Legal Knowledge Management and the Rise of Artificial Intelligence
Robotic Refactoring the Workplace
"AI -The Future of Automotive Industry"
WiFi Networks: Shifting from Providing a Service to Improving the...
Breaking the Stereotypes in the Development of AI
Yves Jacquier, Executive Director, Production Studio Services, Ubisoft
Operationalize Machine Learning
Zongjie Diao, Director of Product Strategy and Management, Data Center Compute Group, CISCO
Where is AI Already Having an Impact on Business?
David Wirt, VP, ASEAN & Greater China, Pure Storage
Artificial Intelligence in the Biopharma and Healthcare Sector
Ronald Dorenbos, Associate Director Materials & Innovation, Takeda
Thank you for Subscribing to CIO Applications Weekly Brief
AI-powered Surveillance Revolutionizes the Connected Home Network Securities
AI fuels the home intruder-detection technologies, boosting in-house security.
FREMONT, CA: Consumers are increasingly worried about hacking their phones and information as they hear about more information breaches and problems like ransomware, identity theft, and botnet assaults. Data security issues have also been shown to boost with more linked device ownership. Enterprise safety apps have been using sophisticated AI for some time, but the consumer market's economic limitations make it difficult to pay for business-grade safety alternatives.
To provide endpoint safety, network security, and digital parenting, device identification on the home network is fundamental. Solutions differ from recognizing only fundamental MAC addresses to comprehensive device kinds, model, brand and operating system classifiers. When a security agent runs on the network and leverages cloud intelligence, it can tap on any endpoint link and see the header information with the device for every handshake protocol. The device information then tells a device profile that allows safety software to detect unreliable device behavior without needing to decrypt the data packets and examine them. This type of behavioral analysis of IoT devices identifies deviations from acceptable device behavior, alerts users, and network-infected devices that are quarantined. Some device categories, such as networked cameras, have a unique attack profile that often starts with camera remote access. Artificial Intelligence allows one-of-a-kind attack profiles to be learned, detected in real time by looking at target URLs and protocols used, and blocking approaches such as remote access security.
AI can also be used to filter web content, and sophisticated text analysis can be used to identify threats from cyberbullies and child abusers. Some extensive parental controls apply even outside the home network to mobile devices. Consumers have shown small interest in purchasing more robust safety alternatives that can safeguard home network and IoT devices as critical as network security is to the user experience.