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Comcast Is Turning Millions of Its Routers Into Motion Detectors

著者: BeauHD
2026年8月19日 07:00

🤖 AI Summary

Comcastは、数百万台のXfinityゲートウェイを対象にWi-Fi運動検知機能を活用し、ルーターが接続されたデバイス間の信号の不連続性により動きを検出するようになっています。この無料サービスは「Xfinity Shield」の一環として提供され、活動警報をXfinityアプリで送信します。ホームモード、エイウェイモード、およびナイトモードが用意されており、別々の運動センサーを必要としないです。The Vergeによると、この技術は長年にわたり存在していますが、最近になって正確で信頼できるものになり、普及に至りました。Linksysは2021年に類似のサービスを提供しましたが、数年後に中止しました。照明会社Wizは2023年にWi-Fiセンシングスマート bulbを発売し、最近ではPhilips HueもZigbeeを使用した類似の無線周波数検知技術を製品に導入しました。Comcastの運動感知機能はXfinityアプリの新しいモード(ホームウォッチ、エイウェイウォッチ、ダークウォッチ)と組み合わせて提供されており、ユーザーの活動に基づいてセンシングのオン/オフが可能になっています。
Comcast is activating Wi-Fi motion sensing on millions of compatible Xfinity gateways, allowing the routers to detect movement by measuring disruptions in signals between the gateway and connected devices. The free feature, part of Xfinity Shield, can send activity alerts through the Xfinity app and offers Home, Away, and nighttime monitoring modes without requiring separate motion sensors. The Verge reports: Wi-Fi motion sensing is a technology that has been around for a while, but it's only recently that it's become accurate and reliable enough to catch on. Linksys launched a similar service in 2021, but discontinued it a few years later. Lighting company Wiz launched a line of Wi-Fi-sensing smart bulbs in 2023, and more recently Philips Hue deployed a similar radio-frequency sensing technology in its products (using Zigbee rather than Wi-Fi). Comcast's motion sensing pairs with new modes in the Xfinity app -- Home Watch, Away Watch, and Dark Watch (a night/sleep mode) -- allowing you to turn sensing on or off based on your activities.

Read more of this story at Slashdot.

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

著者: EditorDavid
2026年8月16日 23:34

🤖 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.

DEF CON Crowd Suspected In Fake-Hotspot Attack On Delta Flight

著者: BeauHD
2026年8月13日 04:00

🤖 AI Summary

DEF CON会議終了の翌日、ダルタ便591でのフライト中のWi-Fi妨害事件が報告されました。飛行機内の乗客が偽のWi-Fiホットスポットを作り出し、「Delta WiFi Fast」と名付けた後、乗客の個人情報収集用にフィッシングページを設置したとされています。この技術は「evil twin」攻撃と呼ばれ、ITセキュリティコミュニティでは長年にわたり知られていました。

デルタ航空の声明によると、「搭乗者が提供・運営・供給していない無認可のWi-Fiネットワークが短時間で機内に存在した」という最初の見解が得られました。しかし、フライトの安全性は常に確保され、航空機のオペレーティングシステムにも影響はありませんでした。緊急事態は宣言されていません。

また、ダルタ側によると、実際のフライト中のWi-Fiは30分間停止されました。

この事件はDEF CON会議 Attendeesが起きた可能性があり、当局による注意を引きつけました。
An anonymous reader quotes a report from Ars Technica: On Monday, passengers aboard Delta flight 591 going from Las Vegas to Atlanta allegedly spoofed the onboard Wi-Fi, raising the attention of federal law enforcement. The incident came one day after the DEF CON security conference concluded in Las Vegas, and was first described on social media accounts that follow publicly available air-to-ground messages, known as ACARS. According to the "ACARS Drama" account, a message was sent by pilots from the plane stated: "NO INFO AS OF NOW WE HAVE A BUNCH OF PAX THAT WERE AT A CYBER CONFERENCE IN LAS THEY WERE ABLE TO JAM OUR WIFI AND BROADCAST THEIR SIGNAL." A description of the incident posted to Reddit further stated that these passengers created a fake hotspot ("Delta WiFi Fast"), with a phishing landing page "designed to harvest passengers' personal credentials." This technique, sometimes known as an "evil twin" attack, has been long-known to the IT security community. It involves setting up a fake Wi-Fi network and then capturing login credentials and other data. "One initial finding is an unauthorized WiFi network, which was not provided, operated, or supplied by Delta, was present onboard the aircraft for a short time during the flight," said a Delta spokesperson. Delta further noted that the flight's safety was "never in question and no aircraft operating systems were affected," and that no emergency was declared. Ars notes that the "actual onboard Wi-Fi was disabled for 30 minutes."

Read more of this story at Slashdot.

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