Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Duo: Software Defined Intrusion Tolerant System Using Dual Cluster

An intrusion tolerant system (ITS) is a network security system that is composed of redundant virtual servers that are online only in a short time window, called exposure time. The servers are periodically recovered to their clean state, and any infected servers are refreshed again, so attackers have insufficient time to succeed in breaking into the servers. However, there is a conflicting interest in determining exposure time, short for security and long for performance. In other words, the short exposure time can increase security but requires more servers to run in order to process requests in a timely manner. In this paper, we propose Duo, an ITS incorporated in SDN, which can reduce exposure time without consuming computing resources. In Duo, there are two types of servers: some servers with long exposure time (White server) and others with short exposure time (Gray server). Then, Duo classifies traffic into benign and suspicious with the help of SDN/NFV technology that also allows dynamically forwarding the classified traffic to White and Gray servers, respectively, based on the classification result. By reducing exposure time of a set of servers, Duo can decrease exposure time on average. We have implemented the prototype of Duo and evaluated its performance in a realistic environment

Autonomic computing architecture for SCADA cyber security

Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator

A survey on online monitoring approaches of computer-based systems

This report surveys forms of online data collection that are in current use (as well as being the subject of research to adapt them to changing technology and demands), and can be used as inputs to assessment of dependability and resilience, although they are not primarily meant for this use

Classifying resilience approaches for protecting smart grids against cyber threats

Smart grids (SG) draw the attention of cyber attackers due to their vulnerabilities, which are caused by the usage of heterogeneous communication technologies and their distributed nature. While preventing or detecting cyber attacks is a well-studied field of research, making SG more resilient against such threats is a challenging task. This paper provides a classification of the proposed cyber resilience methods against cyber attacks for SG. This classification includes a set of studies that propose cyber-resilient approaches to protect SG and related cyber-physical systems against unforeseen anomalies or deliberate attacks. Each study is briefly analyzed and is associated with the proper cyber resilience technique which is given by the National Institute of Standards and Technology in the Special Publication 800-160. These techniques are also linked to the different states of the typical resilience curve. Consequently, this paper highlights the most critical challenges for achieving cyber resilience, reveals significant cyber resilience aspects that have not been sufficiently considered yet and, finally, proposes scientific areas that should be further researched in order to enhance the cyber resilience of SG.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. Funding for open access charge: Universidad de Málaga / CBUA

Comparative assessment of the vulnerability and resilience of 10 deltas : work document

Background information about: Nile delta (Egypt), Incomati delta (Mozambique), Ganges-Brahmaputra-Meghna (Bangladesh), Yangtze (China), Ciliwung (Indonesia), Mekong (Vietnam), Rhine-Meuse (The Netherlands), Danube (Romania), California Bay-Delta, Mississippi River Delta (USA

Impact of salinization on rice production and farmers' adaptation preferences: a case in Thua Thien Hue province, Vietnam

Das übergeordnete Ziel dieser Studie ist es, die Auswirkungen des Eindringens von Salzwasser auf den Reisanbau bei unterschiedlichen Salzgehalten zu analysieren und zu untersuchen, wie Veränderungen in den Reissortenoptionen innerhalb der nördlichen zentralen Küstenregion Vietnams dazu beitragen können, diese Auswirkungen zu reduzieren. Auf Böden mit hohem Salzgehalt, die für den Reisanbau nicht mehr geeignet sind, werden geeignetere Anpassungsstrategien gefordert, indem die Präferenz der Landwirte für verschiedene Anbaufolgen und die Faktoren, die ihre Präferenzen im Zusammenspiel mit verschiedenen Salzgehaltsstufen beeinflussen, untersucht werden. Die Studie untersuchte die Auswirkungen des Salzgehalts auf den Mittelwert und die Variabilität der Reiserträge in vier Gemeinden der Provinz und untersuchte mögliche Änderungen im Portfolio der Reissorten, die Erträge zu steigern und gleichzeitig die Ertragsvariabilität zu verringern. Außerdem wurden die Auswirkungen des Salzwassereinbruchs auf die Produktivität und die technische Effizienz der Reisfarmen im Untersuchungsgebiet bewertet. Im Gegensatz zu bestehenden Studien wurden in dieser Untersuchung die Auswirkungen der Bodenversalzung analysiert. Salztolerante Reissorten können die Erträge sichern, solange der Salzgehalt moderat ist, sind aber ungeeignet, sobald der Salzgehalt hoch ist. Dies führte zur Durchführung eines dritten methodischen Ansatzes, der mit Hilfe eines Choice-Experiments Informationen über die Präferenzen und Motivationen der Reisbauern für die Wahl zwischen dem Portfolio der lokal möglichen adaptiven und transformativen Optionen generierte. Die Adoptionsergebnisse der Befragten bei verschiedenen Versalzungsgraden wurden ebenfalls simuliert. Die Ergebnisse zeigen, dass sich der Salzgehalt negativ auf die Reiserträge auswirkt, zu einer Erhöhung der Variabilität der Erträge beiträgt und die technische Effizienz von Reis in Abhängigkeit von den Reissorten verringert.The overall objective of this study is to analyze the impact of saltwater intrusion on rice cultivation at different salinity levels and it also explores how changes in the rice cultivar options within the north central coastal region of Vietnam can help to reduce these impacts. In soils with high salinity levels which are no longer suitable for rice cultivation, more suitable adaptation strategies are called upon through examining farmers’ preference for different crop sequences and the factors affecting their preferences in the interaction with various levels of salinity. The study investigated impacts of salinity on mean and variability of rice yields in four communes of Thua Thien Hue Province and looked at possible changes in the portfolio of rice cultivars, which would offer farmers the potential to increase yields and decrease yield variability simultaneously. I also evaluated the impact of saltwater intrusion on the productivity and technical efficiency of rice farms in the study area. Contrasting to existing studies, this research analyzed season-differentiated impact of soil salinity. Salt tolerant rice varieties can secure yields as long as salinity levels are moderate but are inappropriate once salinity becomes severe. This led to the conduct of third methodological approach that generated information about rice farmers’ preferences and motivations for choosing among the portfolio of locally feasible adaptive and transformative options using a choice experiment. The respondents’ adoption outcomes at different salinity levels were also simulated. The results showed that salinity has negative impact on rice yields, contributes to an increase in variability of yields and reduces rice technical efficiency depending on rice varieties