This method involves the use of crowdsourced attack data to identify and investigate potential threats. By creating hypotheses about possible threats and then investigating them using various techniques such as network traffic analysis, log analysis, and malware analysis, threat hunters can identify potential threats before they become an issue. This method is effective in understanding the Tactics, Techniques, and Procedures (TTPs) used by attackers.
This technique uses intelligence to detect and investigate malicious activities. By collecting data from various sources such as IoCs (indicators of compromise), hash values, IP addresses, domain names, networks, etc., and analyzing it, threat hunters can identify potential threats. This data is then used to create an Intel-based hunting strategy which can be used to detect and investigate malicious activities in the network. This method also involves using TAXII (trusted automated exchange of intelligence information) and STIX (structured threat information expression) standards for exchanging threat intelligence information between different organizations.
This method uses machine learning, AI, and analytics to identify potential threats. By using analytical frameworks and models to detect anomalies in data and uncover malicious activities, threat hunters can reduce bias in the analysis. The Diamond Model of Intrusion Analysis (DMIA) is one such model that requires the threat hunters to structure the data they are analyzing into categories including adversary, infrastructure, capability, and victim. However, it's important to note that this method may not work for every situation, and hunters must understand the limitations of their expertise and how to eliminate bias from their analysis-driven investigations.