Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Identify and flag any files or user behaviors that present a significant risk warranting attention from business management. This user and entity behavior analytics (UEBA) system employs advanced, rule-driven modeling to analyze various data sources, helping to identify established behavioral norms and detect potentially harmful activities. By conducting thorough analysis, it can significantly lower the risk of insider threats, which are notoriously hard to identify due to the insider's familiarity with security protocols and their ability to circumvent them. Monitor for abnormal events, such as logins from user accounts belonging to former employees, users logging in from multiple locations at once, or unauthorized individuals accessing an excessive number of sensitive documents. Additionally, keep an eye on file-related risks, including unauthorized attempts to decrypt confidential information. User-specific risks should also be observed, such as an increase in the frequency of file decryption, an uptick in printing after business hours, or a rise in the number of files sent to external parties. Overall, this comprehensive approach aims to enhance organizational security by proactively identifying potential threats.
Description
LotusEye offers a cloud-based service for AI-driven anomaly detection that autonomously acquires knowledge of standard behavior from numerical or sensor data provided in CSV format and consistently computes anomaly scores to identify irregularities that could signify faults or unforeseen activities, delivering notifications and visual analytics without necessitating any machine learning expertise from users. The service accommodates both wide-format CSV files, where every row corresponds to sensor readings at specific timestamps, and long-format CSV files that include timestamp, sensor name, and value columns, allowing users to upload their data either through a simple drag-and-drop interface or via an API for automated processing on a scheduled basis. Once an AI model is trained using data from normal operations, users can then input test data to obtain calculated anomaly scores and view these results on dashboards featuring time-series graphs, threshold markers, and filtering options, which assist teams in identifying unusual trends and probing potential concerns swiftly. This streamlined process enhances operational efficiency and empowers teams to act on insights generated by the platform.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Google Sheets
No
Microsoft Excel
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$13 per month
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Fasoo
Country
United States
Website
en.fasoo.com/products/fasoo-riskview/
Vendor Details
Company Name
LotusEye
Country
Japan
Website
lotuseye.co.jp/