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Remember:

    Artificial intelligence itself does not decide who to target. These decisions are made by individuals or organizations leveraging AI technology for their purposes. Here’s how it works:

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1. Who Is Behind It?
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  • Scammers and Cybercriminals:
    Use AI to execute mass or targeted attacks aimed at stealing money, data, or influence.
  • Political and Propaganda Organizations:
    Create synthetic identities or deepfakes to manipulate public opinion or discredit opponents.
  • Corporate Malefactors:
    Employ AI for industrial espionage, imitating competitors, or generating fake clients.
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2. How Are Victims Selected?
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a) Mass Targeting (Bulk Targeting):
  • How it works:
    Attackers aim at a large group of users, hoping a fraction will fall for the scam.
  • Examples:
    • Mass phishing emails pretending to be from a "bank," where attackers don’t know the victims personally.
    • Creating synthetic profiles that send friend requests to thousands of users on social media.
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b) Targeted Attacks:
  • How it works:
    Personal information about the victim is used to make the attack appear more convincing.
  • Sources of information:
    • Social Media: Posts, photos, comments, likes.
    • Data Breaches: Email addresses, phone numbers, data from hacked databases.
    • Public Sources: Biographies on corporate websites, interviews.
  • Examples:
    • Creating a deepfake of a colleague to fraudulently request money.
    • A synthetic persona building trust for fraudulent purposes.
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3. The Role of AI in Target Selection
AI helps automate and optimize the victim selection process:
  • Data Collection:
    AI scans public social media profiles to identify suitable targets, such as vulnerable groups like lonely individuals (for romance scams) or business owners (for fraudulent deals).
  • Personalization:
    AI can automatically generate messages tailored to specific individuals based on their data.
    • Example: "Hello Alex, you ordered a laptop yesterday, but we encountered a payment issue."
  • Probability Analysis:
    Using algorithms, AI can assess the likelihood of success with specific targets.
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4. Examples of AI-Driven Attacks
  • Romantic Scams:
    A synthetic persona engages in prolonged conversations to gain the victim’s trust.
  • Fake Business Proposals:
    A deepfake of a "company director" requests employees to transfer money to a fraudulent account.
  • Social Manipulation:
    Fake accounts comment on posts or send messages to influence the victim’s opinion.
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5. Who Is Most Vulnerable to These Attacks?
  • Social Media Users:
    The more information you share, the easier it is for scammers to use it against you.
  • Business Owners and Company Employees:
    Especially those with publicly available contact details and job titles.
  • Technologically Unaware Users:
    Those who don’t know how to recognize threats like phishing emails or suspicious requests.
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By understanding these methods, you can better protect yourself from becoming a victim of AI-driven scams.

Core Components of AI

  • Machine Learning (ML): A subset of AI where systems learn from data and improve over time without explicit programming. It enables predictive modeling and decision-making.

  • Natural Language Processing (NLP): A branch of AI that allows machines to understand and process human language for communication and analysis.

  • Computer Vision: An AI field focused on enabling computers to interpret visual data like images and videos for decision-making.

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