cyber
TRENDS
Gen Z Americans shun biometric authentication solutions
However, while the technological arms race in cybersecurity intensifies, a new study shows a deep public distrust among US citizens regarding biometric security measures. A report from Frontegg, Americans Hate Password Resets So Much They’ d Rather Abandon Your App that is based on a survey of over 1,000 Americans, reveals a significant reluctance to adopt biometric authentication, despite its potential to offer a more secure alternative to traditional passwords.
The study found that 70 % of Americans would refuse biometric implants, such as brain chips, under any circumstances, regardless of the purported benefits, citing concerns over bodily autonomy and the potential for misuse of such invasive technologies.
The study also revealed a generational divide in trust towards AI in security. A concerning 72 % of Generation Z, the digital natives, expressed distrust in AI for securing their data – a higher percentage than any other generation. This scepticism among younger users, who are often early adopters of technology, raises questions about the future acceptance of AI-driven security measures.
Concerns extend beyond invasive implants, with nearly half( 49 %) of Americans expressing worry that facial recognition technology is being used to track them beyond their personal devices. This highlights a broader unease about the potential for surveillance and the privacy implications of biometric data collection. Despite the welldocumented weaknesses of traditional passwords, 61 % of Americans stated they trust passwords more than AI for their security.
Why NHIs impact Human Identity fraud
communications from malicious attempts to steal their login credentials, personal information and financial details.
• Social engineering enhanced by AI: AI significantly enhances social engineering attacks, which often precede or accompany identity-related breaches. AI can be used to analyse social media profiles, online behaviour, and personal information to create highly targeted and believable scams that trick individuals into divulging sensitive data or performing actions that compromise their security. This often involves the theft or misuse of human identities.
• Credential phishing: The report focuses on the need to strengthen Multi-Factor Authentication( MFA) to combat the growing threat of credential phishing. This highlights that stealing human credentials( usernames and passwords) remains a primary goal for attackers, and AI is making these phishing attempts more effective.
• Ransomware and Human Identity Fraud: Ransomware attacks often begin by compromising human user accounts. AI could potentially be used to identify vulnerable human targets within an organisation to gain initial access for ransomware deployment. The‘ double extortion’ tactics also involve the exfiltration of sensitive data, which often includes personally identifiable information( PII) linked to human identities.
• Exploiting weak password habits: Many Americans still have poor password habits. AI could be used to predict common password patterns and launch more effective bruteforce or password spraying attacks against human accounts.
The study also revealed a generational divide in trust towards AI in security. A concerning 72 % of Generation Z, the digital natives, expressed distrust in AI for securing their data – a higher percentage than any other generation.
While the Delinea report doesn’ t provide a specific numerical breakdown solely for AI-powered attacks targeting human identities, it offers insights into the evolving threat landscape where human identities remain a significant point of attack, especially when combined with AI tactics.
• AI-driven phishing attacks: AI-driven phishing attacks are a direct threat to human identities as cybercriminals leverage AI to craft increasingly convincing and personalised phishing emails. These sophisticated emails make it harder for individuals to distinguish legitimate
The Frontegg study also highlights a paradox: while a significant majority express distrust in advanced security methods, 57 % of self-identified‘ tech-savvy’ users already rely on biometrics like fingerprint or facial recognition for authentication. This reveals a growing divide between early adopters who prioritise convenience and those who remain sceptical due to privacy and trust concerns.
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