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.

Abstract
In this paper we present the architecture of RTPM, a middle-ware framework aimed at supporting the development and management of information systems for high-speed public transportation systems. The framework is based on a peer-to-peer overlay infrastructure with the main focus being on providing a scalable, resilient, reconfigurable, highly available platform for real-time and QoS computing. Copyright 2008 ACM.

Abstract
We address the problem of providing transparent, lightweight, fault-tolerance mechanisms for generic peer-to-peer middleware systems. The main idea is to use the peer-to-peer overlay to provide for fault-tolerance rather than support it higher up in the middleware architecture, e.g. in the form of services. To evaluate our approach we have implemented a fault-tolerant middleware prototype that uses a hierarchical peer-to-peer overlay in which the leaf peers connect to sensors that provide data streams. Clients connect to the root of the overlay and request streams that are routed upwards through intermediate peers in the overlay up to the client. We report encouraging preliminary results for latency, jitter and resource consumption for both the non-faulty and faulty cases.

Abstract
This paper discusses the design of YapDss, an or-parallel Prolog system for distributed memory parallel machines, such as the Beowulf PC clusters. The system builds on the work of YapOr, an or-parallel system for shared memory machines, and uses the distributed stack splitting binding model to represent computation state and work sharing among the computational workers. A new variant scheme of stack splitting, the diagonal splitting, is proposed and implemented. This scheme includes efficient algorithms to balance work load among computing workers, to determine the bottommost common node between two workers, and to calculate exactly the work load of one worker. An initial evaluation of the system shows that it is able to achieve very good speedups on a Beowulf PC cluster.

Abstract
HAL 9000 is an Intrusion Tolerant Systems (ITSs) Risk Manager, which assesses configuration risks against potential intrusions. It utilizes gathered threat knowledge and remains operational, even in the absence of updated information. Based on its advice, the ITSs can dynamically and proactively adapt to recent threats to minimize and mitigate future intrusions from malicious adversaries.Our goal is to reduce the risk linked to the exploitation of recently uncovered vulnerabilities that have not been classified and/or do not have a script to reproduce the exploit, considering the potential that they may have already been exploited as zero-day exploits. Our experiments demonstrate that the proposed solution can effectively learn and replicate National Vulnerability Database's evaluation process with 99% accuracy. © 2024 IEEE.

Abstract