# Securing IoT: Mitigating Sybil Flood Attacks with Bloom Filters and Hash Chains
## 1 Introduction  
The proliferation of the Internet of Things (IoT) has led to the integration of countless devices into networked environments, enabling unprecedented levels of connectivity and automation. However, this vast network of interconnected devices also introduces significant security challenges, particularly in the context of data transmission and network integrity. With the rapid expansion of the IoT and its deep integration into various aspects of society, these networks present a vast attack surface for malicious actors. The limited capabilities of some devices might initially suggest a lower risk of data access due to restricted functionality [1]. However, it is crucial to recognize that even the most basic devices and networks require robust authentication and identity management for several key reasons encompassing both user-to-device and device-to-device communication. Unfortunately, applying conventional authentication techniques such as passwords, certificates, biometrics, and two-factor authentication (2 FA) to Internet of Things (IoT) settings presents numerous challenges. These challenges include insufficient computational resources for the complex operations involved, limited storage capacity on IoT devices, lack of precision in IoT biometric sensors, and difficulties in managing and distributing certificates across numerous devices [2, 3]. The rapid growth of the IoT has coincided with a significant increase in the adoption of Routing Protocol for Low-Power and Lossy Networks (RPL) as the primary routing protocol for IoT networks [4, 5]. While RPL may be the ideal choice for resource-constrained devices, its inherently trust-based model does not provide sufficient security guarantees in IoT environments, opening networks up to potential attacks such as sybil and flood attacks. Sybil attacks pose a severe threat to network security in IoT environments [6]. In such attacks, a malicious actor creates a multitude of fake identities to disrupt critical processessuch as voting or resource allocation. Sybil attacks are particularly concerning in IoT contexts due to their large number of low-power devices with limited security capabilities [7]. These compromised identities can present a distorted view of the network topology, granting the attacker control over multiple nodes and potentially disrupting network operations. Furthermore, sybil attacks can be leveraged to launch Denial-of-Service (DoS) attacks by overwhelming the network with illegitimate traffic. These vulnerabilities highlight the critical need for robust authentication techniques to prevent unauthorized devices from impersonating legitimate ones and manipulating the network for malicious purposes. Flood attacks, also known as Denial-of-Service attacks, aim to overwhelm a network or system with excessive traffic, rendering it unavailable to legitimate users [8]. The combination of a sybil attack and a flood attack is a particularly serious threat to IoT networks [9]. In this scenario, the attacker leverages the sybil attack to distribute the flood attack across a large number of seemingly legitimate nodes, making it extremely difficult to distinguish between legitimate and malicious traffic. This combined attack can severely degrade network performance, disrupt essential services and potentially compromising the overall security of IoT systems. Moreover, the weakened network defenses resulting from this attack create opportunities for further malicious activities, such as data breaches or unauthorized access attempts. To address these challenges and ensure secure authentication in IoT environments, this paper proposes a novel authentication and flood mechanism integrating Bloom filters and hash chains.