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Stream Economics: Resource Efficiency in Streams with Task Over-Allocation and Load Shedding
No full textInternational audienceIn this paper we propose an alternative task scheduling mechanism for stream processing systems such as Apache Flink, that targets resource efficiency in a multi-tenant stream processing environment with several resource heterogeneous tasks being executed in parallel. The task scheduler we propose doesn’t limit the amount of tasks that can run on each machine, instead, it adapts tasks’ allocation based on their runtime metrics, scheduling tasks to the machines with more available resources. At the same time, we explore load shedding in stream processing applications, as a mechanism to solve the tasks’ resource starvation problem that may appear due to bad decisions performed by the scheduler, because of its optimistic approach and due to the dynamic workloads of the applications. We implemented a proof-of-concept of such system in Apache Flink and tested it against scenarios that show the different aspects and advantages of the developed mechanism in action
Formally Verifying a Rollback-Prevention Protocol for TEEs
No full textPart 1: Full PapersInternational audienceFormal verification of distributed protocols is challenging and usually requires great human effort. Ivy, a state-of-the-art formal verification tool for modeling and verifying distributed protocols, automates this tedious process by leveraging a decidable fragment of first-order logic. Observing the successful adoption of Ivy for verifying consensus protocols, we examine its practicality in verifying rollback-prevention protocols for Trusted Execution Environments (TEEs). TEEs suffer from rollback attacks, which can revert confidential applications’ states to stale ones to compromise security. Recently, designing distributed protocols to prevent rollback attacks has attracted significant attention. However, the lack of formal verification of these protocols leaves them potentially vulnerable to security breaches. In this paper, we leverage Ivy to formally verify a rollback-prevention protocol, namely the TIKS protocol in ENGRAFT (Wang et al., CCS 2022). We select TIKS because it is similar to other rollback-prevention protocols and is self-contained. We detail the verification process of using Ivy to prove a rollback-prevention protocol, present lessons learned from this exploration, and release the proof code to facilitate future research (https://github.com/wwl020/TIKS-Proof-in-Ivy). To the best of our knowledge, this is the first endeavor to explain the formal verification of a rollback-prevention protocol in detail
Noninterference Analysis of Reversible Probabilistic Systems
No full textPart 1: Full PapersInternational audienceNoninterference theory supports the analysis of secure computations in multi-level security systems. In the nondeterministic setting, the approach to noninterefence based on weak bisimilarity has turned out to be inadequate for reversible systems. This drawback can be overcome by employing a more expressive semantics, which has been recently proven to be branching bisimilarity. In this paper we extend the result to reversible systems that feature both nondeterminism and probabilities. We recast noninterference properties by adopting probabilistic variants of weak and branching bisimilarities. Then we investigate a taxonomy of those properties as well as their preservation and compositionality aspects, along with a comparison with the nondeterministic taxonomy. The adequacy of the resulting noninterference theory for reversible systems is illustrated via a probabilistic smart contract example
Trust Management XIV: 14th IFIP WG 11.11 International Conference on Trust Management, IFIPTM 2023, Amsterdam, The Netherlands, October 18–20, 2023, Proceedings
No full textInternational audienceBook Front Matter of AICT 69
Configuration of Software Product Lines Driven by the Softgoals: the TEAEM Approach
No full textPart 4: Security, Compliance, and Configuration in Enterprise ModelingInternational audienceThe Model-Driven Architecture (MDA) serves as an essential framework for designing enterprise information systems, emphasizing the alignment and traceability of goals across different modeling layers. However, MDA typically overlooks the integration of qualitative attributes, or softgoals, which are critical for enhancing user satisfaction. Our previous work introduced the Technology-Aware Enterprise Modeling (TEAEM) approach, which enhances MDA by integrating model checking, validation, and impact analysis. This paper extends TEAEM to more effectively incorporate softgoals. We achieve this by integrating SysML component modeling for low-level, and softgoals into the high-level of the MDA. These advancements facilitate bottom-up constraint propagation and ensure that technological decisions are reflected consistently at all levels of abstraction, thereby optimizing the system to meet strategic business goals. Additionally, we propose generating configurations in software product lines, driven by the fulfillment of softgoals, to apply the TEAEM approach
A Multi-agent Model for Opinion Evolution in Social Networks Under Cognitive Biases
No full textInternational audienceWe generalize the DeGroot model for opinion dynamics to better capture realistic social scenarios. We introduce a model where each agent has their own individual cognitive biases. Society is represented as a directed graph whose edges indicate how much agents influence one another. Biases are represented as the functions in the square region [-1,1] and categorized into four sub-regions based on the potential reactions they may elicit in an agent during instances of opinion disagreement. Under the assumption that each bias of every agent is a continuous function within the region of receptive but resistant reactions (R), we show that the society converges to a consensus if the graph is strongly connected. Under the same assumption, we also establish that the entire society converges to a unanimous opinion if and only if the source components of the graph-namely, strongly connected components with no external influence-converge to that opinion. We illustrate that convergence is not guaranteed for strongly connected graphs when biases are either discontinuous functions in or not included in R. We showcase our model through a series of examples and simulations, offering insights into how opinions form in social networks under cognitive biases
Simulation-Based Framework for Assessing Synchromodal Transportation Solutions in Low-Density Ecosystems
No full textPart 6: Simulation FrameworksInternational audienceTransport and mobility play a crucial role in collaborative networks, facilitating access to resources. While this strengthens economic and social integration, the expansion of collaborative networks poses major challenges in terms of effectiveness, sustainability and equity. Improving transport services is consequently crucial, particularly in sparsely populated areas, to reduce economic and social disparities. If urban areas benefit from Smart City principles to optimize the flow of people and goods, rural areas are often marginalized. Some authors have demonstrated qualitatively the potentiality of using Physical Internet and synchromodality paradigms to change this situation. But no quantitative demonstration has been done yet. The purpose of this research work is to design and present our multi-agent vision of a simulation framework for evaluating synchromodal transport solutions in low-density ecosystems. Composed of four components (demand estimator, transportation planner, simulator engine and performance assessor), this framework is intended to be tested on ECOTRAIN case study
A Systematic Task and Knowledge-Based Process to Tune Cybersecurity Training to User Learning Groups: Application to Email Phishing Attacks
No full textPart 2: Social EngineeringInternational audienceCybersecurity training is one of the most important countermeasures to address cybersecurity threats and their reported increase in terms of types and occurrences. Several approaches addressing the development of cybersecurity training have been proposed but a careful analysis of these approaches highlighted limitations both in terms of identification of required knowledge, skills, in terms of description of users' tasks (the job they have to perform) as well as in terms of adaptation of the training to diverse user groups. This paper proposes a systematic process to tune cybersecurity training for diverse user groups, and in particular to support the development of cybersecurity training programs for different learning groups (built from the analysis of the diverse user groups). We illustrate this process on the concrete case of phishing attacks
Teacher education and teacher support associations for informatics and computing in schools, 2024 Edition: ePublication 5
No full textInternational audienceThe Informatics for All (I4All) coalition is exploring how informatics and computing in schools can be further developed and is currently focusing on how teachers are being supported in terms of teaching informatics and computing. Part of the exploratory work is a gathering of initial details about national and regional structures that provide such support.This document has been created from responses to a consultation, circulated to I4All Steering Commitee members and the International Federation for Information Processing (IFIP) Technical Commitee 3 on Education (TC3) members and to IFIP TC Chairs (as IFIP is a member of the I4All coalition)
Adaptive Genetic Algorithm with Optimized Operators for Scheduling in Computer Systems
No full textPart 3: Neural and Evolutionary ComputingInternational audienceModern computing and networking environments provide the important problems of efficient using such resources as energy and cores or processors. It is based on the possibility of dynamically varying the speed of processors and using parallel calculations in the execution of operations. We consider the NP-hard speed scaling scheduling problem with energy constraints and parallelizable jobs. Each job must be executed on the given number of processors. Processors can vary their speeds dynamically. It is required to assign speeds to jobs and schedule them such that the total completion time is minimized under the given energy budget. An adaptive genetic algorithm with optimized crossover operators is proposed. The optimal recombination problem is solved in the crossover operator. This problem is aimed at searching for the best possible offspring following the well-known gene transmitting property. The experimental evaluation shows that the algorithm outperforms the known metaheuristics and demonstrates the perspectives of using adaptive techniques and optimized operators