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Researchers Use Ordinary WiFi Connections to Create Images of Nearby People and Their Surroundings

🤖 AI Summary

WiFi信号を使用した人物画像生成と識別技術についての研究を紹介します。キーポイントは以下の通りです:

1. ユーザーが持つ不要なWi-Fiデバイス(スマートフォンやワッチなど)が必要なく、他の周囲にいる有効なデバイスからの無暗号化のビームフォーミングフィードバック情報(BFI)を分析することで、人物の画像を作成し、100%以上の精度で識別できます。

2. テストでは197人の被験者に対して実施され、様々な角度や歩き方に関わらず正確な結果が出ました。

3. これは「通常のカメラ」のように機能しますが、光ではなく無線電波を使用して認識します。

4. 研究者は、この手法は周囲に活動している他のデバイスがある限り、個人を識別するためのプロセスが数秒で完了します。これは機械学習モデルが既に人物を認識するために訓練された場合です。

5. 本研究はプライバシーへの深刻な懸念を引き起こす可能性があり、今後のWi-Fiセキュリティ対策の指針となるでしょう。
Science Daily reports: Researchers showed that unencrypted signals routinely exchanged between WiFi devices and routers can be used to create radio-based images of people and recognize them within seconds. In tests involving 197 participants, the system identified individuals with nearly 100% accuracy, even from different angles and regardless of how they walked. "By observing the propagation of radio waves, we can create an image of the surroundings and of persons who are present," says Professor Thorsten Strufe from KASTEL, KIT's Institute of Information Security and Dependability. "This works similar to a normal camera, the difference being that in our case, radio waves instead of light waves are used for the recognition," explains the cybersecurity expert. Because the technique analyzes radio waves moving through a space, a person does not need to have a phone, smartwatch, or other WiFi enabled device with them. "Thus, it does not matter whether you carry a WiFi device on you or not." Even turning off your own device would not necessarily prevent the system from working. "It's sufficient that other WiFi devices in your surroundings are active...." Connected devices routinely send information back to the router to help optimize wireless communication. These signals, known as beamforming feedback information (BFI), are transmitted without encryption, meaning that anyone within range can potentially read them. By analyzing that information, the system can generate images of people from multiple viewpoints. Those images can then be used to determine a person's identity. Once the machine learning model has already been trained to recognize individuals, the identification process takes only a few seconds.

Read more of this story at Slashdot.

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