Gradian’s Post

🌐 Thrilled to complete the course "Introduction to Data Protection and Privacy" on Coursera! 🎉 With the growing adoption of AI in healthcare, securing sensitive data has never been more critical. This course has equipped me with key strategies for: 🔐 Data masking and encryption to protect patient information 🚪 Advanced access control measures to ensure data integrity 📂 Data isolation and backups for robust system resilience ⚡ Proactive incident response plans for rapid and effective action As AI continues to transform healthcare, maintaining trust through strong data protection is essential. These insights will play a vital role in helping healthcare organizations leverage AI while ensuring privacy and security. I'm excited to contribute to building AI-driven, secure healthcare solutions! 💼🚀 Sanofi Coursera #AIinHealthcare #DataPrivacy #DataProtection #HealthcareInnovation #Cybersecurity #HealthTech

🔒 Strengthening Privacy in Federated Learning: A Comprehensive Approach! 🔒 Last week, we unveiled how a malicious server could compromise the privacy of Federated Learning by exploiting gradient information to recover original data. How do we prevent this? The key lies in having clients encrypt their gradients before sending them to the server. This encryption must not obstruct the server's ability to aggregate data. One particularly effective method for this is Shamir Secret Sharing. Shamir Secret Sharing is fundamental to VeriQloud's Qasmat software, which facilitates secure distributed storage. This innovative solution enables users to distribute data across multiple servers within a Qasmat cluster, ensuring that no single server has enough information to reconstruct the original data. In fact, each server individually holds no information about the dataset. Additionally, we can repurpose a Qasmat cluster for storage as an aggregation cluster. Instead of relying on a single server, clients send Shamir secret shares to multiple servers, allowing them to perform aggregation securely. Clients can then reconstruct the complete gradient from the shares received, enabling model updates while safeguarding privacy. As long as the servers remain non-communicative, they cannot extract any information about the client’s data. The workflow for this blind version of Federated Learning closely mirrors the standard approach, now requiring at least two servers. Clients will encrypt their data before transmission and decrypt it upon receipt, while standard machine learning operations continue unaffected. Stay tuned for next week! We will showcase how standard machine learning libraries can be integrated with Qasmat's cryptographic methods to implement blind Federated Learning effectively. #DataPrivacy #FederatedLearning #CyberSecurity #MachineLearning #Qasmat

Day 7 of Week 4: Cybersecurity Awareness Month 🔐 To close this week of Cybersecurity Awareness Month, let’s discuss the evolving landscape of Cybersecurity Skills for the Future. 🌐👨💻👩💻 As technology advances, so do the skills needed to secure it. The future of cybersecurity will demand professionals who not only understand current threats but are also prepared to tackle the unknowns of tomorrow—like quantum computing, AI-driven attacks, and advanced biometrics. Key skills for future cybersecurity professionals include: 1. AI and Machine Learning: As AI is increasingly used in both attacks and defenses, knowledge in these areas will be crucial. 2. Quantum-Safe Encryption: Preparing for the potential impact of quantum computing will be essential for future-proof encryption strategies. 3. Risk Management and Privacy: As data privacy becomes a focus, understanding data protection laws and privacy by design will be highly valuable. 4. Threat Intelligence and Incident Response: Rapid detection and response will always be a core skill for cybersecurity experts. Investing in these skills today can help ensure we’re prepared for the cybersecurity challenges of tomorrow. 🌍🔐 #CyberSecurityAwareness #CyberSecurityMonth #FutureSkills #EmergingTech #DataProtection #QuantumComputing #AI #CyberTalent

Breaking the Privacy of Federated Learning: The Hidden Threats! At VeriQloud, we take data privacy seriously. Today, we kick off a special 3-part series focused on a critical vulnerability in Federated Learning. What is Federated Learning? It’s a method where devices work together to train a machine learning model—without sharing their raw data. Each device keeps its data local, only sending model updates (gradients) to a central server, which aggregates them into a global model. The Hidden Risk: While this sounds secure, here’s the problem: hackers who gain access to the server can reverse-engineer these gradients to reconstruct your original data! Our engineers ran a real-world test, using nothing but public algorithms and a simple laptop, and they were able to shatter privacy in minutes. Why Does This Matter? Consider the sensitive applications of Federated Learning—like medical data, energy consumption, or personal finance. Without strong privacy, these revolutionary use cases are simply too risky. What’s Next? Next week, we’ll reveal a powerful yet simple solution that makes Federated Learning truly privacy-proof—and it’s easier than you think! Stay tuned to learn how Qasmat ensures your data stays secure, no matter what. #DataPrivacy #FederatedLearning #CyberSecurity #MachineLearning #QuantumSecurity

Day 7 of Week 4: Cybersecurity Awareness Month 🔐 To close this week of Cybersecurity Awareness Month, let’s discuss the evolving landscape of Cybersecurity Skills for the Future. 🌐👨💻👩💻 As technology advances, so do the skills needed to secure it. The future of cybersecurity will demand professionals who not only understand current threats but are also prepared to tackle the unknowns of tomorrow—like quantum computing, AI-driven attacks, and advanced biometrics. Key skills for future cybersecurity professionals include: 1. AI and Machine Learning: As AI is increasingly used in both attacks and defenses, knowledge in these areas will be crucial. 2. Quantum-Safe Encryption: Preparing for the potential impact of quantum computing will be essential for future-proof encryption strategies. 3. Risk Management and Privacy: As data privacy becomes a focus, understanding data protection laws and privacy by design will be highly valuable. 4. Threat Intelligence and Incident Response: Rapid detection and response will always be a core skill for cybersecurity experts. Investing in these skills today can help ensure we’re prepared for the cybersecurity challenges of tomorrow. 🌍🔐 #CyberSecurityAwareness #CyberSecurityMonth #FutureSkills #EmergingTech #DataProtection #QuantumComputing #AI #CyberTalent

This week in cybersecurity from the editors at Cybercrime Magazine – Read the Full Radiology Today Story Sausalito, Calif. – Oct. 7, 2024 Arguably the biggest single challenge for healthcare providers making their way through the Digital Age is especially near and dear to Vikram Chhabra, general manager of diagnostics products in Microsoft’s health and life sciences division in Burlington, Mass. That would be cybersecurity. Radiology Today reports that Chhabra mastered the art, science and oversight of the discipline, largely while at Cisco (2001 to 2017) and IBM (2017 to 2021). Even so, he remains humbled enough by the scope and persistence of the threat to admit that the learning curve never flatlines. “The frontier of large language models is very new and very attractive to bad actors,” he says. The good news, he suggests, is that Microsoft is as methodical and nimble a force as there is in the war between the good guys and the cybercriminals. And its sheer size can be an advantage. That’s important since financial damages caused by organized gangs and other malicious hackers are projected to top $10.5 trillion by next year, making cybercrime the third largest source of economic impact in the world after the U.S. and China, Chhabra notes, citing a 2024 report from Cybersecurity Ventures. At Microsoft, he says, investing in cybersecurity is a business decision and a CEO-level mandate. Please follow Hardial Singh  for such content. #linkedIn #Cybersecurity #informationsecurity #cloudsecurity #datasecurity #cybersecurityawareness #Data #Bigdata #Hadoop #Enterprisedata #Hybridcloud #Cloud #Cloudgovernance #Devops #Devsecops #Secops #cyber #infosec #riskassessment #informationsecurity #auditmanagement #informationprotection #securityaudit #cyberrisks #cybersecurity #security #cloudsecurity #trends #AWS #EC2 #AWSStorage #Cloudstorage

The rapid development of technology has dramatically changed the cybersecurity landscape, requiring organizations and individuals to change the way they approach their digital security. As data breaches and cyberattacks become more common, it is important for stakeholders to make cyber security a key part of their management strategies. The consequences of ignoring this important aspect can be dire, from financial loss to reputational damage, highlighting the urgent need for cyber security measures. Furthermore, as our reliance on digital systems increases, the sophistication of cyber threats increases. Attackers use advanced techniques such as artificial intelligence and machine learning to exploit vulnerabilities in computers and networks (McKinsey and Company, 2020). This evolving threat landscape demands that organizations not only invest in cutting-edge technologies but also foster a culture of cybersecurity awareness among employees. Training programs that educate staff about potential risks and safe practices are essential for mitigating human error—a leading cause of data breaches. Furthermore, regulatory frameworks are increasingly emphasizing the importance of robust cybersecurity practices. Governments worldwide are implementing stricter regulations aimed at protecting sensitive information and enforcing accountability among businesses. Organizations that proactively adapt to these changes will not only comply with legal obligations but also enhance consumer trust and loyalty through demonstrated commitment to safeguarding personal data. As a result, transitioning to a cybersecurity priority is no longer optional. It is essential for sustainable business operations in today's digital world. By embracing these developments, organizations can better protect themselves against new threats and at the same time build trust with customers and stakeholders. #CyberSecurity #ml #DL #AI #DataScience

The Role of Machine Learning in Cybersecurity : Machine Learning (ML) is a game-changer in cybersecurity, enabling systems to learn from data and improve defenses over time. Here’s how ML enhances cybersecurity: 1. Predictive Analytics : ML algorithms analyze historical data to identify patterns and predict potential threats before they manifest. 2. Automated Threat Detection : Tools like “Darktrace” use ML to autonomously detect anomalies and adapt to new threats, improving response times significantly. 3. Fraud Detection : ML is utilized in financial sectors to identify fraudulent transactions in real-time by learning what constitutes “normal” behavior. → Tool: IBM Watson for Cyber Security” leverages ML to analyze vast amounts of data, providing insights into emerging threats and trends in cybersecurity. Understanding and implementing ML can significantly bolster your organization’s defenses. Day-06/30 AISecurity

The rapid evolution of technology has moved leaps and bounds in the last 50 years and never has that been more evident than with the more recent advancements in AI. Over the last 5 years, the shift towards digital infrastructure as demanded by hybrid and remote work has underscored the critical need for efficiently accessible and secured resources and the timely introduction of AI has risen to meet some of those goals. This pacing of innovation continues to present the unwavering need for security, privacy and resiliency in our digital resources and frameworks. Security can never and should never be outpaced or sacrificed. With my cybersecurity education growing further in the distance and with the dynamic nature of technology, I recognize the need for a commitment to ongoing learning and growth in this field and will always be conscience of what I know, and certainly what I do not. In the spirit of continuing that education, I have successfully attained my first, in what I hope will be many, cybersecurity professional certifications. The Certified in Cybersecurity (CC) accreditation focuses on fundamental security operations and principles, serving as a solid foundation for future specialized security certifications. Continuing to be curious and vigilant are key in navigating the complex cybersecurity landscape. I am dedicated to staying informed, exploring new horizons, and reinforcing my expertise in safeguarding the tech that we all have come to rely on so entirely. #Cybersecurity #AI #DigitalInnovation #ProfessionalDevelopment #Certification #ISC2

Cybersecurity is a critical concern in today’s digital age, where organizations face an ever-evolving cyber threat landscape. This study explores the potential of leveraging artificial intelligence and Amazon Web Services to improve cybersecurity practices. Combining the capabilities of OpenAI’s GPT-3 and DALL-E models with Amazon Web Services infrastructure aims to improve threat detection, generate high-quality synthetic training data, and optimize resource utilization. This work begins by demonstrating the ability of artificial intelligence to create synthetic cybersecurity data that simulates real-world threats. These data are essential for training threat detection systems and strengthening an organization’s resilience against cyberattacks. While our research shows the promising potential of artificial intelligence and Amazon Web Services in cybersecurity, it is essential to recognize the limitations. Continued research and refinement of AI models are needed to address increasingly sophisticated threats. Additionally, ethical and privacy considerations must be addressed when employing AI in cybersecurity practices. The results support the notion that this collaboration can revolutionize how organizations address cyber challenges, delivering greater efficiency, speed, and accuracy in threat detection and mitigation. https://lnkd.in/dHzThz3E