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?? Artificial Intelligence (AI) has swiftly evolved, reshaping industries and driving innovation. However, this rapid advancement has outpaced current regulatory frameworks, particularly regarding data security and privacy. Tim Freestone emphasizes that while frameworks like the NIST AI Risk Management Framework and Executive Order 14110 have made strides, they fall short in critical areas such as access controls and data tracking. This oversight exposes AI systems to significant risks, including data breaches, privacy violations, and loss of public trust. Freestone proposes a robust approach to fill these gaps by prioritizing data security through zero trust principles. Implementing least-privilege access, continuous monitoring, and stringent tracking mechanisms can significantly enhance data protection. This approach ensures regulatory compliance, reduces algorithmic bias, and fosters public trust, paving the way for responsible AI innovation. Key Points: ?? Current AI regulations lack comprehensive data security measures. ?? Zero trust principles can enhance AI data protection. ?? Proper data handling can mitigate risks and build public trust. #AI #DataSecurity #Privacy #ZeroTrust #AIRegulation #TechInnovation #Cybersecurity #DataProtection

?? ?? Deploying and monitoring AI models across distributed industrial environments presents several challenges, especially when it comes to ensuring cybersecurity and compliance. ?? Here are some key challenges and considerations: ?? Challenges: ??? ?? Data Security: Ensuring that data used for training and deploying AI models is secure from unauthorized access and breaches. ?? Integration with Existing Systems: Seamlessly integrating AI models with legacy systems and ensuring compatibility. ?? Scalability: Managing the scalability of AI models across multiple sites and devices. ?? Latency and Connectivity: Dealing with latency issues and maintaining reliable connectivity in remote or distributed environments. ??? Regulatory Compliance: Adhering to various industry regulations and standards, such as GDPR, HIPAA, or industry-specific guidelines. ?? Model Accuracy and Reliability: Ensuring that AI models perform accurately and reliably in real-world industrial settings. ?? Ethical Considerations: Addressing ethical concerns related to AI, such as bias in decision-making and transparency. Best Practices for Cybersecurity and Compliance: 1 Risk Assessment: Conduct thorough risk assessments to identify potential vulnerabilities and compliance risks. 2 Data Encryption: Implement strong encryption methods to protect data both in transit and at rest. 3 Access Control: Use robust access control mechanisms to ensure that only authorized personnel can access sensitive data and AI systems. 4 Regular Audits: Perform regular security audits and compliance checks to identify and address any issues promptly. 5 Employee Training: Provide ongoing training for employees on cybersecurity best practices and compliance requirements. 6 Continuous Monitoring: Implement continuous monitoring and anomaly detection systems to quickly identify and respond to potential threats. 7 Policy Management: Develop clear policies and procedures for AI deployment, data handling, and security measures. By addressing these challenges and implementing best practices, organizations can deploy and monitor AI models more effectively while ensuring cybersecurity and compliance. #RA #ACL #GDPR #HIPAA #CYBERSECURITY #AUTOMATION #CLOUD #QMS

Protecting Data in the Age of AI AI is transforming the way we work, but it also introduces new cybersecurity risks. While it enhances efficiency, it can also be exploited, leading to data breaches and compliance challenges. A recent discovery by a cybersecurity firm Wiz highlights this risk: DeepSeek, an AI model, reportedly leaked over one million sensitive records, exposing vulnerabilities in AI-driven systems. With AI becoming essential for professionals and students alike, how can organizations safeguard data and ensure compliance with NDPA/NDPR, GDPR, and other regulations? 5 Key Strategies to Protect Your Data with AI 1?? Define and enforce clear data usage policies 2?? Train employees on responsible AI and data handling 3?? Implement access controls for AI tools and sensitive data 4?? Review privacy policies of AI tools before adoption 5?? Test and verify AI-generated code, information and outputs Policy Considerations To ensure responsible AI deployment, organizations should align with key security and governance frameworks, such as: ? NIST Cybersecurity Framework (CSF) – Guides organizations in managing cybersecurity risks, including AI-related threats. ? NIST AI Risk Management Framework (AI RMF)– Provides structured risk management for AI systems, focusing on security, fairness, and transparency. ? ISO/IEC 27001 (Information Security Management System)– Establishes a strong security foundation for protecting data in AI-driven environments. ? ISO/IEC 42001 (AI Management System) – The latest global standard for responsible AI governance, covering risk, transparency, and compliance. ? OECD AI Principles – International guidelines promoting trustworthy and ethical AI use. ? NBA AI Principles – Nigeria’s legal framework for ethical and responsible AI adoption. ?? Example Policy Statement: "Our organization shall develop and implement AI systems in compliance with the NIST Cybersecurity Framework and ISO/IEC 27001. AI systems shall prioritize fairness, transparency, and accountability while ensuring the protection of sensitive data and regulatory compliance." As AI adoption accelerates, staying ahead of cyber threats is critical. What strategies do you think organizations should adopt to secure AI-driven data? Let’s discuss in the comments! #AI #DataProtection #CyberSecurity #AIRegulation #PrivacyByDesign #AISecurity #RiskManagement #NigeriaAI #DataPrivacyNigeria #NBALawTech

?? ???????????? ???? ???????????????????? - ?????? ??????/?????? ?????????? ???? ?? ????????-??????????????? In a world dominated by Artificial Intelligence, trust, security, and compliance are more critical than ever. The ISO 42001 Certification is the global benchmark for AI excellence, helping professionals and organizations align their practices with ethical AI standards. ?? ?????? ???????????????????? ???????? ?????? ??????????? 1. Build stakeholder confidence with transparent AI practices. 2. Guard your reputation against AI misuse. 3. Simplify audits with a globally recognized framework. ?? ?????? ???????????????? ??????????????????????????: 1. Protect sensitive data with integrated security and AI threat detection. 2. Safeguard systems with cutting-edge cybersecurity and AI synergy. ?? ?????? ????????????????????, ???????? & ???????????????????? ??????????: 1. Meet global AI standards and avoid legal pitfalls. 2. Manage AI audits and regulatory alignment seamlessly. ?? ?????? ???????????????? ??????????????: 1. Drive secure innovation with adaptable AI strategies. 2. Build trust through ethical AI practices. ?? LIMITED SEATS - Join our LIVE Online Training and master ISO/IEC 42001 to stay ahead of regulatory demands, secure your AI ecosystem, and lead with confidence in the digital age. ?? ?? Contact Now : +91-91130 68710 ?????? ?????????????????? & ???????????? ?????? ???????????? ???? ?????????????? ???? ! #ISO42001 #ArtificialIntelligence #AIGovernance #AICompliance #CyberSecurity #RiskManagement #AIInnovation #EthicalAI #AILeadership #ProfessionalGrowth #GlobalCertifications #CareerDevelopment Exemplar Global, Inc. V Narayanmurthy

Unlock the power of agentic AI while ensuring top-notch security and compliance! ???? Our blog dives deep into the world of agentic AI security, exploring why governance frameworks matter and how to tackle key challenges. Learn about our TRAPS Framework, designed to accelerate time-to-value while addressing potential risks. Discover how Aisera is: ?? Enhancing transparency and explainability ?? Prioritizing data privacy and security ?? Staying ahead of evolving compliance requirements Don't miss out on leveraging agentic AI responsibly and effectively for your business. Read our blog to find out how Aisera is leading the way in secure, ethical AI deployment. https://lnkd.in/gKTqaJSm #AgenticAI #AISecurity #AIGovernance #AICompliance #FutureOfAI

Artificial Intelligence and Cybersecurity—Balancing Risks and Rewards? #ArtificialIntelligence (#AI) is transforming industries, offering unprecedented opportunities for innovation, but also introducing complex cybersecurity challenges. The World Economic Forum, in collaboration with the Global Cyber Security Capacity Centre (GCSCC), University of Oxford, presents this report to address the dual role of AI as both a tool for strengthening #cybersecurity and a potential attack vector.? The Dual Impact of AI on Cybersecurity ?? AI’s influence on cybersecurity is twofold: it enhances cyber defense mechanisms while simultaneously being leveraged by malicious actors to conduct more sophisticated attacks. #Cybercriminals exploit AI for large-scale phishing, reconnaissance, zero-day exploit detection, and AI model poisoning. Meanwhile, defenders employ AI for advanced threat detection, automated remediation, and enhanced #riskassessment.? Emerging Cybersecurity Practices for AI ?? A proactive approach to AI cybersecurity is essential. The report introduces the “Shift Left, Expand Right, and Repeat” model, which emphasizes:?? - Shift Left: Implementing security-by-design principles early in AI system development.?? - Expand Right: Extending cybersecurity measures beyond deployment to continuously monitor and mitigate risks.?? - Repeat: Continuously reassessing vulnerabilities throughout the AI lifecycle.? Strategic Leadership in AI Cyber Risk Management AI adoption must be governed by clear cybersecurity policies aligned with business objectives. Senior executives must ensure:?? - A cross-disciplinary #riskmanagement approach involving cybersecurity, legal, compliance, and #business units.?? - AI application inventories to track exposure and manage risks associated with “shadow AI.”?? - Secure AI #supplychains, ensuring transparency in third-party AI integrations.?? - Investment in #cybersecurityinfrastructure, #workforce training, and AI-specific resilience frameworks.? Regulatory and compliance considerations are also critical, as AI governance standards are evolving rapidly across jurisdictions. Organizations must align AI cybersecurity strategies with global regulatory frameworks to mitigate legal and #financialrisks.?? ?? In summary, AI’s integration into cybersecurity presents a paradox: it strengthens defenses while simultaneously introducing new risks. Organizations must adopt an adaptive, forward-looking cybersecurity strategy to navigate this evolving landscape. Effective AI risk management requires collaboration between AI developers, cybersecurity professionals, regulators, and #policymakers. By embedding security into AI’s entire lifecycle, businesses can confidently leverage AI’s potential while mitigating its risks, ensuring both resilience and competitive advantage in an increasingly AI-driven #economy.

?? AI Compliance: The Next Frontier in Cybersecurity ?? As AI technology continues to reshape industries, the need for robust AI compliance is no longer a distant concern—it’s here now! Are you prepared? Here are some mind-blowing facts that highlight why AI compliance is critical for cybersecurity professionals: ?? 95% of organizations believe that AI will increase their compliance risks. As AI systems become more complex, ensuring compliance will become increasingly challenging. ?? According to Gartner, by 2025, 75% of organizations will establish AI compliance programs to mitigate risks related to ethical use, privacy, and security. ?? 60% of companies report they have no clear AI governance policies in place, leaving them vulnerable to regulatory fines and reputational damage. ?? As of 2024, over 30 countries are expected to introduce AI regulations, making it imperative for organizations to prepare for a multi-jurisdictional compliance landscape. ?? 83% of organizations say they lack the necessary tools to manage AI compliance, which could lead to significant legal repercussions. ?? The cost of non-compliance is staggering; organizations can face fines of up to 4% of global revenue under regulations like the EU's GDPR—this extends to AI applications as well. ?? A recent study found that 54% of AI projects will fail due to compliance and ethical challenges, highlighting the critical need for governance frameworks. ?? The rapid rise of AI in decision-making processes increases the risk of biased outcomes. Without proper compliance measures, organizations risk discrimination claims and erosion of trust. ?? 70% of cybersecurity experts believe AI compliance will be a top priority in the next 2-3 years, necessitating immediate action to build compliant frameworks. ?? As AI adoption accelerates, the window to establish compliance protocols is closing fast. Organizations must act now to avoid falling behind in a competitive market. ?? The time to act is NOW! Cybersecurity professionals must advocate for and implement AI compliance strategies that not only protect their organizations but also build public trust in AI technologies. Let's lead the charge in shaping a secure and compliant future for AI! Share knowledge with other people! #AI #Cybersecurity #Compliance #DataProtection #EthicalAI #AIRegulation #Governance #Infosec

With Bill 194 out in Ontario, the?Strengthening Cyber Security and Building Trust in the Public Sector Act, 2024, public sector entities are required to adopt robust measures for the responsible use of AI. This includes developing accountability frameworks, managing risks, and ensuring transparency in AI operations. At C3SA Cyber Security & Audit, we are excited to be partnering with AGAT Software AI, whose?BusinessGPT., a security and governance firewall for AI, is well aligned to meet these needs. Here's how: Key AI Requirements of Bill 194: Transparency: Public sector entities must provide information about their use of AI systems. Accountability: Development and implementation of accountability frameworks for AI use. Risk Management: Steps to manage risks associated with AI systems. Oversight: Ensuring oversight and compliance with prescribed regulations The BusinessGPT AI Firewall?offers comprehensive visibility and control over GenAI usage, ensuring full oversight of how it is utilized and what data is involved, providing transparency and accountability. It enforces risk-based policies tailored for AI services, mitigating risks associated with GenAI use while ensuring compliance with regulatory standards. For organizations that prefer to avoid exposing their data to public AI services like ChatGPT and Microsoft Copilot, BusinessGPT provides a?Private AI Solution. This secure and customizable chatbot includes advanced Retrieval-Augmented Generation (RAG) and data analysis capabilities. It supports self-hosting and on-premises deployment options, safeguarding data privacy while meeting stringent accountability requirements. Organizations (public or private) can harness the benefits of GenAI, stay competitive, and manage risks effectively without compromising on data security or compliance. Curious? ??Please reach out. #AI #CyberSecurity #PublicSector #Ontario #BusinessGPT #AGATSoftware #DigitalTransformation

Best practices for securing and ensuring the resilience of #AIsystems include: -?Apply a risk-based approach to AI adoption with a wide range of stakeholders involved in managing the risks end-to-end within the organization. -?Create an inventory of AI applications to assess how and where AI is being used within the organization, including whether it is part of the mission-critical #supplychain. -?Ensure that there is adequate investment in the essential #cybersecurity controls needed to protect AI systems and ensure that they are prepared to respond to and recover from disruptions. Key practices include robust #threat and vulnerability management practices, implementing controls for protecting the perimeters of systems – such as segmentation of networks and databases and data-loss prevention, beside segregation of duties and ensuring that the AI systems and the infrastructure hosting AI algorithms and #data are protected by access controls such as #MFA and #PAM. -?Implement technical controls around the AI systems with people- and process-based controls on the interface between the technology and business operations. -?Give extra care to information governance specifically, what data will be exposed to the AI and what controls are needed to ensure that organizational data policies are met. Also, secure sharing sensitive information with AI system