Description
Society’s dependence on communication networks for all aspects of day-to-day living; business, education, entertainment etc. makes “the network” a very attractive target for malicious attack, which cyber criminals are only too eager to exploit, attempting to limit or block access to essential services (e.g., healthcare, banking, critical infrastructure etc.), disrupting our daily lives and causing high cost to businesses and individuals. Advances in networking such as Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) have enabled the network availability and scalability required to support massive global connectivity. With SDN and programmable networks, we introduce flexibility to the control and processing of network traffic, which may be leveraged for in-network security functions. However, as we explore the use of network programmability frameworks and languages such as P4 to accelerate packet processing functions for the flexible and scalable connectivity in next-generation networks, we cannot lose sight of the security of the programmable network itself. Indeed, this flexibility and programmability potentially exposes the network devices to compromise.This talk will explore the opportunities and challenges of programmable network security, developments in the field, and our related research at CSIT/QUB.
Next sessions
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Opening Pandora's Box: White-Box Attacks on Microsoft's PhotoDNA Perceptual Hash Function
Speaker : Diane Leblanc-Albarel - KU Leuven
PhotoDNA is a widely deployed perceptual hash function used for the detection of illicit content such as Child Sexual Abuse Material (CSAM). In this talk, I will present our paper introducing the first mathematical description of Alleged PhotoDNA, a function that reproduces the outputs of PhotoDNA. Our analysis reveals several structural weaknesses: the function is piece-wise linear and[…]-
Cryptography
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Privacy
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Towards More Secure Large Language Models
Speaker : Raouf Kerkouche - Inria Lille
Large Language Models (LLMs) have achieved considerable success and are now widely used across multiple domains, highlighting their transformative impact on both technology and society. However, this widespread adoption also exposes LLMs to numerous security threats that can alter model behavior or degrade overall performance. To mitigate these threats, most research has focused on alignment[…]-
Machine learning
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