Key Takeaways:
- Find out how generative AI is changing cloud security.
- Learn best practices for cloud security in the generative AI era.
- Discover generative AI tools and techniques for enhancing and improving system security.
- What are the anticipated future trends with generative AI and cloud security?
Cloud security in a generative AI world
If cloud security wasn’t already complex and evolving, new threats from generative AI and security are becoming more challenging to manage. Businesses must move fast and keep one step ahead of cybersecurity threats from all directions. The ability to build a business on the cloud securely and retain compliance requires a depth of expertise most individuals alone do not possess.
Amazon’s cloud environment is based on its Amazon Web Services (AWS) computing infrastructure and provides a complete set of security tools and services directly to businesses and also through experienced service providers. Businesses can integrate advanced security into their operations using automation. Innovate securely and build with confidence.
No need to choose between speed and security because you create both with AWS. As generative AI changes the cybersecurity landscape, cloud providers are leveraging generative AI to improve security and contain new threats automatically.
Generative AI and cloud security challenges
Generative AI presents new challenges and opportunities for cloud security. Despite the potential benefits of generative AI for improving cybersecurity, it makes data intensive operations riskier. For example, in the healthcare industry, using adversarial networks and language networks positively impacts medical diagnosis accuracy and patient care. However, healthcare records are data intensive and contain protected patient information.
With generative AI, protected information faces a greater risk of exposure. Generative AI expands the security threat surface by:
- Introducing vulnerabilities during model training
- Exposing personal data in violation of data privacy regulations
- Exposing intellectual property
- Increasing realism in phishing attacks
- Creating fake data or other fake content
During model training, data may be exposed during transfer or storage as systems are not regulated and have ineffective security rules or safeguards. Threat actors manipulate model training to access and alter data. Altered data is then released when the training model deploys.
Currently, generative AI does not have the regulatory structure in place to ensure personal data privacy. When building AI training models with personal data, the data can be accessed and used for identity theft or other cybercrimes. Corporate data is not safe either. Intellectual property and other confidential business information may be exposed when using proprietary data in training AI models.
Generative AI also enhances phishing attacks. Just when humans think we have all the scams figured out, the attacks become more human-like with generative AI’s influence that scammers can use to create more humanly realistic scams.
Enhancing cloud security with generative AI
The good news is that generative AI enhances cloud security protocols through automated identity verification and network management. The benefits of using generative AI tools for cybersecurity include enhanced real-time threat detection and response management. Businesses can detect and block an attack immediately through automated management.
Generative AI security automates security tasks like scanning server logs. Using AI automation, businesses can continuously scan networks without overloading the security team. AI is useful for identifying known vulnerabilities. New developments are in progress that create options for AI to proactively identify vulnerabilities and keep business systems fully secured.
Businesses can also leverage generative AI to increase security quality by:
- Creating realistic security training attacks using generative AI will prepare teams to respond effectively
- Generate anonymized data for use in software development and testing to reduce data exposure
- Automated security monitoring, reporting, and continuous vulnerability scanning
- Supply chain and third-party application risk assessment
- Proactive security threat analysis
- Cybersecurity incident tracking and forensic data generation
- Automating network management so updates are made on time every time
- Phishing detection so employees are alerted to suspicious communications
Best practices for cloud security in the Generative AI era
Best practices for cybersecurity are essentially the same as before the generative AI era, with a few additions:
- Create AI governance frameworks to manage AI operations in cloud systems and services
- Understand your cloud provider’s governance documentation to ensure oversight and effective security coverage
- Include human review of all AI use to ensure ethical and responsible business use
- Build automation into security processes within the cloud system
- Keep security practices and protocols up to date and train all affected employees
- Know and understand how the generative AI tools store or transfer data
- Never use or input sensitive data into generative AI models
- Keep generative AI tools managed the same way as other tools and networks
- Understand data governance and security protocols for your cloud provider
- Consider using data loss prevention and cloud-native application protection services
Knowing your cloud provider is the bottom line. Understand how security is configured and working on both sides. For example, AWS operates on a shared responsibility model. The business must understand and track security configuration settings.
Ensure security coverage is accurate and effective. Quality cloud service providers like CloudHesive Security Services can partner with your business to keep data and operations fully secured.
Preparing for the future of cloud security
Cloud security’s future is full of ongoing innovation, including threat detection and even prevention for known and emerging threats. The future is proactive – think offense rather than defense. Protect your business data and be fully compliant all the time.
Cloud service providers are preparing by:
- Developing Zero-Day attack prevention programs that proactively manage network systems and scan for known and new potential vulnerabilities
- Implementing dynamic security policies that adjust automatically to changing conditions and manage threats
- Leverage behavioral biometrics for user authentication accuracy
- Detect and prevent fake data and content
- Creating strong data privacy solutions
- Practice ongoing and continuous threat detection and tracking
Generative AI is both a security threat and an opportunity. Furthermore, it contributes to the cybersecurity problem but also provides the ability to innovate proactive solutions to prevent, track, and eliminate threats. Your business and your cloud service provider need to work together to keep cloud networks and data safe.
CloudHesive partners with your business to provide a dedicated, experienced cloud security and compliance team. Together, we’ll design a robust and compliant security strategy that keeps your business data secure and managed proactively. See what our customers say about working with CloudHesive. Don’t hesitate when it comes to your cybersecurity; contact us today!
