A Survey on Attacks and Defences on LoRaWAN Gateways

LoRaWAN (long-range wide-area network) is an emerging technology for the connection of internet of things (IoT) devices to the internet and can as such be an important part of decision support systems. In this technology, IoT devices are connected to the internet through gateways by using long-range radio signals. However, because LoRaWAN is an open network, anyone has the ability to connect an end device or set up a gateway. Thus, it is important that gateways are designed in such a way that their ability to be used maliciously is limited. This chapter covers relevant attacks against gateways and potential countermeasures against them. A number of different attacks were found in literature, including radio jamming, eavesdropping, replay attacks, and attacks against the implementation of what is called beacons in LoRaWAN. Countermeasures against these attacks are discussed, and a suggestion to improve the security of LoRaWAN is also included.

Cloud-Based Big Data Analysis Tools and Techniques Towards Sustainable Smart City Services

Cloud computing and big data analytics are the key parts of smart city development that can create reliable, secure, healthier, more informed communities while producing tremendous data to the public and private sectors. Since the various sectors of smart cities generate enormous amounts of streaming data from sensors and other devices, storing and analyzing this huge real-time data typically entail significant computing capacity. Most smart city solutions use a combination of core technologies such as computing, storage, databases, data warehouses, and advanced technologies such as analytics on big data, real-time streaming data, artificial intelligence, machine learning, and the internet of things (IoT). This chapter presents a theoretical and experimental perspective on the smart city services such as smart healthcare, water management, education, transportation and traffic management, and smart grid that are offered using big data management and cloud-based analytics services.

Early Detection and Recovery Measures for Smart Grid Cyber-Resilience

The internet of things (IoT) has recently brought major technological advances in many domains, including the smart grid. Despite the simplicity and efficiency that IoT brings, there are also underlying risks that are slowing down its adoption. These risks are caused by the presence of legacy systems inside existing infrastructures that were built with no security in mind. In this chapter, the authors propose a method for early-stage detection of cyber-security incidents and protection against them through applicable security measures. This chapter introduces security techniques such as anomaly detection, threat investigation through a highly automated decision support system (DSS), as well as incident response and recovery for smart grid systems. The introduced framework can be applied to industrial environments such as cyber-threats targeting the production generator as well as the electricity smart meters, etc. The chapter also illustrates the framework's cyber-resilience against zero-day threats and its ability to distinguish between operational failures as well as cyber-security incidents.

Body Motion Capture and Applications

The motion capture (MoCap) is a highly popular subject with wide applications in different areas such as animations, situational awareness, and healthcare. An overview of MoCap utilizing different sensors and technologies is presented, and the prominent MoCap methods using inertial measurement units and optics are discussed in terms of their advantages and disadvantages. MoCap with wearable inertial measurement units is analyzed and presented specifically with the background information and methods. The chapter puts an emphasis on the mathematical model and artificial intelligence algorithms developed for the MoCap. Both the products from the important technology developers and the proof-of-concept applications conducted by Havelsan are presented within this chapter to involve an industrial perspective. MoCap system will act as a decision support system in either application by providing automatic calculation of metrics or classification, which are the basic tools for decision making.

A Review of Wireless Positioning From Past and Current to Emerging Technologies

Many techniques for wireless positioning have existed for years, but with emerging technologies like 5G and ultra wideband, wireless positioning is becoming more accurate than ever. On the one hand, improved accuracy implies increased usefulness. It will open up new application areas and lead to advances in areas like internet of things (IoT), self-driving cars, and contact tracing. Furthermore, decision support systems can benefit from better positioning techniques. On the other hand, the ability to track connected devices with sub-meter precision brings some privacy and security concerns. This chapter aims to review indoor and outdoor positioning technologies and how they can be used for contact tracing. It then further discusses some of the data management, privacy, and security concerns that follow. To that end, this chapter studies the main techniques for wireless positioning, cellular-based positioning using 5G, and their use to contact tracing. Finally, the authors provide some insight into how 5G and UWB might help the area of positioning and contact tracking in the future.

Services in Connected Vehicles

Smart vehicles have introduced many services which can be categorized by their functionality (infotainment, comfort, ADAS, OEM services). Introducing new services increases the risk of compromising security. A mobile app used by drivers to connect the vehicle could be infected with malware and spread to the vehicle. Forging remote starting signals enables an attacker to start the vehicle without a key. Security implications of these services should be investigated and addressed thoroughly. This chapter investigates such problems and provides an overview of vulnerabilities, attacks, and mitigations related to these services along with findings including software bugs and insecure protocols. The mitigations for these attacks include strengthening the security protocol of the vehicle CAN bus and incorporating security protocols such as TLS and IPsec. It is hard to say that all connected vehicles are secured. In conclusion, security cannot be neglected, and best practices like sufficient logging (e.g., IDS), reviewing, security testing, and updating of software and hardware should be used.

Decision Making in IoT Systems Based on Guided Self-Organization and Autonomic Computing in the Context of the I4.0 Era

Internet of things (IoT) systems are taking an important role in daily life. Each year the number of connected devices increases considerably, and it is important to keep systems working appropriately. There are some options related to decision support systems to perform IoT systems tasks such as deployment, maintenance, and its operation on environments full of different connected devices and IoT systems interacting among them. For the decision-making process, the authors consider the complexity nature observed in IoT systems and their operational context and environments. In this sense, rather than using grain and fixed control rules/laws for the system design, the use of general principles, goals, and objectives are defined to guide the system adaptation. This has been referred to as guided self-organization (GSO) in the literature. The GSO design approach is based in evaluating the system entropy to reduce the emergence and enable self-organization. Also, in this chapter, a series of study cases from different IoT application domains are presented.

Implications of Cybersecurity Breaches in LPWANs

With the contrast of limited performance and big responsibility of IoT devices, potential security breaches can have serious impacts in means of safety and privacy. Potential consequences of attacks on IoT devices could be leakage of individuals daily habits and political decisions being influenced. While the consequences might not be avoidable in their entirety, adequate knowledge is a fundamental part of realizing the importance of IoT security and during the assessment of damages following a breach. This chapter will focus on two low-powered wide area network (LPWAN) technologies, narrow-band iot (NB-IoT) and long-range wide area network (LoRaWAN). Further, three use cases will be considered—healthcare, smart cities, and industry—which all to some degree rely on IoT devices. It is shown that with enough knowledge of possible attacks and their corresponding implications, more secure IoT systems can be developed.

A Case Study of Decision Support System and Warehouse Management System Integration

A warehouse is an indispensable part of the logistics. A warehouse management system (WMS) is designed to improve efficiency in warehouses to increase their throughput and potential. The rise of IoT and its commercialization enabled ‘smart things' to be widely adopted by hobbyists and companies. Cheap sensors and smart devices triggered better automation opportunities. Many devices and sensors that are being deployed in the industry and warehousing are affected by this trend. A well-designed WMS is needed to connect devices and humans in a heterogenous warehouse environment. This chapter introduces a prototype of a WMS powered by a decision support system (DSS) based on real-life requirements. In order to have fast, reliable, and efficient decision making in warehousing, the importance of employing DSS in the WMS is emphasized. Warehouse-related IoT technology is briefly introduced, and its security considerations are discussed thoroughly. The main contribution of this chapter is to show how warehouse operations can be modeled in business process model notation and executed in a DSS.

Security of In-Vehicle Communication Systems

The automotive industry has seen remarkable growth in the use of network and communication technology. These technologies can be vulnerable to attacks. Several examples of confirmed attacks have been documented in academic studies, and many vehicular communications systems have been designed without security aspects in mind. Furthermore, all the security implications mentioned here would affect the functionality of decision support systems (DSS) of IoT and vehicular networks. This chapter focuses on in-vehicle security and aims to categorize some attacks in this field according to the exploited vulnerability by showing common patterns. The conclusion suggests that an ethernet-based architecture could be a good architecture for future vehicular systems; it enables them to meet future security needs while still allowing network communication with outside systems.