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FBI warns seniors about billion-dollar scam draining retirement funds, expert says AI driving it

FOX News

Pete Nicoletti, chief information security officer at Check Point, told Fox News Digital that an FBI-warned scam is now using AI to target seniors. A cybersecurity expert warns that a scam that has been used to drain entire life savings or retirement accounts has become "devastating" for seniors. FBI Los Angeles on July 15 posted a reminder on X about the Phantom Hacker Scam, which has cost Americans over 1 billion since at least 2024, according to the agency. The FBI said the scam targets senior citizens and warns that victims could lose their "life savings." The scam operates in three phases: a "tech support impostor," "financial institution impostor" and a "US government impostor." In the first phase, a tech support impostor will contact victims through text, phone call or email, then direct them to download a program allowing the scammer remote access to their computer.


DODGE: Ontology-Aware Risk Assessment via Object-Oriented Disruption Graphs

Nicoletti, Stefano M., Hahn, E. Moritz, Fumagalli, Mattia, Guizzardi, Giancarlo, Stoelinga, Mariëlle

arXiv.org Artificial Intelligence

When considering risky events or actions, we must not downplay the role of involved objects: a charged battery in our phone averts the risk of being stranded in the desert after a flat tyre, and a functional firewall mitigates the risk of a hacker intruding the network. The Common Ontology of Value and Risk (COVER) highlights how the role of objects and their relationships remains pivotal to performing transparent, complete and accountable risk assessment. In this paper, we operationalize some of the notions proposed by COVER -- such as parthood between objects and participation of objects in events/actions -- by presenting a new framework for risk assessment: DODGE. DODGE enriches the expressivity of vetted formal models for risk -- i.e., fault trees and attack trees -- by bridging the disciplines of ontology and formal methods into an ontology-aware formal framework composed by a more expressive modelling formalism, Object-Oriented Disruption Graphs (ODGs), logic (ODGLog) and an intermediate query language (ODGLang). With these, DODGE allows risk assessors to pose questions about disruption propagation, disruption likelihood and risk levels, keeping the fundamental role of objects at risk always in sight.