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🚀 Unveil how the AI executive order strengthens security measures for federal agencies, emphasizing directives and time-bound objectives to mitigate AI risks and promote responsible implementation. 🔒 Delve into the domain of secure AI deployment in the public sector and its implications for enhancing data protection and privacy. 📰 Learn more about the AI executive order's impact on federal agency security in the detailed Federal News Network article. #AIExecutiveOrder #FederalAgencies #AIsecurity [Link to article]

Information Security: Navigating the AI-Driven Future (and the EU's AI Act) Artificial intelligence is rapidly reshaping the cybersecurity landscape, but so is landmark legislation like the EU's AI Act. This groundbreaking regulation will have significant implications for AI usage in information security. Key Trends to Watch: Automated Threat Detection: AI excels at spotting subtle patterns, identifying previously unknown attacks much faster than traditional systems. Adaptive Security: AI systems will continuously improve defenses, making it harder for attacks to succeed. AI-Powered Attacks Bad actors will harness AI to exploit vulnerabilities and craft attacks that bypass traditional defenses. The Ethics of AI in Security: Concerns about bias, privacy, and accountability must be addressed when AI drives security decisions. EU's AI Act Impact: The regulation's risk-based approach will demand stricter controls as AI systems become more complex. Expect increased transparency, explainability, and human oversight, especially for high-risk AI applications in security. The Future of InfoSec in the Age of AI (and Regulation) The EU's actions set an important precedent. Tomorrow's cybersecurity professionals will need a strong grasp of AI's capabilities, the limitations of the technology, and the evolving regulatory environment. Here's where the conversation gets interesting! How do you think the EU's AI Act will reshape infosec practice in Europe and beyond? Do you believe this type of regulation is necessary to balance innovation with security? #informationsecurity #AI #cybersecurity #futureofwork #EUregulation

Generative AI and Large Language Models (LLMs) are becoming integral in both internal and external enterprise applications. But with great power comes great responsibility. Here's a deep dive into the potential security concerns: 🌐 Internal & External Applications: From automating data analysis and handling routine inquiries internally to offering personalized recommendations and intuitive experiences for customers, the potentials are vast. 🚫 Potential Pitfalls: Inadvertent data sharing and biased responses from LLMs pose real risks. Think of unintentional sharing of sensitive data or unintentionally discriminatory responses – the implications can be vast, from reputational harm to regulatory penalties. 🔐 Shifting Security Landscape: Traditional WAFs might not cut it. As integrations with AI and LLMs often happen through APIs, the security measures need a rehaul. It's not just about blocking certain IPs or users; it's about monitoring individual transactions, ensuring data privacy, and more. Dive into the full article to get detailed insights! 🚀 #AI #Cybersecurity #LLMs #GenerativeAI #artificialintelligence

Generative AI and Large Language Models (LLMs) are becoming integral in both internal and external enterprise applications. But with great power comes great responsibility. Here's a deep dive into the potential security concerns: 🌐 Internal & External Applications: From automating data analysis and handling routine inquiries internally to offering personalized recommendations and intuitive experiences for customers, the potentials are vast. 🚫 Potential Pitfalls: Inadvertent data sharing and biased responses from LLMs pose real risks. Think of unintentional sharing of sensitive data or unintentionally discriminatory responses – the implications can be vast, from reputational harm to regulatory penalties. 🔐 Shifting Security Landscape: Traditional WAFs might not cut it. As integrations with AI and LLMs often happen through APIs, the security measures need a rehaul. It's not just about blocking certain IPs or users; it's about monitoring individual transactions, ensuring data privacy, and more. Dive into the full article to get detailed insights! 🚀 #AI #Cybersecurity #LLMs #GenerativeAI #artificialintelligence

Richard Davies, UK Managing Director at Netcompany, discusses how businesses can leverage retrieval-augmented generation to protect their data from security risks posed by generative AI. With deepening aspirations to embrace generative AI, controlling and managing data will be essential for businesses to create systems that deliver value without compromising safety. In a recent report that assessed concerns about generative AI, it found that organisations were most worried about data privacy and cyber issues (65%), employees making decisions based on inaccurate information (60%) and employee misuse and ethical risks (55%). Click the link below to discover more. ⬇ https://lnkd.in/gKGQ-R8p #ArtificialIntelligence #MachineLearning #DeepLearning #NeuralNetworks #DataScience #AIInnovation #Automation #NaturalLanguageProcessing #ComputerVision #AIEthics

Protecting sensitive data from generative AI is crucial. Generative AI has sparked extensive interest in artificial intelligence pilots, but organizations often don’t consider the risks until AI models or applications are already in production or use. A comprehensive AI trust, risk, security management (TRiSM) program helps you integrate much-needed governance upfront, and proactively ensure AI systems are compliant, fair, reliable and protect data privacy. #data #security #protection #challenges #ai #yallo #yalloretail #goyallo

Generative AI, like any technology, has the potential to pose risks to data governance and privacy. For example, DEEEP FAKE VIDEOS - DFVs (you know what we're talking about!) These highly realistic videos that manipulate and superimpose someone's face onto another person's body or create entirely fabricated videos can be disastrous for anyone. The AI technology has the potential to deceive viewers and can be misused to:   - Spread false information  - Defame individuals  - Manipulate public opinion...and so on. These scenarios raise concerns about privacy, consent, and the authenticity of visual content/data/information. It highlights the need for robust data governance and privacy measures to address the risks associated with #generativeAI. Besides Deep Fake Videos [DFVs], generative AI in crazy hands can produce large amounts of data that may contain sensitive information, and if not handled properly, could lead to data breaches or misuse of information. The threats may include: 1. Sensitive data exposure: Risk of exposing sensitive information. 2. Misuse of information: Potential for malicious use. 3. Fake data creation: Generating deceptive or manipulated data. 4. Lack of transparency: Insufficient clarity and regulation. 5. Biassed data generation: Perpetuating biases and discrimination. 6. Security vulnerabilities: Prone to breaches and attacks. If threats are not handled with a proper solution designed to protect your business ops, it could be used to deceive or mislead individuals or organisations. Strong security measures, proper data governance, and privacy policies are crucial to protect data. Access to data should be restricted to authorised individuals or systems. Transparency about data collection and use is also important. At the end of the day, the responsible use of generative AI can be prioritised to protect individuals' privacy and the security of their data. If you're looking for a solution that can help you fight cybercrimes, secure your business ops from potential security threats, and build support for trust transformation, you're free to connect with us today! We're pioneering security solutions, fostering next-gen innovations, and creating solutions for a secure environment to conduct business. #dataprivacy #ai #dataprotection #databreach #cyberattack #cyberthreats

🚀 Explore AI Governance with TRiSM! 🌐 Discover TRiSM – The Comprehensive Framework for AI Model Governance, Trustworthiness, and Data Protection. 🤖💡 Read about the five pillars: Trustworthiness, Fairness, Reliability, Robustness, and Efficacy. Learn how TRiSM ensures responsible AI development, robust security, and data privacy. 📅 Apply the framework for transparent, accountable, and ethical AI systems. 🔗 bit.ly/4aIdPvA #AI #Governance #TRiSM #ResponsibleAI #DataPrivacy #EthicalAI #Innovation 🌐

Quick Friday thought! As AI and Machine Learning continue to revolutionise our world. Here are the top 5 areas to think about: Data privacy: Protecting sensitive data used in training and operating AI/ML models. Ensuring data integrity and confidentiality is paramount. Model security: Guarding against adversarial attacks that can manipulate or deceive AI algorithms. Robust testing and validation methods are essential. Ethical AI & bias mitigation: Ensuring AI systems are fair, transparent, and non-discriminatory. This involves careful design and continuous monitoring. Regulatory compliance: Keeping pace with evolving legal standards, especially in GDPR and other privacy laws impacting AI data usage. Securing AI infrastructure: Protecting the underlying infrastructure, including cloud environments and data storage, against cyber threats. As we harness the power of AI and ML, prioritising these security areas will help mitigate risks and foster trust in these transformative technologies. #security #ML #AI #artificialintelligence #machinelearning #dataprivacy #ethicalai

Concerns around the informal rise of generative AI in the enterprise are growing. CIOs are worried about data security, privacy, and compliance issues. There's also the risk of models becoming biased through adversarial attacks. So, how can CIOs succeed in managing the safe use of generative AI within their organizations? #AI #cios #Compliance #DataSecurity #enterpriseai