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  1. In an age where data is often called "the new oil," safeguarding our personal information has become crucial to maintaining control over our lives and identities.

    Join @null_NEU for an enlightening presentation on data privacy by Naomi Brockwell, renowned tech journalist and privacy advocate. Learn essential strategies to protect your personal information in today's digital landscape.

    📅 Date: October 4th, 2024
    🕒 Time: 6 PM Onwards
    📍 Venue: West Village G-104, Northeastern University

    🎯 What you'll gain from attending:
    ✅ Expert insights on privacy importance
    ✅ Practical privacy protection strategies
    ✅ Contribution to privacy awareness efforts
    ✅ Professional development in data privacy
    ✅ Up-to-date information on privacy challenges

    Also, you can connect with like-minded individuals, expand your professional network, and forge valuable connections within the cybersecurity community. 🤝

    Limited Spots Available! 🚀 Register on Meetup to secure your place: meetu.ps/e/NvJpn/110Z9W/i

    #CybersecurityExperts #ProfessionalGrowth #nullCommunity #PrivacyFirst #DataProtection🛡️💻🔒

    cc: @null0x00 @nullBoston

  2. First was the workshop on continual learning in computer vision at #CVPR2024, with notable talks by Vineeth Balasubramanian (integrating explainability and privacy-awareness) and Elisa Ricci (class-incremental novel class discovery) youtube.com/watch?v=fQ_HZu-8eM (2/4) #AI

  3. ----------------

    🛠️ Tool
    ===================

    Opening — Purpose and scope

    Sniffnet is an open-source desktop application designed to let users monitor Internet traffic on their machines through a graphical interface. The project emphasizes usability, cross-platform availability, multilingual support and a set of UI-focused features such as an overview page, an Inspect view for connection details, notifications and a thumbnail mode for compact visualization.

    Key Features
    • User-facing traffic overview: a consolidated dashboard presenting active connections and bandwidth usage.
    • Inspect page: interactive view for investigating individual connections and associated metadata.
    • Notifications: configurable alerts for new connections or notable traffic events.
    • Visual modes: thumbnail mode and customizable themes for different display preferences.
    • Localization and sponsorship: translations into many languages and community/organizational sponsors supporting development.

    Technical implementation (conceptual)

    Sniffnet combines a native desktop UI with system-level traffic observation. Conceptually, the application collects network telemetry from the host OS, aggregates per-connection and per-application metrics, and presents them in a responsive GUI. Integrations referenced in project materials include third-party services for enrichment and sponsorship acknowledgements. The repo structure and screenshots indicate modular UI pages (Overview, Inspect, Notifications) and theming capabilities.

    Use cases
    • Rapidly visualizing which applications are generating outbound traffic on a workstation.
    • Investigating unexpected or high-volume connections via the Inspect page.
    • Receiving desktop notifications for new or suspicious connection events.
    • Demonstrating network behavior in privacy-awareness or troubleshooting workflows.

    Limitations and considerations
    • Platform-level capture capabilities depend on the host OS networking APIs and permissions; behavior may vary across platforms.
    • The project is presented as user-oriented rather than enterprise-grade packet capture/forensic tooling; depth of protocol analysis is not highlighted.
    • External enrichment services and sponsorships are noted, and privacy implications of any telemetry or third-party lookups should be considered based on deployment choices.

    Final note

    Sniffnet fills a niche for accessible, GUI-driven network visibility on the desktop, with a clear emphasis on user experience and localization. #tool #sniffnet #network_monitoring #open_source

    🔗 Source: github.com/GyulyVGC/sniffnet