###### Abstract  
The constant increase in volume and wide variety of available Internet of Things (IoT) devices leads to highly diverse software and hardware stacks, which opens new avenues for exploiting previously unknown vulnerabilities. The ensuing risks are amplified by the inherent IoT resource constraints both in terms of performance and energy expenditure. At the same time, IoT devices often generate or collect sensitive, real-time data used in critical application scenarios (e.g., health monitoring, transportation, smart energy, etc.). All these factors combined make IoT networks a primary target and potential victim of malicious actors. In this paper, we presented a brief overview of existing attacks and defense strategies and used this as motivation for proposing an integrated methodology for developing protection mechanisms for smart city IoT networks. The goal of this work was to lay out a theoretical plan and a corresponding pipeline of steps, i.e., a development and implementation process, for the design and application of cybersecurity solutions for urban IoT networks. The end goal of following the proposed process is the deployment and continuous improvement of appropriate IoT security measures in real-world urban IoT infrastructures. The application of the methodology was exemplified on an OMNET++-simulated scenario, which was developed in collaboration with industrial partners and a municipality.  
IoT; smart city; open urban platform; machine learning; cybersecurity; methodology; intrusion detection; toolchain +
Footnote †: journal:  
further IoT adoption and consequently could shut down the wide variety of benefits that the field introduces [1; 2]. With this in mind, some of the most prevalent security challenges in the context of IoT are related to privacy, authentication and authorization, access control, and data storage and processing [1; 2; 3]. These areas are not specific to the IoT domain. However, there is a difference between traditional network security and IoT security. These differences stem from multiple factors such as the following [1]:  
* There are noticeable software and computational resource limitations for IoT devices, which prevents the utilization of more sophisticated security algorithms;
* The IoT devices are low-powered, which restricts the usage of more energy-intensive security best practices and also increases the risk for technical failures (e.g., loss of data);
* The highly heterogenous hardware also leads to the usage of diverse software stacks and different data formats, which increases the available attack surface. Challenges such as these introduce major security risks. Therefore, the goal of this work can be summarized as follows:  
1. Analyze and identify the potential risks and available attacks against IoT- based platforms;
2. Present a comprehensive set of steps and measures that aim at providing improved security and attack prevention for a particular IoT-based platform and the underlying urban data platform--in this case, the UrbanPulse [4] of [iii] [iii] is the abbreviation for Urban Instutute GmbH--this is the industrial partner, with whom the case studies are being investigated and researched).