Threat intelligence helps businesses and organisations make the right decisions in their fight against cyber threats, and strategically design their digital defences for an optimised and up-to-date security situation. Combined with advanced security analysis, threat intelligence helps reduce the time between the detection of an attack and its containment. This is achieved by continuously providing information, accompanied by data, on existing and emerging cyber threats and vulnerabilities affecting corporate networks. This paper addresses challenges that organisations are bound to face when they decide to invest in effective and interoperable cybersecurity information sharing and categorises them in a layered model. Based on this, it provides an evaluation of existing sources that share cybersecurity information. The aim of this research is to help organisations improve their cyber threat information exchange capabilities, to enhance their security posture and be more prepared against emerging threats.

Cyber Threat Intelligence (CTI) is an important asset for organisations to facilitate the safeguarding of their systems against new and emerging cyber threats. CTI continuously provides up-to-date information which enables the design and implementation of better security measures and mitigation strategies. Organisations gather data from different sources either internal or external to the organisation, which are analysed, resulting in CTI. Nevertheless, the gathered data usually contain a large amount of content that is irrelevant to CTI or even to cybersecurity. Furthermore, most approaches concerning CTI management (e.g., gathering, analysis) involve simply gathering and storing the information without any enrichment such as classification or correlation. However, in order to obtain the optimal results, organisations should be able to utilise all capabilities of CTI. Therefore, in this work, we propose ThreatWise AI, a novel framework which enables the gathering, analysis, enrichment, storing and sharing of CTI in an efficient and secure manner. In particular, we have developed a novel pipeline in ThreatWise AI which incorporates different advanced tools, with distinct capabilities that interact with each other to provide a complete set of functionalities for the administration of the overall CTI lifecycle. The developed tools integrate various Python scripts and provide gathering and analysis functionalities of CTI. Furthermore, the proposed framework leverages the MISP platform for storing, enriching and sharing while it also integrates Artificial Intelligence (AI) and Machine Learning (ML) algorithms for advanced data enrichment.

The use of Unmanned Aerial Vehicles (UAVs) in various domains is continuously increasing. The benefits offered by UAVs enable the facilitation of functions or execution of tasks, such as search and rescue, which would otherwise be challenging or financially restrictive. Furthermore, UAVs are important for the military domain being considered as efficient weapons. Therefore, many countries and retail companies are investing in the massive production of UAVs for market as well as government purposes. Nevertheless, most UAVs in all domains, lack even basic cybersecurity mechanisms, thus, posing cybersecurity threats that significantly affect cybersecurity aspects or result in physical damage and even loss of human life. Many cybersecurity solutions have been proposed in the literature, encompassing both reactive and proactive measures, with the latter being preferable. Added to this, threat modeling emerges as an effective proactive measure with minimal cost and complexity. The current work conducts extensive and comprehensive research concerning the domain of UAVs. Initially, the article outlines the historical development of UAVs and the different taxonomies in which they are classified according to different characteristics (e.g., number of rotors). The next sections detail a comprehensive description of the Internet of Drones (IoD) environment and the various relevant cybersecurity issues. Subsequently, the article examines a wide range of diverse threat modeling approaches found in the literature, while it categorizes relevant articles based on whether they describe solutions that integrate threat modeling or propose novel approaches for threat modeling.