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Cyber threat hunting is a proactive cyber defence activity. It is "the process of proactively and iteratively searching through networks to detect and isolate advanced threats that evade existing security solutions."
Anomalies are detected in several ways, most often with artificial intelligence type techniques. Systems using artificial neural networks have been used to great effect. Another method is to define what normal usage of the system comprises using a strict mathematical model, and flag any deviation from this as an attack.
OWASP pytm is a Pythonic framework for threat modeling and the first Threat-Model-as-Code tool: The system is first defined in Python using the elements and properties described in the pytm framework. Based on this definition, pytm can generate a Data Flow Diagram (DFD), a Sequence Diagram and most important of all, threats to the system.
The STRIDE was initially created as part of the process of threat modeling. STRIDE is a model of threats, used to help reason and find threats to a system. It is used in conjunction with a model of the target system that can be constructed in parallel. This includes a full breakdown of processes, data stores, data flows, and trust boundaries. [5]
The report, released this week by Gladstone AI, flatly states that the most advanced AI systems could, in a worst case, “pose an extinction-level threat to the human species.”
For example, model extraction could be used to extract a proprietary stock trading model which the adversary could then use for their own financial benefit. In the extreme case, model extraction can lead to model stealing , which corresponds to extracting a sufficient amount of data from the model to enable the complete reconstruction of the model.
The use of artificial intelligence in NDR tools is growing, as security teams explore AI's potential to enhance NDR capabilities. Key AI use cases for NDR include: [ 5 ] Improved threat detection: AI can analyze large volumes of data on vulnerabilities, threats, and attack tactics to identify anomalous network activities.
Protective Intelligence (PI), is a subsection of executive protection and a type of threat assessment. [1] [2] PI is a proactive method of identifying, assessing, and mitigating possible threats to the client. It is meant to reduce the ability of an individual from getting close enough to attack the client or even the likelihood of them ...