Headlines- In the war-torn Gaza Strip, where about two-thirds of the population struggles to obtain food, the United Nations World Food Program (WFP) has been forced to reduce its monthly food aid, the organization announced on Monday.
- As attacks on shipping continue, Iran's Islamic Revolutionary Guard Corps claims that an oil tanker "violating regulations" caught fire after striking a sea mine in the Strait of Hormuz.
- Two troops have died in a helicopter crash in Najran, Saudi Arabia, according to the Saudi-led coalition fighting in Yemen, which also claims to have downed more drones close to Riyadh.
- After riots, looting, and arson during cost-of-living protests, nearly 2,400 people were detained throughout France.
- Israeli Prime Minister Benjamin Netanyahu has received the "complete and total" support of US President Donald Trump.
- Giorgia Meloni, the prime minister of Italy, denounced rioting during cost-of-living protests on Sunday and expressed support for law enforcement after clashes in multiple cities.
- Eight cases of Ebola have been confirmed in Kenya as of Sunday, according to the country's Health Ministry.
- After a fatal fire at a Canadian military base on Sunday, 39 people were admitted to the hospital, at least 19 of whom were in critical condition.
Tag: Prevent Cyber Crime
Multi-Layered Verification Strategy
Several cutting-edge technologies are combined in a multi-layered verification strategy to identify and prevent fraudulent attempts at every step of the customer journey. Document validation, biometric comparison, device or location signals, and behavioral biometrics are examples of multi-layered identity verification.
Foundation Models
Strong artificial intelligence (AI) models that can be tailored to a variety of tasks are foundation models. They are trained on vast amounts of data.According to the experts, a general contextual understanding of patterns, structures, and representations is built into foundation models.
NDR and ITDR
One type of cybersecurity solution called network detection and response (NDR) helps defend network infrastructure from both known and unknown threats. To help organizations and businesses in identifying, isolating, and mitigating network-related risks, it makes use of machine learning (ML), active monitoring, behavioral analytics, and other integrated capabilities and technologies.
LLM Phishing
Large Language Models (LLMs) are used in LLM phishing to generate grammatically correct, highly convincing phishing and social engineering campaigns on a large scale.Fruadsters can generate customized lures in a matter of seconds, mimic professional writing styles, and scan public data by using sophisticated LLMs.
AI-Powered Mortgage Fraud
The use of generative AI tools to create identity documents, payslips, bank statements, and tax returns in order to qualify for rental properties or mortgage loans that the applicant would not otherwise be able to is known as AI-powered mortgage and rental fraud.
Buy Now Pay Later Fraud
Any fraudulent activity involving Buy Now Pay Later is referred to as Buy Now Pay Later Fraud (BNPL). In this fraud either fraudsters target payment systems or they take advantage of BNPL providers’ and merchants’ onboarding procedures.
Backpropagation
Gradient descent is used in the backpropagation (Backward Propagation of Errors) algorithm for supervised artificial neural network learning.Backpropagation is a process of analyzing errors, comparing them to the anticipated response, and re-running the model until it produces the desired outcome.
AI Fluency
The ability to work effectively and ethically with AI systems by comprehending their potential, constraints, and ramifications is known as “AI fluency.”AI fluency helps users in identifying when outputs require human review, verification, or correction, particularly in important sectors.
Payroll Fraud
When an employee uses the company’s payroll system to embezzle funds, this is known as payroll fraud.Payroll fraud can be committed by both employers and employees by paying fictitious or fired employees, issuing unapproved bonuses, or fabricating timesheets.
Synthetic Identity Fraud
Synthetic identity fraud is the method of fraudsters creating completely new identities by fusing false information with real data, as opposed to stealing a real person’s entire identity.