# Prospects of Cybersecurity in Smart Cities
## 2 Literature Review
### Security Risks in Smart Cities
This involves following the best security practices, conducting risk assessments, and implementing appropriate security controls [57; 58]. Protecting data privacy is another area of concern in smart cities' environments. Smart cities generate massive amounts of data from sensors, surveillance systems, and connected devices. These data often contain sensitive information about individuals, including their locations, behaviors, and personal preferences. Data encryption is a fundamental technique used to secure data in transit and at rest. In smart cities, sensitive data such as personal information, financial records, and surveillance footage should be encrypted to prevent unauthorized access or interception by malicious actors [59]. The importance of data minimization and anonymization is associated with the appearance of data encryption. [PERSON] et al. [60] recommend that smart cities should practice data minimization, collecting only the necessary data to fulfill their functions and reducing the risk associated with storing excessive personal information. Furthermore, smart cities must implement robust access controls to restrict access to sensitive systems and data. This involves implementing secure authentication mechanisms such as multi-factor authentication and role-based access control (RBAC) to ensure that only authorized individuals can access specific data [61]. Additionally, smart cities must incorporate secure communication mechanisms. Communication between devices and systems within a smart city's infrastructure should be secured to prevent eavesdropping or tampering. In the review work carried out by [PERSON] et al. [62] it is highlighted that the adoption of secure protocols like Transport Layer Security (TLS) and Virtual Private Networks (VPNs) can ensure encrypted and authenticated communication channels. These proposals are relevant to the approach of our study, which identifies cybersecurity challenges related to network vulnerabilities related to unauthorized access and interception of communications. IoT devices are the backbone of smart cities, enabling connectivity and data exchange among various systems and devices. However, these devices are often vulnerable to cyber-attacks due to their limited security measures [63]. Consequently, robust cybersecurity practices are needed to secure IoT devices, including implementing secure authentication, encryption, and regular software updates to prevent unauthorized access or control. Several approaches are proposed in the literature to increase the security of IoT devices. Implementing robust authentication mechanisms such as multi-factor authentication (MFA) is proposed by [PERSON] et al. [64] to ensure that only authorized users or devices can access the IoT devices. This helps prevent unauthorized access and protects against brute-force attacks. The adoption of secure communication protocols such as Transport Layer Security (TLS) or Secure Shell (SSH) to encrypt data transmitted between IoT devices and the backend systems is proposed by [PERSON] et al. [65]. This prevents the eavesdropping of and tampering with sensitive information. Regular firmware updates are recommended by [PERSON] et al. [66] to keep the firmware of IoT devices up to date by applying regular security patches and updates provided by the manufacturers. This helps address vulnerabilities and ensures that devices are protected against known security risks. Finally, [PERSON] et al. [67] employ an approach using test data from different datasets to suggest the implementation of network segmentation to isolate IoT devices from other critical infrastructure systems. This way, even if one device is compromised, it will not provide direct access to the entire network, reducing the potential impact of an attack. Our study confirms that IoT security plays a critical role in safeguarding not only the devices and systems connected to the internet, but also the entire digital infrastructure and data ecosystem.