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The NSA's research director, Gilbert Herrera, recently shared insights on the impact of large language models (LLMs) like ChatGPT on the intelligence community. Here are the key takeaways: 1. The conversational abilities of ChatGPT mark a significant advance, even though the NSA has been researching AI for over two decades. 2. Due to privacy laws and budget limitations, the NSA faces hurdles in developing its own LLMs compared to tech giants. However, this doesn't significantly hinder their core mission of foreign intelligence. 3. The NSA could leverage commercial LLMs for reverse engineering cyber defenses. Techniques like retrieval augmented generation (RAG) could allow LLMs to analyze NSA data while adhering to privacy regulations. 4. The proliferation of AI introduces new security risks, such as enhanced phishing attacks. To address challenges like model theft and data leakage, the NSA has established an AI Security Center. The way forward is evident - the intelligence community must identify methods to harness the capabilities of commercial LLMs while safeguarding privacy and security. This will necessitate cutting-edge technical solutions, strong cybersecurity measures, and continued AI security research. Action items: - Explore technical approaches like RAG to enable privacy-preserving use of LLMs on sensitive data - Invest in robust cybersecurity practices to protect AI models and training data - Foster public-private partnerships to share knowledge and develop AI security best practices - Support ongoing research into AI security threats and countermeasures Knight, W. (2024, March 21). The NSA Wants a ChatGPT For Spooks. Fast Forward. Wired. Artificial Intelligence Security Center #aisc https://www.nsa.gov/AISC/ #ai #generativeai #llm #rag #NSA #aisecurity #publicprivatepartnership #emergingtechnologies

Yes, Apple has plans to enhance Siri with capabilities similar to ChatGPT. At the 2024 WWDC, Apple announced a significant upgrade to Siri, incorporating elements of OpenAI's ChatGPT technology. This integration will allow Siri to perform more complex tasks, offer better contextual understanding, and provide more human-like interactions. The upgraded version of Siri, enhanced with generative AI capabilities, is expected to be available later in the fall of 2024, alongside iOS 18.1. Apple is focusing on making Siri not just a voice assistant but also a more interactive and intelligent system, similar to ChatGPT, with improvements in natural language processing and context awareness. Read my blog post to learn more: https://lnkd.in/emH5xeda This integration reflects Apple's ongoing efforts to improve Siri by leveraging advanced AI models while maintaining a strong emphasis on privacy and on-device processing for basic tasks, with cloud processing reserved for more complex requests.

𝗔𝗜 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗧𝗿𝗲𝗻𝗱𝘀 𝟮𝟬𝟮𝟰: 𝗠𝗮𝗿𝗸𝗲𝘁 𝗢𝘃𝗲𝗿𝘃𝗶𝗲𝘄 & 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀 According to Immuta’s 2024 State of Data Security Report, 80% of data experts agree that AI is making data security more challenging. Read the complete blog to learn about Latest AI Security Trends in 𝟭. 𝗠𝗮𝗿𝗸𝗲𝘁 𝗢𝘃𝗲𝗿𝘃𝗶𝗲𝘄  90% of organizations are actively implementing or planning to explore large language model (LLM) use cases, while only 5% feel highly confident in their AI security preparedness. (Lakera) 𝟮. 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗖𝗼𝗻𝗰𝗲𝗿𝗻𝘀 Enterprises are blocking 18.5% of all AI and machine learning (ML) transactions—a 577% increase in blocked transactions over nine months—reflecting growing concerns around AI data security and companies’ reluctance to establish #AI policies. (Zscaler)    𝟯. 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗥𝗲𝗴𝘂𝗹𝗮𝘁𝗶𝗼𝗻 The European Union (EU) is leading the way in establishing comprehensive regulations for AI, with the EU AI Act highlighting its commitment to safe and ethical AI development. 𝟰. 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁𝘀 #Data leaders are also interested in the potential for AI as a data security tool. Respondents say that some of the main advantages of AI for data security operations will include: (Immuta) 1. #Anomalydetection (14%) 2. #Securityapp development (14%) 3. #Phishing #attack identification (13%) 4. #Security awareness training (13%) #AI #Security #Innovation #GenAI #Cybersecurity #Lakera

2024 the year of Artificial Intelligence (AI) privacy breaches. 2024, the year of AI governance. 2024, the year of AI data privacy, data security and ethics. As AI technology continues to evolve, new ethical and regulatory challenges are emerging around the globe. As a data practitioner, it is important to have a clear understanding of the AI data privacy and security landscape to manage potential risks effectively. Here are a few ways to secure AI data: 1. Encryption and Access Controls 2. Data Masking 3. Data Loss Prevention 4. Security Information and Event Management Systems 5. Regular Security Testing Protecting your data’s privacy and security in AI is a crucial step to ensure the integrity of your data and to comply with the global regulatory policies. Stay ahead of the game by keeping up with the latest trends and developments in AI data privacy and security.

🚨 Breaking News in Artificial Intelligence Security 🚨 #AI #Cybersecurity #OpenAI In an unsettling development, OpenAI, a leading force in the realm of artificial intelligence and the creator of ChatGPC, suffered a security breach in April 2023. A hacker managed to penetrate OpenAI’s internal messaging system, gaining unauthorized insights into the company's advanced AI technologies. Fortunately, the intrusion did not result in the theft of any code crucial for building their AI models, nor was any sensitive customer or partner data compromised. 🔐 Why It Matters: This incident raises formidable questions about the protocols OpenAI employs to handle security breaches and their decision not to inform law enforcement or the public. In the digital age, the protection of intellectual and operational data is paramount, especially for entities like OpenAI that lead innovations shaping our interaction with technology. 🔍 Behind The Scenes: The breach allowed the hacker access to private discussions among employees on a specialized forum, revealing the nuanced details of OpenAI's latest technological advancements. Although the direct impact was contained, the exposure of such conversations is a glaring breach of internal security. 📉 The Response: After identifying the breach, OpenAI opted for silence, not deeming it a national security threat and citing the non-theft of customer data as justification. This discretion brings their commitment to transparency and data security under scrutiny, sparking debates on corporate responsibility in handling sensitive information. 💡 Moving Forward: OpenAI has since ramped up their security measures across the organization. As AI technologies continue to evolve, the necessity for robust, transparent, and responsive security frameworks becomes increasingly critical. 🤔 Thoughts? As we navigate these complex issues, the importance of transparency and security in AI cannot be overstated. What measures can AI companies take to enhance their security frameworks? Join the conversation below! #TechNews #ArtificialIntelligence #DataSecurity #EthicsInAI

The fundamental problem is that every machine-learning algorithm has to be trained on data — lots and lots of data. The Pentagon is making a tremendous effort to collect, collate, curate, and clean its data so analytic algorithms and infant AIs can make sense of it. In particular, the prep team needs to throw out any erroneous datapoints before the algorithm can learn the wrong thing. “Any commercial LLM [Large Language Model] that is out there, that is learning from the internet, is poisoned today,” stated Jennifer Swanson, the deputy assistant secretary of the US Army for Data, Engineering and Software. I am honestly more concerned about what you call, the ‘regular’ AI, because those are the algorithms that are going to really be used by our soldiers to make decisions in the battlefield.” So various AI will be represented and, in this Peter Cox, has stated that a ‘Large Event Model’ (LEM) in cyber defence is preferred for 3 reasons: 1.     It’s closer to LLM which is now generally accepted (if not understood). 2.     An event is not significant until some analyses have been completed, so we need to collect a large set of data, the analysis will identify significant events. 3.     Snitch (the global discovery dB showing IP call fraud with over 5 billion attacks is a starting point for LEM.) Live now at www.um-labs.com Many AI systems operate using a Large Language Model (LLM), LLM is basically a large data set relevant to the domain in which the AI system operates. A large collection of natural text, often generated by scanning the Internet, is a common choice. When AI is applied to cybersecurity, an LLM is not the best choice. Implementing cybersecurity controls means validating attempts to interact with a software system implementing a well-defined application protocol and validating information flows generated by those protocols. This means that, by definition, the language model for those interactions is restricted. A better basis for applying AI to cybersecurity is to build a Large Event Model (LEM). Using IP telephony as an example a LEM will collect data on events such as successful and failed calls a collate the sequence of events. Event data includes location and identify of the caller and call recipient. With this approach, an AI engine will detect attempted security breaches and identify abnormal behaviour providing an early warning of malicious misuse. #kpn #hsd #btgroup #awswavelength #awsapn #microsoft #NVIDA #ai #ml #lem #llm #royalairforce #defencedigigital #commercialX #youradf #ads #techuk #bcs #ncsc #nist #dod #mod #atos #eviden #metaverse #pwc #xr #ar #5g #redcap #privatelte #wifi6 #wifi7 #systemonchip #edge #iot #cctv #drones #bodycam #police #metpolice #politie #cabinetoffice #fcdo #fco #ukhomeoffice #dbt #nttdata #ciso #cisos #cisco

Manipulation, Misinformation, and Security Risks in AI AI's capabilities extend to generating deepfakes and spreading misinformation, which can have detrimental effects on society. These technologies can erode trust and manipulate public opinion. Additionally, AI systems are vulnerable to adversarial attacks, where input data is subtly altered to deceive the AI. Key Points: -Deepfakes and Misinformation: AI can create convincing but false content, spreading misinformation and eroding trust. -Behavioural Manipulation: Personalised content can exploit psychological vulnerabilities, manipulating behaviour. -Security Risks: AI systems are susceptible to adversarial attacks, and the automation of harmful actions like cyber-attacks poses significant threats. Addressing these issues requires stringent security measures and ethical guidelines to prevent misuse. Let's work together to ensure AI is used responsibly and ethically.

A recent article in The Guardian https://lnkd.in/epDVZ3Dq highlights a critical concern that underscores this need: AI chatbots, despite sophisticated safeguards, can have vulnerabilities that are easily bypassed. This brings to light the broader issue of data security and the imperative for businesses to protect their sensitive information effectively. AI chatbots are increasingly integral to customer service, data management, and automated tasks across various industries. However, the ability of researchers to bypass these safeguards illustrates a potential risk to data integrity and privacy. If chatbots can be manipulated, the data they access and manage could be compromised, leading to severe consequences for businesses, including data breaches and loss of confidential information. This is where digital document storage solutions come into play. Properly implemented digital document storage provides a secure, organised, and efficient way to manage business documents. These systems offer several key advantages that can mitigate risks associated with AI vulnerabilities: Enhanced Security: Digital document storage solutions are equipped with advanced security features such as encryption, access controls, and audit trails. These measures ensure that sensitive information remains protected from unauthorised access and potential cyber threats. Reliable Backup and Recovery: In the event of a data breach or system failure, digital document storage systems offer reliable backup and recovery options. This ensures that critical business documents are not lost and can be quickly restored, minimizing downtime and operational disruptions. Improved Compliance: Businesses must adhere to various regulatory requirements regarding data protection and privacy. Digital document storage solutions help maintain compliance by providing features that support data retention policies, access logs, and secure document disposal. Efficient Document Management: Digital storage systems streamline document management processes, making it easier to organise, retrieve, and share documents. This not only enhances productivity but also ensures that the right people have access to the right information when needed. Scalability and Flexibility: As businesses grow, their document management needs evolve. Digital document storage solutions offer scalability and flexibility, allowing businesses to adjust their storage capacity and features according to their changing requirements. Digital document solutions - makes sense, doesn't it? #AISafeGuards #DataStorage #DigitalDocumentSolutions

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

The formation of the Coalition for Secure AI (CoSAI) marks a significant step towards standardizing AI security across the industry. This consortium, which includes AI giants like Google, OpenAI, Anthropic, Microsoft, IBM, Intel, Nvidia, and PayPal, aims to develop tools and best practices to secure AI applications. Creating a Secure AI Ecosystem CoSAI's initial efforts focus on AI and software supply chain security, along with preparing defenders for the evolving cyber landscape. The coalition is set to establish a secure environment with robust checks and balances to protect AI models from cyberattacks. This initiative is crucial as generative AI continues to advance, posing new cybersecurity challenges. Importance of AI Safety Since the launch of ChatGPT, AI safety has become a paramount concern, raising issues like social engineering, misinformation through deepfakes, and the ethical implications of AI decisions. The coalition's framework aims to address these concerns by ensuring AI systems are secure and reliable. Government and Industry Collaboration US President Joe Biden's executive order in July 2023 emphasized the need for AI safety and ethics, urging the private sector to develop and share safety standards. CoSAI's collaboration with organizations like the Frontier Model Forum, Partnership on AI, OpenSSF, and MLCommons reflects a broader commitment to establishing common standards and mitigating AI risks. Autonomos.AI’s Role in Enhancing AI Security Autonomos.AI can play a crucial role in this initiative by leveraging its AI-driven capabilities to enhance security measures. With advanced anomaly detection and real-time monitoring, Autonomos.AI can help organizations identify and respond to potential threats swiftly. Its continuous learning and adaptive algorithms ensure that security protocols evolve alongside emerging AI technologies, providing a robust defense against cyber threats. Conclusion The launch of CoSAI represents a concerted effort by leading AI companies to prioritize security and ethical standards. By developing comprehensive frameworks and collaborating with governmental and industry partners, the coalition aims to safeguard AI applications against misuse and ensure their responsible deployment. With the integration of advanced AI security solutions from companies like Autonomos.AI, the industry can build a more secure and trustworthy AI landscape. #AIsecurity #CoSAI #AutonomosAI #Cybersecurity #AIethics #AIstandards #TechInnovation #CyberDefense #AItech #supplychainsecurity #genAI #socialengineering #aidriven