Details
Name
Tadeu Augusto FreitasCluster
Computer ScienceRole
Research AssistantSince
18th January 2017
Nationality
PortugalCentre
Advanced Computing SystemsContacts
+351220402963
tadeu.a.freitas@inesctec.pt
2023
Authors
Freitas, T; Soares, J; Correia, ME; Martins, R;
Publication
53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2023 - Supplemental Volume, Porto, Portugal, June 27-30, 2023
Abstract
The increasing level of sophistication of cyber attacks which are employing cross-cutting strategies that leverage multi-domain attack surfaces, including but not limited to, software defined networking poisoning, biasing of machine learning models to suppress detection, exploiting software (development), and leveraging system design deficiencies.While current defensive solutions exist, they only partially address multi-domain and multi-stage attacks, thus rendering them ineffective to counter the upcoming generation of attacks. More specifically, we argue that a disruption is needed to approach separated knowledge domains, namely Intrusion Tolerant systems, cybersecurity, and machine learning.We argue that current solutions tend to address different concerns/facets of overlapping issues and they tend to make strong assumptions of supporting infrastructure, e.g., assuming that event probes/metrics are not compromised.To address these issues, we present Skynet, a platform that acts as a secure overseer that merges traditional roles of SIEMs with conventional orchestrators while being rooted on the fundamentals introduced by previous generations of intrusion tolerant systems. Our goal is to provide an open-source intrusion tolerant platform that can dynamically adapt to known and unknown security threats in order to reduce potential vulnerability windows. © 2023 IEEE.
2018
Authors
Freitas, T; Rodrigues, J; Bogas, D; Coimbra, M; Martins, R;
Publication
2018 IEEE 6TH INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD (FICLOUD 2018)
Abstract
The increasing capabilities of smartphones is paving way to novel applications through the crowd-sourcing of these untapped resources, to form hyperlocal meshes commonly known as edge-clouds. While a relevant body-of-work is already available for the underlying networking, computing and storage facilities, security and privacy remain second class citizens. In this paper we present Panoptic, an edge-cloud system that enables the search for missing people, similar to the commonly known Amber alert system, in high density scenarios where wireless infrastructure might be limited (WiFi and LTE), e.g. concerts, while featuring privacy and security by design. Since the limited resources present in the mobile devices, namely battery capacity, Panoptic offers a computing offloading that tries to minimize data leakage while offering acceptable levels of performance. Our results show that it is achievable to run these algorithms in an edge-cloud configuration and that it is beneficial to use this architecture to lower data transfer through the wireless infrastructure while enforcing privacy. Results from our experimental evaluation show that the security layer does not impose a significant overhead, and only accounts for 2% of the total execution time for an edge cloud comprised by, but not limited to, 8 devices.
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