## 1 Introduction  
Wireless communication advances from 3G to 5G have had an enormous effect on user experience, connection, and technology [1]. However, these progressions have also led to significant security challenges [2]. Despite the security advancements in 5G networks, approximately 70% of 5G operators have seen several security breaches, resulting in network outages, data leaks, and significant financial losses, according to a GlobalData research study conducted for Nokia [3]. Operators continue to report that their defenses lack the ability to address the new threats, almost five years after the initial 5G launch [4]. Drawing from experiences with earlier generations, it is expected that 6G will bring even more complex challenges for network operators. The introduction of advanced technologies in 6G could create new vulnerabilities, which cybercriminals may exploit. Moreover,the integration of massive IoT with 6G poses additional risks, as it significantly enlarges the attack surface, thereby complicating the security of an already intricate and widespread network infrastructure [5]. The ITU-R M.2160 framework's description of the integration of sophisticated technologies like terahertz (THz) transmission, Open Radio Access Networks (O-RANs), disaggregated Het-clouds, and native AI within 6G may create new security flaws that hackers might take advantage of [6]. For instance, the switch to O-RANs expands the attack surface while encouraging innovation by disassembling conventional network components into modular structures. Substantial supply chain risks are posed by this modular architecture, including the likelihood of compromised software and hardware from multiple manufacturers, irregular adherence to security standards, and vulnerabilities from integrations by third parties [7]. The combination of sensing and communication capabilities in IMT-2030, alongside AI, is expected to support new applications like digital twins, industrial automation, and personal health, which will pose significant security challenges [8]. While terahertz (THz) communication offers high data speeds and low latency, it is susceptible to denial-of-service assaults, eavesdropping, and signal interference [9]. Similarly, transmissions might be rerouted using Intelligent Reflecting Surfaces (IRSs), which can strengthen signals, disrupt communications, or permit man-in-the-middle attacks [10]. Massive MIMO (Multiple-Input Multiple-Output) technology improves network capacity, yet it additionally presents complicated safety issues, namely, pilot contamination and challenges in safeguarding multiple antennas [11]. The growing reliance on AI within 6G networks enhances performance optimization but raises concerns about algorithm manipulation and adversarial attacks [5]. Additionally, the use of disaggregated heterogeneous clouds increases the risk of cross-tenant attacks, insider threats, and vulnerabilities tied to virtualization [12]. Lastly, integrating native AI could introduce risks like model poisoning, adversarial attacks, and AI-generated malware [8]. Anticipated 6G use cases, like collaborative robotics, immersive communication (augmented and virtual reality), and native AI integration, are expected to exacerbate existing security risks and introduce new vulnerabilities. These innovations could expose sensitive biometric data, create opportunities for content manipulation, and lead to operational threats such as command injection and denial of service (DoS) attacks. AR/VR technologies are especially vulnerable to exploitation through data manipulation, where attackers could alter or inject sensory data, potentially causing severe harm to users' well-being [13]. Likewise, operational outages, hijacking, and other hacks could affect the performance of collaborative robotics, which depends on real-time interaction and coordination [14].