Defaince’s Post

🔐 Enhancing Insider Threat Detection with Advanced AI Techniques 🔐 Insider threats—whether data breaches, ransomware, or extortion—pose serious challenges for organizations. This new study explores six experiments combining Natural Language Processing (NLP) with Machine Learning (ML) models like XGBoost and AdaBoost to analyze insider activities. By focusing on user sentiment and behavioral context, the research presents a robust, adaptable detection method. The innovative use of hyperparameter tuning and the red fox optimization algorithm significantly improved detection rates across email, HTTP, and file content scenarios. The results emphasize the importance of dynamic AI-based security solutions to reduce false positives and strengthen insider threat identification. Detailed article: https://lnkd.in/gssUtY9z 🚨 Embrace cutting-edge AI for smarter cybersecurity. Proactive defense is key to staying ahead! #Cybersecurity #AI #InsiderThreats #MachineLearning

AI chatbots are transforming business operations by handling customer inquiries, automating tasks, and delivering recommendations. But as their role grows, so does the need for robust cybersecurity. 🔍 Enter Prompt Engineering – a critical practice for penetration testers working to secure AI systems. What is prompt engineering? It’s the art of crafting specialised inputs to challenge, exploit, or manipulate AI models, uncovering vulnerabilities unique to language-based systems. Unlike traditional software testing, prompt engineering focuses on the logic of the AI model, evaluating its ability to handle complex or malicious inputs. Why is this important? AI chatbots rely on natural language processing (NLP), which makes them susceptible to attacks that bypass conventional security measures. By testing these systems with prompt engineering, businesses can identify and address weaknesses before attackers do. As AI continues to evolve, so must our approach to securing it. Prompt engineering isn’t just a tool; it’s a new frontier in cybersecurity. #CyberSecurity #AIChatbots #PromptEngineering #PenetrationTesting #AI How Penetration Testers Secure Your AI Chatbots with Prompt Engineering – CyberCrowd https://hubs.ly/Q02-x3rx0

🚨 Is AI training vulnerable to malicious attacks? 🤔🚨 As AI systems increasingly rely on vast datasets sourced from the web 🌐 and crowdsourcing platforms 👥, they become targets for poisoning attacks ☠️ — where bad actors may introduce false data to manipulate model outcomes 📉. Is such a process of obtaining data from thousands of people vulnerable to attack? What if a large organized group of people were employed in the process and wanted to smuggle in false annotations? 🤔 How can we protect AI from these threats? 🛡️ 🎯 We explore this problem in our latest paper published in Elsevier's Information Fusion (Impact Factor 14.7): 📄 Fortifying NLP models against poisoning attacks: The power of personalized prediction architectures Teddy Ferdinan, Jan Kocoń 🔍 Key insights: 🛡️ Personalized models like User-ID provide a robust shield against malicious data. 🏆 These models outperform standard ones, especially in high-intensity attack scenarios 🔥. ✅ Personalization enhances both prediction accuracy and resilience 💪 without sacrificing performance. 🏰 Our research shows that by adopting personalized approaches, we can fortify AI systems and ensure that they remain reliable, even when faced with malicious data. Interested in learning more? Check out the full paper! 📖 Link in the comments ⬇️⬇️⬇️ #AI #MachineLearning #NLP #Cybersecurity #AIResearch #DataPoisoning #Personalization

Simplify Cybersecurity: Empower Your SOC with Exabeam In a perfect world, your Security Operations Centre (SOC) would predict every cyberthreat and act instantly to prevent damage. But with the growing complexity of attacks, maintaining that defensive line has never been harder. Exabeam makes querying simple for everyone in the SOC—whether you’re a junior analyst or a CISO. With Natural Language Processing (NLP), Exabeam turns natural language questions into actionable insights, no technical query skills needed. This empowers teams to quickly perform searches and uncover context-rich answers to potential threats. When every team member can confidently query and respond, your entire organisation wins. Get in touch today ➡️https://bit.ly/3YKOnBO #ExabeamEXN #SOC

Simplify Cybersecurity: Empower Your SOC with Exabeam In a perfect world, your Security Operations Centre (SOC) would predict every cyberthreat and act instantly to prevent damage. But with the growing complexity of attacks, maintaining that defensive line has never been harder. Exabeam makes querying simple for everyone in the SOC—whether you’re a junior analyst or a CISO. With Natural Language Processing (NLP), Exabeam turns natural language questions into actionable insights, no technical query skills needed. This empowers teams to quickly perform searches and uncover context-rich answers to potential threats. When every team member can confidently query and respond, your entire organisation wins. Get in touch today ➡️https://bit.ly/3YKOnBO #ExabeamEXN #SOC

Simplify Cybersecurity: Empower Your SOC with Exabeam In a perfect world, your Security Operations Centre (SOC) would predict every cyberthreat and act instantly to prevent damage. But with the growing complexity of attacks, maintaining that defensive line has never been harder. Exabeam makes querying simple for everyone in the SOC—whether you’re a junior analyst or a CISO. With Natural Language Processing (NLP), Exabeam turns natural language questions into actionable insights, no technical query skills needed. This empowers teams to quickly perform searches and uncover context-rich answers to potential threats. When every team member can confidently query and respond, your entire organisation wins. Get in touch today ➡️https://bit.ly/3YKOnBO #ExabeamEXN #SOC

Simplify Cybersecurity: Empower Your SOC with Exabeam In a perfect world, your Security Operations Centre (SOC) would predict every cyberthreat and act instantly to prevent damage. But with the growing complexity of attacks, maintaining that defensive line has never been harder. Exabeam makes querying simple for everyone in the SOC—whether you’re a junior analyst or a CISO. With Natural Language Processing (NLP), Exabeam turns natural language questions into actionable insights, no technical query skills needed. This empowers teams to quickly perform searches and uncover context-rich answers to potential threats. When every team member can confidently query and respond, your entire organisation wins. Get in touch today ➡️https://bit.ly/3YKOnBO #ExabeamEXN #SOC

As generative AI advances, cyber threats grow more sophisticated and harder to detect, outpacing traditional security measures. That’s why harnessing AI for good is crucial. At Abnormal, we use advanced AI tools like natural language processing (NLP) to revolutionize email protection. Our platform analyzes vast amounts of email data, detecting subtle signs of malicious intent that might otherwise go unnoticed. Discover how we use NLP to defend against even the most advanced threats in our latest blog: https://lnkd.in/e7WTYnwY

At Abnormal, we use advanced AI tools like natural language processing (NLP) to revolutionize email protection. Our platform analyzes vast amounts of email data, detecting subtle signs of malicious intent that might otherwise go unnoticed. Check this blog out to learn more, and… Go ahead, be human. #AI #cybersecurity

Hello everyone!! Exciting News: Successfully Completed Spam SMS Detection Task with CodSoft in Machine Learning! Proud to share that I've recently wrapped up an engaging project with CodSoft , focusing on Spam SMS Detection using advanced Machine Learning techniques. Throughout this project, I dived deep into analyzing text data, extracting meaningful features, and building robust models to classify spam messages accurately. Key Highlights: •Conducted thorough exploratory data analysis to understand the characteristics of spam and non-spam messages. • Implemented state-of-the-art Machine Learning algorithms, including Natural Language Processing (NLP) techniques, for classification. • Achieved exceptional performance metrics through model optimization and ensemble learning. • Contributed to enhancing cybersecurity measures by effectively detecting and filtering out spam messages. This project not only strengthened my expertise in Machine Learning and NLP but also underscored the significance of combating cyber threats in our digital ecosystem. Grateful for the opportunity to collaborate with CodSoft and contribute to projects aimed at enhancing data security and privacy. Let's continue to leverage technology for a safer and more secure digital future! #MachineLearning #SpamDetection #Cybersecurity #CodSoft