Investigating the Interaction between Energy Consumption, Quality of Service, Reliability, Security, and Maintainability of Computer Systems and Networks

Kehagias, Dionysios; Janković, Marija; Siavvas, Miltiadis; Gelenbe, Erol

doi:10.1007/s42979-020-00404-8

Cited by 12 publications

(8 citation statements)

References 36 publications

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“…The field that started with the need to encrypt data and create secure systems through strong means for security such as passwords, authentication schemes, firewalls and cryptographic keys, has now substantially evolved towards the detection and mitigation of cyberattacks. In addition issues with respect to software's own specific vulnerabilities [23] and the need to detect and mitigate such properties has also become important [23,24,44,88,109,110].…”

Section: Discussionmentioning

confidence: 99%

AI and Quality of Service Driven Attack Detection, Mitigation and Energy Optimization: A Review of Some EU Project Results

Caglayan

2022

Communications in Computer and Information Science

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This article summarizes briefly the contributions presented in this EuroCyberSecurity Workshop 2021 which is organized as part of the series of International Symposia on Computer and Information Sciences (ISCIS), with the support of the European Commission funded IoTAC Project, that was held on November and in NIce, France, and sponsored by the Institute of Teoretical and Applied Informatics of the Polish Academy of Sciences. It also summarizes some of the research contributions of several EU Projects including NEMESYS, GHOST, KONFIDO, SDK4ED and IoTAC, primarily with a cybersecurity and Machine Learning orientation. Thus subjects covered include the cybersecurity of Mobile Networks and of the Internet of Things (IoT), the design of IoT Gateways and their performance, the security of networked health systems that provide health services to individuals across the EU Member states, as well as the issues of energy consumption by ICT which are becoming increasingly important, including in the cybersecurity perspective, as we focus increasingly on climate change and the needed transition towards highly reduced emissions. Many of the techniques and results discussed in this article are based either on Machine Learning (ML) methods, or on methods for the performance modeling and optimization of networked and distributed computer systems.

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Section: Discussionmentioning

confidence: 99%

AI and Quality of Service Driven Attack Detection, Mitigation and Energy Optimization: A Review of Some EU Project Results

Caglayan

2022

Communications in Computer and Information Science

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“…Information and tutorials on how the SDK4ED Dashboard can be installed locally and used for analyzing software products with respect to their Maintainability, Energy Consumption, and Security have been also provided online 17 . More information about the SDK4ED Platform can be found in our relevant publications (Jankovic et al, 2019;Siavvas et al, 2020b;Kehagias et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

A hierarchical model for quantifying software security based on static analysis alerts and software metrics

et al. 2021

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Despite the acknowledged importance of quantitative security assessment in secure software development, current literature still lacks an efficient model for measuring internal software security risk. To this end, in this paper, we introduce a hierarchical security assessment model (SAM), able to assess the internal security level of software products based on low-level indicators, i.e., security-relevant static analysis alerts and software metrics. The model, following the guidelines of ISO/IEC 25010, and based on a set of thresholds and weights, systematically aggregates these low-level indicators in order to produce a high-level security score that reflects the internal security level of the analyzed software. The proposed model is practical, since it is fully automated and operationalized in the form of a standalone tool and as part of a broader Computer-Aided Software Engineering (CASE) platform. In order to enhance its reliability, the thresholds of the model were calibrated based on a repository of 100 popular software applications retrieved from Maven Repository. Furthermore, its weights were elicited in a way to chiefly reflect the knowledge expressed by the Common Weakness Enumeration (CWE), through a novel weights elicitation approach grounded on popular decision-making techniques. The proposed model was evaluated on a large repository of 150 open-source software applications retrieved from GitHub and 1200 classes retrieved from the OWASP Benchmark. The results of the experiments revealed the capacity of the proposed model to reliably assess internal security at both product level and class level of granularity, with sufficient discretion power. They also provide preliminary evidence for the ability of the model to be used as the basis for vulnerability prediction. To the best of our knowledge, this is the first fully automated, operationalized and sufficiently evaluated security assessment model in the modern literature.

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“…To compute the actual parameters that are necessary for the execution of our mathematical model, the Energy Toolbox of the SDK4ED Project was utilized [57,58]. The Energy Toolbox provides measurements of the execution time and energy consumption of a software program at the loop-level of granularity, being mainly based on popular profiling tools like Linux Perf (https://perf.wiki.kernel.org/) and Valgrind (http://www.valgrind.org/) , as well as on static estimations [57,59].…”

Section: Demonstration Through a Real-world Examplementioning

confidence: 99%

Minimizing Energy and Computation in Long-Running Software

Gelenbe

Siavvas

2021

Applied Sciences

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Long-running software may operate on hardware platforms with limited energy resources such as batteries or photovoltaic, or on high-performance platforms that consume a large amount of energy. Since such systems may be subject to hardware failures, checkpointing is often used to assure the reliability of the application. Since checkpointing introduces additional computation time and energy consumption, we study how checkpoint intervals need to be selected so as to minimize a cost function that includes the execution time and the energy. Expressions for both the program’s energy consumption and execution time are derived as a function of the failure probability per instruction. A first principle based analysis yields the checkpoint interval that minimizes a linear combination of the average energy consumption and execution time of the program, in terms of the classical “Lambert function”. The sensitivity of the checkpoint to the importance attributed to energy consumption is also derived. The results are illustrated with numerical examples regarding programs of various lengths and showing the relation between the checkpoint interval that minimizes energy consumption and execution time, and the one that minimizes a weighted sum of the two. In addition, our results are applied to a popular software benchmark, and posted on a publicly accessible web site, together with the optimization software that we have developed.

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Investigating the Interaction between Energy Consumption, Quality of Service, Reliability, Security, and Maintainability of Computer Systems and Networks

Cited by 12 publications

References 36 publications

AI and Quality of Service Driven Attack Detection, Mitigation and Energy Optimization: A Review of Some EU Project Results

AI and Quality of Service Driven Attack Detection, Mitigation and Energy Optimization: A Review of Some EU Project Results

A hierarchical model for quantifying software security based on static analysis alerts and software metrics

Minimizing Energy and Computation in Long-Running Software

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