Internet of Things (IoT) cyber threats, exemplified by jackware and crypto mining, underscore the vulnerability of IoT devices. Due to the multi-step nature of many attacks, early detection is vital for a swift response and preventing malware propagation. However, accurately detecting early-stage attacks is challenging, as attackers employ stealthy, zero-day, or adversarial machine learning to evade detection. To enhance security, we propose ARIoTEDef, an Adversarially Robust IoT Early Defense system, which identifies early-stage infections and evolves autonomously. It models multi-stage attacks based on a cyber kill chain and maintains stage-specific detectors. When anomalies in the later action stage emerge, the system retroactively analyzes event logs using an attention-based sequence-to-sequence model to identify early infections. Then, the infection detector is updated with information about the identified infections. We have evaluated ARIoTEDef against multi-stage attacks, such as the Mirai botnet. Results show that the infection detector’s average F1 score increases from 0.31 to 0.87 after one evolution round. We have also conducted an extensive analysis of ARIoTEDef against adversarial evasion attacks. Our results show that ARIoTEDef is robust and benefits from multiple rounds of evolution.
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Free, publicly-accessible full text available August 31, 2025
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Networks are today a critical infrastructure. Their resilience against attacks is thus crucial. Protecting networks requires a comprehensive security life-cycle and the deployment of different protection techniques. To make defenses more effective, recent solutions leverage AI techniques. In this paper, we discuss AI-based protection techniques, according to a security life-cycle consisting of several phases: (i) Prepare; (ii) Monitor and Diagnose; and (iii) React, Recovery and Fix. For each phase, we discuss relevant AI techniques, initial approaches, and research directions.more » « less
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The lack of authentication protection for bootstrapping messages broadcast by base-stations makes impossible for devices to differentiate between a legitimate and a fake base-station. This vulnerability has been widely acknowledged, but not yet fixed and thus enables law-enforcement agencies, motivated adversaries, and nation-states to carry out attacks against targeted users. Although 5G cellular protocols have been enhanced to prevent some of these attacks, the root vulnerability for fake base-stations still exists. In this paper, we propose an efficient broadcast authentication protocol based on a hierarchical identity-based signature scheme, Schnorr-HIBS, which addresses the root cause of the fake base-station problem with minimal computation and communication overhead. We implement and evaluate our proposed protocol using off-the-shelf software-defined radios and open-source libraries. We also provide a comprehensive quantitative and qualitative comparison between our scheme and other candidate solutions for 5G base-station authentication proposed by 3GPP. Our proposed protocol achieves at least a 6x speedup in terms of end-to-end cryptographic delay and a communication cost reduction of 31% over other 3GPP proposals.more » « less
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Digital signatures are a fundamental building block for ensuring integrity and authenticity of contents delivered by the Named Data Networking (NDN) systems. However, current digital signature schemes adopted by NDN open source libraries have a high computational and communication overhead making them unsuitable for high throughput applications like video streaming and virtual reality gaming. In this poster, we propose a real-time digital signature mechanism for NDN based on the offline-online signature framework known as Structure-free and Compact Real-time Authentication scheme (SCRA). Our signature mechanism significantly reduces the signing and verification costs and provides different variants to optimize for the specific requirements of applications (i.e. signing overhead, verification overhead or communication cost). Our experiments results show that SCRA is a suitable framework for latency-sensitive NDN applications.more » « less
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Abstract This paper focuses on protecting the cellular paging protocol — which balances between the quality-of-service and battery consumption of a device — against security and privacy attacks. Attacks against this protocol can have severe repercussions, for instance, allowing attacker to infer a victim’s location, leak a victim’s IMSI, and inject fabricated emergency alerts. To secure the protocol, we first identify the underlying design weaknesses enabling such attacks and then propose efficient and backward-compatible approaches to address these weaknesses. We also demonstrate the deployment feasibility of our enhanced paging protocol by implementing it on an open-source cellular protocol library and commodity hardware. Our evaluation demonstrates that the enhanced protocol can thwart attacks without incurring substantial overhead.more » « less