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リアルタイムGPS偽造検出と暗号化されたUAS制御のための多層AIセンサーシステム

Ayoub Alsarhan1,2, Bashar S Khassawneh3, Mahmoud AlJamal4

  • 1Department of Data Science and Artificial Intelligence, Faculty of Information Technology, Al-Ahliyya Amman University, Amman 19111, Jordan.

Sensors (Basel, Switzerland)
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まとめ

本研究では,無人航空機システム (UAS) でのGPSの偽造を検出するためのAI駆動のセンサーフレームワークを提示しています. このシステムは,ドローンの安全なナビゲーションと通信を保証し,運用の安全性を高めます.

キーワード:
AI対応のセンサーが搭載されています.GPS/GNSS スプーフィング検出 スプーフィング検出微分可能なアーキテクチャ検索 (DARTS)エッジ/エンベデッドの推論軽量暗号法による暗号化.マルチセンサポジショニングとナビゲーションリアルタイムセンサー処理安全なコマンドとコントロールを確保する.センサデータ融合 センサデータ融合無人航空機システム (UAS) とは

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科学分野:

  • 航空宇宙工学 航空宇宙工学とは
  • 人工知能 (AI) とは,人工知能 (AI) のことです.
  • サイバーセキュリティー サイバーセキュリティー

背景:

  • 無人飛行システム (UAS) は,民間および国防部門において不可欠です.
  • 暗号化されていないGPS信号への依存は,UASを偽造攻撃に脆弱にし,安全と運用を脅かす.

研究 の 目的:

  • リアルタイムGPSスプーフィング検出のためのAI駆動の多層センサーフレームワークを導入し,UASでコマンド・アンド・コントロール (C2) をセキュアにします.
  • テレメトリの信頼性を高め,リソースが制限されているUASプラットフォームで安全な通信を可能にします.

主な方法:

  • GPSドリフトインデックス (GDI),統計的正規化,オーバーサンプリング,カルマンフィルタリング,クォーターニオンフィルタリングを備えた精巧なプリプロセッシングパイプライン.
  • 機内スプーフィング検出のための軽量ニューラルネットワークを生成するためのディファレンシブルアーキテクチャ検索 (DARTS).
  • PRESENT-128暗号化とCMAC認証により,セキュアなC2通信が可能になります.

主要な成果:

  • このフレームワークは,優れた検出精度 (99.99%),F1スコア (0.999),AUC (0.9999) を達成しました.
  • 低レイテンシー (1.79 ms) とエネルギーコスト (0.51 mJ) の安全なC2通信.
  • 現実の世界で,リソースが制限されているUAS環境に適性があることが実証されています.

結論:

  • AI駆動のフレームワークは,自動運転航空機のGPSスプーフィングに対抗するための堅牢でスケーラブルで安全なソリューションを提供します.
  • この研究は,強化されたUASのナビゲーションとセキュリティのために,AI対応のセンサーシステムを進歩させています.