Detecting IoT Attacks Using an Ensemble Machine Learning Model

Malicious attacks are becoming more prevalent due to the growing use of Internet of Things (IoT) devices in homes, offices, transportation, healthcare, and other locations. By incorporating fog computing into IoT, attacks can be detected in a short amount of time, as the distance between IoT devices and fog devices is smaller than the distance between IoT devices and the cloud. Machine learning is frequently used for the detection of attacks due to the huge amount of data available from IoT devices. However, the problem is that fog devices may not have enough resources, such as processing power and memory, to detect attacks in a timely manner. This paper proposes an approach to offload the machine learning model selection task to the cloud and the real-time prediction task to the fog nodes. Using the proposed method, based on historical data, an ensemble machine learning model is built in the cloud, followed by the real-time detection of attacks on fog nodes. The proposed approach is tested using the NSL-KDD dataset. The results show the effectiveness of the proposed approach in terms of several performance measures, such as execution time, precision, recall, accuracy, and ROC (receiver operating characteristic) curve

The adoption of open sources within higher education in Europe : a dissemination case study

For some time now, the open-source (OS) phenomenon has been making its presence felt; disrupting the economics of the software industry and, by proxy, the business of education. A combination of the financial pressure Higher Education Institutions (HEIs) find themselves under and the increasing focus on the use of technology to enhance students' learning have encouraged many HEIs to look towards alternative approaches to teaching and learning. Meanwhile, the "OS" has challenged assumptions about how intellectual products are created and protected and has greatly increased the quantity and arguably the quality of educational technologies available to HEIs

Cisco networking: using Skype and Netlab+ for distance practical learning

Delivering a 'hands on' ICT practical lesson online offers vocationally based courses an increased presence in a learning sphere otherwise dominated by remote learning, exercise and material based courses. This paper explores work within the UK Open University to deliver collaborative learning with Cisco Systems, the technological pitfalls and how these are being overcome by the use of Skype', Messenger and Netlab+�

The Dark Side(-Channel) of Mobile Devices: A Survey on Network Traffic Analysis

In recent years, mobile devices (e.g., smartphones and tablets) have met an increasing commercial success and have become a fundamental element of the everyday life for billions of people all around the world. Mobile devices are used not only for traditional communication activities (e.g., voice calls and messages) but also for more advanced tasks made possible by an enormous amount of multi-purpose applications (e.g., finance, gaming, and shopping). As a result, those devices generate a significant network traffic (a consistent part of the overall Internet traffic). For this reason, the research community has been investigating security and privacy issues that are related to the network traffic generated by mobile devices, which could be analyzed to obtain information useful for a variety of goals (ranging from device security and network optimization, to fine-grained user profiling). In this paper, we review the works that contributed to the state of the art of network traffic analysis targeting mobile devices. In particular, we present a systematic classification of the works in the literature according to three criteria: (i) the goal of the analysis; (ii) the point where the network traffic is captured; and (iii) the targeted mobile platforms. In this survey, we consider points of capturing such as Wi-Fi Access Points, software simulation, and inside real mobile devices or emulators. For the surveyed works, we review and compare analysis techniques, validation methods, and achieved results. We also discuss possible countermeasures, challenges and possible directions for future research on mobile traffic analysis and other emerging domains (e.g., Internet of Things). We believe our survey will be a reference work for researchers and practitioners in this research field.Comment: 55 page

Implementation of Internet based courses in computer information systems at Milwaukee Area Technical College

Includes bibliographical references