Technological hardening. Nowadays almost every operating computer is connected to a network, which means that it is constantly exposed to new threats and external attacks. In order to prevent and fight these attacks, systems must be technologically prepared. Many of them already offer security features to limit outside access, but even with these features in place, systems are still getting compromised, therefore they also have to be hardened in order to minimize these security vulnerabilities. Technological hardening consists of protecting sensitive data from internal and external threats by eliminating as many security risks that may affect the system as possible, always minimizing the risk of a successful attack. Xxxxx Xxxxxxxx mentioned in one of his articles “Security is a process, not a product” [219]. Therefore, the process of eliminating these risks includes the removal of non-essential programs as well as the use of different techniques to prevent and/or mitigate threats that represent system vulnerabilities. Products can be implemented and be part of the process, but an effective security system is always based on a process or methodology. So far, most of the security processes are reactive and they aim to detect and mitigate attacks, but new technologies are designed to be proactive and not just detect and mitigate but also prevent attacks by setting up the necessary measures. Some of these techniques for hardening systems are Big Data, predictive analytics or data shadow analysis among others. Big Data: This technology and its style analysis can be the answer for detecting and preventing advanced persistent threats. These techniques could play a key role in helping detect threats at an early stage, using a more sophisticated analysis pattern, and combining and analysing multiple data sources. Big data also provide the possibility of identifying anomalies by using feature extraction. Today, security logs are often ignored unless an incident occurs and the red flag is raised. Big Data provides the opportunity to consolidate and analyse logs automatically from multiple sources rather than in isolation. This could provide insight that individual logs cannot, and potentially enhance Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) through continual adjustment and effectively learning “good” and “bad” behaviours. Integrating information from physical security systems, such as building access controls and even CCTV, could also significantly enhance I...
