OJTS OJT students of Bitstop Network Services, Inc. are from different Universities and Colleges of the P

Update from the interns working on the "Power Theft Detection using Arduino Sensors"
17/07/2026

Update from the interns working on the "Power Theft Detection using Arduino Sensors"

Update from the interns working on the "Evil Twin Detection using AI"
17/07/2026

Update from the interns working on the "Evil Twin Detection using AI"

Update and visuals from the WiFi Radar/Fall Detection Team's work :
17/07/2026

Update and visuals from the WiFi Radar/Fall Detection Team's work :

Our congratulations (for completing the internship) to the UPANG team interns that worked on Shadow IT/AI detection (L-R...
06/05/2026

Our congratulations (for completing the internship) to the UPANG team interns that worked on Shadow IT/AI detection (L-R Joshua V. Sebastian, Albert L. Tirao, Sweet Lana M. Sison, Marvin John D. Macam)

29/04/2026

Incoming Batch of Interns will work on these 3 R&D projects:
1. Detecting Power Theives using IoT
2. Fall detection using Wifi Signals
3. Detecting rogue WIFI routers using AI

Send a message to learn more

Using Dynamic Blockist to counter 0-day attacks - R&D project from ISAP interns.THE PROBLEM of "Zero-Day" Threat:A zero-...
15/04/2026

Using Dynamic Blockist to counter 0-day attacks - R&D project from ISAP interns.

THE PROBLEM of "Zero-Day" Threat:
A zero-day attack uses a previously unidentified vulnerability or malware artifact that has no known signature

The Danger: Traditional security relies on "signatures" (like a digital fingerprint) to recognize threats. Because zero-day attacks are brand new, signature-based defenses are often too slow, leading to a successful infection rate of over 50%.

The Speed Gap: It can take days, weeks, or months to develop a manual patch for a new exploit—way too slow for the internet’s fluid environment.

The Solution is to track the "Where" instead of the "What"
IP-Based Reputations: Instead of trying to identify every new piece of malware (the "what"), dynamic blocklists track hostile servers (the "where")
IP Reputation Services (TRS): These automated systems assign scores to IP addresses based on their behavior. If a server is known to be hostile, it gets a bad reputation score

Force Multiplier: This automated approach acts as a "force multiplier" for security teams, protecting the network at the speed of detection rather than manual investigation!

Enterprise network security is often bypassed by shadow IT/AI. That is why we have an R&D team from University of Pangas...
15/04/2026

Enterprise network security is often bypassed by shadow IT/AI. That is why we have an R&D team from University of Pangasinan working on detecting unauthorized devices/applications/AI use.

The ISAP Interns making up the IP Telemetry Analysis team and their ML Analytics output for Traffic Classification:
15/04/2026

The ISAP Interns making up the IP Telemetry Analysis team and their ML Analytics output for Traffic Classification:

Shadow INFRA detection Dashboard:
16/02/2026

Shadow INFRA detection Dashboard:

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