Headlines- After riots, looting, and arson during cost-of-living protests, over 1,800 people were arrested throughout France.
- Authorities have detained a number of people in connection with a deadly stampede in Kolkata, in eastern India.
- Iran's Islamic Revolutionary Guard Corps navy issues a warning that the Strait of Hormuz is "closed," citing five tankers that have been hit since Friday.
- Four drones were intercepted and destroyed over the provinces of Riyadh, Eastern, and Southern, according to the coalition led by Saudi Arabia.
- The Saudi-led military coalition in Yemen claims to have intercepted three drones in the southern and Riyadh regions, two cruise missiles over the Red Sea, and a ballistic missile headed for the Saudi city of Yanbu. In the
- Just two days before the new sanctions and tariffs on Russia mandated by the law named for the late Senator Lindsey Graham were scheduled to go into effect, President Donald Trump signed an executive order on Friday waiving them.
- On Saturday afternoon, a car drove through a soccer match in Wichita, Kansas, killing a child and an adult and injuring numerous others.
Tag: AI
AI Red Teaming
The practice of adversarial testing designed specifically for AI systems to find weaknesses, security holes, and safety concerns before attackers take advantage of them is known as “AI red teaming.”
AI Guardrails
Artificial intelligence (AI) guardrails are the safeguards that ensure AI systems operate responsibly, safely, and within defined boundaries.By eliminating AI hallucinations, enforcing data privacy and regulatory compliance, detecting bias and guaranteeing fairness in decision-making, and providing real-time visibility into model behavior and results, AI guardrails help enforce the responsible use of AI.
AI Anomaly Detection
Finding data patterns using AI that deviate from expected normal behavior is known as AI anomaly detection, or AD.These irregularities may indicate fraud, technological issues, or unusual shifts in user behavior.
Anomaly Detection
The process for identifying data points in a dataset or system that deviate from the norm is known as anomaly detection.Anomaly detection systems can swiftly detect anomalous patterns or points that may indicate a potential threat or an ongoing cyberattack by using machine learning (ML) and artificial intelligence (AI) to identify deviations from normal behavior and events within a network or system.
AI Hallucination
When a model generates inaccurate, incorrect, or misleading outputs that are not supported by the input or training data, this is known as an AI hallucination. This usually occurs when the model identifies patterns improperly, producing unreliable or bias results.
Prompt Engineering
The instruction, query, or discussion topic users provide into a generative AI tool to receive a response is called a prompt. The ability to design and refine these inputs to direct the GenAI tool to produce precise, high-quality, and pertinent outcomes is known as prompt engineering.
AI TRiSM
AI TRiSM (Artificial Intelligence trust, risk and security management) is a framework that uses technical controls that uphold policies to manage the trust, risk, and security of AI systems.AI TRiSM helps organizations and businesses in managing security, risk, and trust in AI technologies.
AI-Powered DDoS Attacks and Prevention
AI-powered DDoS attacks are strategic, adaptive, and dynamic.Cyber attackers can use AI to analyze massive data sets in real time and find vulnerabilities across user devices at machine speed.Misconfigurations, under protected endpoints, and overlooked services can all be found by using AI.
AI Worm
An AI worm is a type of malware that propagates on its own and uses artificial intelligence to enhance its capabilities to evade detection.AI worms are capable of identifying vulnerabilities in systems, evading detection mechanisms, and carrying out highly targeted attacks.
AI Powered Threat Detection
AI threat detection uses automation, behavioral analytics, and machine learning to instantly detect cyber threats.The use of AI technologies, including as machine learning models, large language models (LLMs), and natural language processing (NLP), to augment and expedite up threat identification, investigation, and mitigation in real time is known as AI-driven threat detection and response.