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The Role of NLP in Monitoring Zoom Calls to Detect Twisted Language and Mob Speak

Bologna on 2023-08-22T20:31:00.000+02:00
by Angelo Reale
tags: cybersecurity, ai

Remote work has become a ubiquitous trend, owing to the technological advances of platforms like Zoom. With the increased reliance on video conferencing tools, companies have inevitably moved many of their operations online, including crucial business meetings and sensitive discussions. However, as the digital landscape expands, so does the potential for malicious activities.

In the age of asynchronous communication and varying time zones, written documentation is more essential than ever. While this ensures clarity and reference, while not doing so brings an underlying lurking risk: unscrupulous actors could exploit other mediums for their nefarious purposes.

What if criminals leverage Zoom and similar platforms to organize illegal activities, using twisted language or mob speak to veil their intentions? Here’s where Natural Language Processing (NLP) steps in.

What is Twisted Language and Mob Speak?

Before delving into the solutions, it's imperative to understand the challenge. "Twisted language" refers to the deliberate distortion of speech to convey covert meanings, often with criminal intent. Similarly, "mob speak" is a colloquial term that describes the coded language used by mobsters to communicate secretly.

How can NLP help?

  1. Real-time Monitoring and Analysis: Modern NLP algorithms can be trained to detect anomalies in speech patterns or peculiar phrases that deviate from typical corporate lingo. By analyzing live audio streams during Zoom calls, NLP can highlight potential risks for real-time intervention.

  2. Deep Learning Models: With advancements in deep learning, NLP models can be fine-tuned to recognize more subtle deviations in language patterns. These models can detect the nuanced use of twisted language or mob speak, even if they’re masterfully woven into innocent-sounding discussions.

  3. Historical Analysis: NLP isn’t just for live sessions. Recorded Zoom calls can undergo a detailed post-analysis, helping corporations identify patterns over time and possibly unveiling hidden networks of corrupt actors.

  4. Automated Reporting: Once suspicious language is detected, NLP systems can automatically generate reports, making it easier for security teams to review potential threats and take action.

The Ethical Considerations

While the use of NLP in monitoring communications can provide enhanced security, it also brings forth serious ethical implications:

  1. Privacy Concerns: Continuous monitoring of Zoom calls may infringe on employees' privacy rights. Companies must be transparent about the extent of monitoring and ensure that they adhere to data protection regulations.

  2. False Positives: No system is flawless. There's a risk of false positives, where innocent conversations are flagged. Such incidents can damage trust and morale within the company.

  3. Data Storage and Handling: Recorded Zoom calls contain sensitive information. Corporations must guarantee that this data is securely stored and accessed only by authorized personnel.

The rise of digital communication tools like Zoom offers both opportunities and challenges. As remote work becomes more prevalent, there's a pressing need to ensure that these platforms are not misused. With the help of NLP, corporations can add an extra layer of security, but they must tread carefully, balancing safety with privacy and trust. The future of corporate communication security may lie in the harmonious integration of technology and ethics.