However, one of the existing OSN challenges is the issue of fake accounts. Online social networks (OSN) are well-known platforms for exchanging various information.

Also, it shows that a valuable set of information can be extracted from encrypted WhatsApp and Telegram traffic. The proposed methodology's results enable investigators to detect and extract application user behavior that can be used as evidence for a forensics investigation.

The provided framework was tested by taking over 30 trace files of these activities and looking at some specific payload patterns. The presented framework enables the analysts to detect, classify and analyze encrypted traffic (typing, chatting, media transmission of audio and video calls, etc.). In this paper, we proposed a novel framework and methodology to extract a valuable set of information from encrypted traffic of Instant Messages and Voice Over IP applications. Most of the internet traffic is now encrypted, making the traditional analysis of contents impossible. Internet traffic and content analysis are leading tasks within this research area. It is also a major active research topic in the cybersecurity field. Digital forensics is one of the prime professional fields for law enforcement forces.

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