Data-Driven Security for Smart City Systems: Carving a Trail

Abstract

Smart cities rely heavily on collecting and using data. Smart systems are implemented and deployed to provide intelligent features that help improve efficiency and quality of life. This creates a huge repository of data representing many aspects of smart city operations. Many data-driven applications can take advantage of this data to further improve the "smartness" of a smart city. At the same time, smart city systems, being very large-scale distributed systems and highly integrated with the physical infrastructure and residents of the city, pose immense security challenges as well. So why don't we take advantage of this data to improve security measures? In this paper we propose the use of data-driven security approaches to secure smart city systems. To illustrate the significance of this approach we first identify the different challenges for securing smart city systems given the unique characteristics of these systems. Then we discuss the benefits of using data-driven security. Furthermore, we categorize the different types of security applications (features) needed to help capitalize on the data needs and benefits. We also discuss the how these categories of applications can alleviate some of the challenges. In addition, we highlight possible future research directions to incorporate effective data-driven security in smart city systems.

Applications of Integrated IoT-Fog-Cloud Systems to Smart Cities: A Survey

“…Passwords are used to enable the security mechanism in this protocol. Mohamed et al [175] proposed using data-driven security to protect smart city systems such as iIFCs. Guan et al [176] developed an anonymous and privacy-preserving data aggregation technique for IoT-fog environments.…”

“…There are several promising works to secure iIFCs [178][179][180] for different applications. In addition, there is other emerging effort to develop some security approaches for IoT and fog applications in smart cities [175,[181][182][183]. Nevertheless, there is still the requirement to further improve and upgrade these security and privacy approaches and include them in development platforms.…”

Challenges in IoT Technology Adoption into Information System Security Management of Smart Cities: A Review

“…Furthermore, there are also weaknesses in the data relocation, physical effects of cyber-attacks, huge volumes of data gathering and storage using cloud technology, and manipulation of data by hackers. [4,5,17] System Integration Integration of multiple applications with different datasets poses threats to the cyber vulnerabilities. Poor integration structure and rigid ICT infrastructure to handle multiple data types impact access to emerging technologies, complicates technology acquisition and relocation.…”

“…Data-driven decisionmaking is a process that involves the collection of data based on established concrete objectives and the discovery of evidence, trends, associations, observations, and knowledge from this information. This expertise is then used to build or evaluate processes, operations, structures, policies, and techniques to support the data/system owner [5]. Information monitoring includes multi-device collaboration, which can effectively improve the accuracy and reliability of user-acquired information without fail.…”

“…This creates an immense data repository representing several aspects of SC operational activities. The SC services are based on a centralized architecture, where a complex and heterogeneous set of devices embedded over the urban area generates different-centralized architecture data types that are then delivered to a control center through appropriate communication technologies, where data storage and processing are implemented [5]. An SC is a complex system, which means that any security concern could impact the protection of its citizens valuable information [4].…”