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بتمنى انته واني ماتفاركني ياعمري ثواني وماريد اشوف وجه ثاني بعدك ولا شي جاني. نصيبي ماراح وماكنت اتصور يكون نصيبي بهل الحلا شلون اعوف واحد.
Posted by Pure Machine Design on February 19, 2025 at 4:31am 0 Comments 0 Likes
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ContinuePosted by Pure Machine Design on February 19, 2025 at 4:30am 0 Comments 0 Likes
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To jam a 5G signal, an intelligent adversary can detect unencrypted synchronization signals to obtain the physical cell identity (PCI) and then launch a targeted cell phone jamming attack on the physical broadcast channel (PBCH). This intelligent jamming (PBCH-IJ) disrupts the master information block (MIB) decoding, leading to denial of services for users trying to access the PCI cell. The proposed method in the paper suggests detecting PBCH-IJ by analyzing the principal direction of PBCH demodulation reference signal space at the user side, as this direction is significantly impacted by PBCH-IJ under low mobility scenarios.
Jamming attacks on 5G signals can be executed by exploiting various vulnerabilities inherent in the 5G network architecture. One common method involves targeting the synchronization signal blocks (SSBs) during the initial access phase, as these blocks are unencrypted. An intelligent adversary can detect these signals to obtain the full physical cell identity (PCI) by sniffing, and then use the PCI to attack the physical broadcast channel (PBCH) extraction through targeted jamming. This type of PBCH intelligent jamming (PBCH-IJ) disrupts the decoding of the master information block (MIB), leading to severe denial of service for users attempting to access the PCI cell. Another approach involves using a multi-antenna jammer to interfere with the downlink signals from femto base stations (FBS) to femto users (FUs) in a two-tier 5G heterogeneous network (HetNet). This can be particularly effective in dynamic environments where traditional anti-jamming techniques like frequency hopping (FH) and direct sequence spread spectrum (DSSS) lack self-adaptive capabilities. To counteract such jamming, advanced techniques like federated deep reinforcement learning (DRL) have been proposed, which optimize beamforming and power allocation to improve the achievable rate at FUs despite the presence of signal jammer. Additionally, jamming detection in 5G can be enhanced by using the "EVM-vs-RB" measurement, which calculates the Error Vector Magnitude (EVM) for each Resource Block (RB). This method is more sensitive and informative, capable of detecting jamming even at high Signal-to-Jamming Ratio (SJR) values, which traditional metrics fail to identify. These methods highlight the sophisticated techniques adversaries can use to jam 5G signals and the equally advanced countermeasures required to mitigate such attacks.
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