Osako T, Suzuki T, Iwata Y (2016) Proactive defense model based on cyber threat analysis. IGI Global, pp 42–61Ħ Easy ways to advance your cybersecurity program when you have a small team, ThreatConnect, Arlington, VA (2017). In: Collective creativity for responsible and sustainable business practice. Patrick H, Fields Z (2017) A need for cyber security creativity. State of Malware Report, Malwarebytes Labs, Santa Clara, CA, 2017. The implementation result shows that the proposed model detects new generation malware effectively and fulfils all the security requirements as proposed in SANS Tools and Standards for Cyber Threat Intelligence Projects. Layer 3, provides a detailed report using Elastic search–Logstash–Kibana (ELK) stack. Layer 2 pre-processes, classifies and filters the received data from layer 1. Layer 1 consists of input layer data incoming from online and offline sources. The proposed framework consists of three layers. In addition to this, the paper also proposes a cyber-threat intelligence framework which overcome the problems found in existing models and frameworks. In this paper, we have analysed various cyber threat intelligence models used by organizations with respect to their potential features, their methods of countermeasures, language specification of the threat indicators, whether they are open source or closed source, owning organization, acceptance parameters of security requirements and capability to measure the efficacy of cyber threat intelligence feeds. The emerging risk of cybercrimes has compelled the organisations to shift their cyber defence strategy from reactive to proactive.
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