Far less concerned by the threat of losing their jobs, cybercriminals seem to have embraced the technology with enthusiasm - it's like a long-awaited birthday treat.
AI can help create more sophisticated and effective cyberattacks that are better targeted at exploiting system vulnerabilities.
With AI's ability to learn from data and continuously refine its tactics, cybercriminals can create more sophisticated, elusive, and difficult-to-detect malware.
AI-powered malware can be trained to remain inactive until it detects a vulnerability, to learn and mimic how the uninfected system behaves to stay undetected or act when the camera is on to avoid security measures based on facial recognition.
Deepfake scams leverage AI technology to create convincing fraudulent media, such as videos or audio recordings, to deceive individuals and organizations for malicious purposes.
Cybercriminals are getting smarter with AI. However, we, as their potential targets, keep feeding them with personal data and handing it to them on a silver platter.
The availability of our personal information online contributes to the rise of cybersecurity threats, including new AI threats.
A recent study has revealed that 60% of crimes reported to the Internet Crime Complaint Center were likely facilitated or made worse by criminals with access to people's data.
The data we willingly share online inadvertently becomes fuel for AI-enabled cybersecurity threats.
The adoption of strategies for future-proofing data security should be high on the list of law-making agendas worldwide.
Depending on where you live, data security and privacy laws may already be on the books.
Inevitably, AI-powered security and privacy systems are the answer to AI-powered threats.
Many companies have recently introduced precisely that: AI-powered, cutting-edge security offerings.
Establish secure data policies: This involves encrypting sensitive data and setting up access control measures for confidential information.
Conduct regular audits: Regular audits of data collection and storage practices can help identify potential security issues before they arise.
Implement data anonymization: Data anonymization is an effective technique used to protect individual privacy when dealing with AI systems.
Transforming or encrypting identifiable data into a format that cannot be traced back to specific individuals helps preserve privacy while enabling AI systems to learn from data patterns.
Limit data access: Ensure that AI systems have access only to necessary data to mitigate privacy and security risks.
Build specialized security teams: Considering the cybersecurity workforce gap, it is vital to invest in building technical security teams responsible for monitoring AI systems, identifying vulnerabilities and taking proactive measures.
Staying shy and smart about how we share our data is still the best preventive measure we can all take right now.
This Cyber News was published on securityboulevard.com. Publication date: Thu, 14 Dec 2023 14:43:05 +0000