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In an effort to analyze existing adversarial attacks and defenses, researchers at the University of California, Berkeley, Nicholas Carlini and David Wagner in 2016 propose a faster and more robust method to generate adversarial examples. [97] The attack proposed by Carlini and Wagner begins with trying to solve a difficult non-linear ...
Tactics are the “why” of an attack technique. The framework consists of 14 tactics categories consisting of "technical objectives" of an adversary. [2] Examples include privilege escalation and command and control. [3] These categories are then broken down further into specific techniques and sub-techniques. [3]
Common methods of proactive cyber defense include cyber deception, attribution, threat hunting and adversarial pursuit. The mission of the pre-emptive and proactive operations is to conduct aggressive interception and disruption activities against an adversary using: psychological operations, managed information dissemination, precision targeting, information warfare operations, computer ...
Attack trees have also been used to understand threats to physical systems. Some of the earliest descriptions of attack trees are found in papers and articles by Bruce Schneier, [4] when he was CTO of Counterpane Internet Security. Schneier was clearly involved in the development of attack tree concepts and was instrumental in publicizing them.
Rapid Decisive Operations – Compelling the adversary to undertake certain actions or denying the adversary the ability to coerce or attack others. Raiding – Attacking with the purpose of removing the enemy's supply or provisions; Refusing the flank – Holding back one side of the battle line to keep the enemy from engaging with that flank ...
Active cyber defense has yielded greater efficacy in detecting and prosecuting APTs (find, fix, finish) when applying cyber threat intelligence to hunt and adversary pursuit activities. [36] [37] Human-Introduced Cyber Vulnerabilities (HICV) are a weak cyber link that are neither well understood nor mitigated, constituting a significant attack ...
Since the emergence of prompt injection attacks, a variety of mitigating countermeasures have been used to reduce the susceptibility of newer systems. These include input filtering, output filtering, prompt evaluation, reinforcement learning from human feedback, and prompt engineering to separate user input from instructions. [19] [20] [21] [22]
[1] [2] [3] Carlini became known for his work on adversarial machine learning. In 2016, he worked alongside Wagner to develop the Carlini & Wagner attack, a method of generating adversarial examples against machine learning models. The attack was proved to be useful against defensive distillation, a popular mechanism where a student model is ...