AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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1,065 papers
The research indicates that AI governance responsibilities are often embedded within existing privacy roles, contributing to the rise of hybrid positions alongside dedicated AI governance roles.
Benign-Anchored Ranking and Selection (BARS), a two-stage filter that replaces CMD's global anchor with the benign-class mean and applies an order-preserving decorrelation step, is proposed, which reduces false alarms by up to 32% while maintaining similar detection rates, with larger gains under stronger imbalance.
The dithered Gaussian mechanism is presented, an alternative to the discrete Gaussian mechanism for differential privacy that discretizes the private output rather than the noise distribution itself, and it is shown that cryptographically secure noise generation with reduced exposure to floating-point vulnerabilities c...
This work formalises this as a framework-agnostic retrieval-to-action provenance graph, classify published attack families by their position relative to it, measure the resulting coverage property against collected agent traces, and falsify the detector's standalone deployment, reversing its own earlier recommendation...
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Both traditional heuristics and some common ML detection methods are ill-suited for consistently evolving DGA tactics observed in Gravity Falls, motivating more context-aware approaches and providing a reproducible benchmark for future evaluation.
The Digital Agriculture Sandbox is presented, a secure online platform that enables farmers (with limited technical resources) and researchers to collaborate on analyzing farm data without exposing private information and helps bridge the gap between maintaining farm data privacy and utilizing that data to address crit...
Feature selection is critical for network intrusion detection systems (NIDS) operating under high-dimensional, highly imbalanced traffic, as found in operational and defense networks. Traditional filter methods rank features using global statistics computed symmetrically across classes and thus fail to capture the asym...
This work proposes PromptMIA, a membership inference attack tailored to federated prompt-tuning, in which a malicious server introduces adversarially crafted prompts and exploits their updates during collaborative training to determine whether a target data point belongs to a client's private dataset.
A novel framework for approximating ROC and PR curves using quantiles of the score distribution, which can be computed efficiently under secure aggregation and distributed differential privacy, and provides theoretical guarantees on the approximation quality by bounding the Area Error between the true and estimated cur...
ICER is a black-box framework that addresses the gap in text-to-image models in harmful content generation through two components: an LLM-based rewriter that produces fluent, natural-language adversarial prompts, and in-context experience replay that accumulates successful jailbreaking patterns into a reusable prior.
This work repurposes cyber-physical process invariants from runtime detection heuristics into a verifiable admission requirement for federated updates, mined automatically from clean operational data, and shows invariant compliance using zero-knowledge proofs to allow clients to prove batch adherence without revealing...
As large language models (LLMs) become increasingly widespread, preventing unsafe responses to harmful prompts is essential for their safe deployment. Activation steering offers an approach to improving LLM safety by modifying internal activations during inference without updating model parameters. However, a single pr...
Gemini 3.8 Flash and 3.8 Flash Cyber deliver next-generation intelligence for agentic workflows and cybersecurity.
Google introduces Gemini 3.5 Flash Cyber, a lightweight cybersecurity model to find and patch vulnerabilities.
Students from the MIT Cybersecurity Clinic help local governments and other vulnerable organizations defend against digital threats.
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