms. The findings identified different cybersecurity challenges confronting IoT and the ways to mitigate them.

The article examines the market for connected objects, which is gradually taking its place in the global economy. Autonomous cars, smartphones, video surveillance, connected objects are already present in our daily lives. However, it is in industry that the Internet of Things has developed the most. The Internet of Things, or IoT, is a concept defining the extension of the Internet to physical objects. This includes not only the connected objects, but also the sensors, software and network through which these objects operate. All connected objects are powered by software, which collects data - that are then processed in the cloud. They are, therefore, programmed and programmable objects that can interact via a WiFi, Bluetooth or 4G connection. Connected objects can be found in two main applications: an industrial application and an everyday application. In the industrial sector, connected objects are very well established in various sectors of activity: automotive, aeronautics, agriculture, health, commerce, public sector, logistics, etc. Everyday applications, known as consumer applications, are struggling to develop despite the announced Eldorado. Even though many connected everyday objects exist (toothbrushes, hoovers, watches, home automation, etc.), the business model is having trouble being set up and connected objects are having trouble proving their usefulness in everyday life. There needs to be consistency and logic in the range of connected products on offer and not just a range of independent products.

International Journal of Advanced Computer Science and Applications(IJACSA), 8(6), 2017 ; Wireless communication networks are highly prone to security threats. The major applications of wireless communication networks are in military, business, healthcare, retail, and transportations. These systems use wired, cellular, or adhoc networks. Wireless sensor networks, actuator networks, and vehicular networks have received a great attention in society and industry. In recent years, the Internet of Things (IoT) has received considerable research attention. The IoT is considered as future of the internet. In future, IoT will play a vital role and will change our living styles, standards, as well as business models. The usage of IoT in different applications is expected to rise rapidly in the coming years. The IoT allows billions of devices, peoples, and services to connect with others and exchange information. Due to the increased usage of IoT devices, the IoT networks are prone to various security attacks. The deployment of efficient security and privacy protocols in IoT networks is extremely needed to ensure confidentiality, authentication, access control, and integrity, among others. In this paper, an extensive comprehensive study on security and privacy issues in IoT networks is provided. ; http://thesai.org/Downloads/Volume8No6/Paper_50-Security_Issues_in_the_Internet_of_Things.pdf

Intro -- Foreword -- Contents -- Emulation Versus Instrumentation for Android Malware Detection -- 1 Introduction -- 2 Background -- 2.1 Static and Dynamic Features -- 2.2 Emulation -- 2.3 Selected Android Malware Research -- 3 Methodology -- 3.1 Datasets -- 3.2 Feature Extraction -- 3.3 Machine Learning Models -- 3.4 Evaluation Metrics -- 4 Experiments and Results -- 4.1 Emulation Versus Instrumentation -- 4.2 Binary Classification Experiments -- 4.3 Multiclass Experiments -- 5 Conclusion and Future Work -- References -- Towards a Generic Approach of Quantifying Evidence Volatility in Resource Constrained Devices -- 1 Introduction -- 2 Related Work -- 3 Volatility in IoT Devices -- 3.1 Data Volatility -- 3.2 A Model for Data Volatility -- 3.3 Information Volatility -- 3.4 Forensic Resources -- 4 A Statistical Approach to Data Volatility -- 4.1 Exponential Distribution -- 4.2 Weibull Distribution -- 4.3 Series and Parallel Systems -- 4.4 Probability Distribution Fitting -- 5 Example: Contiki-NG -- 6 Summary and Conclusions -- References -- Application of Artificial Intelligence and Machine Learning in Producing Actionable Cyber Threat Intelligence -- 1 Introduction -- 2 Cyber Threat Intelligence -- 2.1 Overview of CTI -- 2.2 Types of Threat Intelligence -- 2.3 Benefits of Cyber Threat Intelligence -- 3 Cyber Threat Intelligence Cycle -- 3.1 Planning and Direction -- 3.2 Collection -- 3.3 Processing and Exploitation -- 3.4 Analysis and Production -- 3.5 Dissemination and Integration -- 3.6 Feedback -- 4 Application of Artificial Intelligence and Machine Learning in Producing Actionable CTI -- 5 Discussion -- 6 Conclusion -- References -- Drone Forensics: The Impact and Challenges -- 1 Introduction -- 1.1 Unmanned Aerial Vehicles -- 1.2 Current Threats and Impact of UAVs -- 1.3 Legal Implications -- 1.4 Motivation.