关于健康物联网设备和接触者追踪相关风险的网络战视角。

IF 4.5 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Neural Computing & Applications Pub Date : 2023-01-01 Epub Date: 2022-01-20 DOI:10.1007/s00521-021-06720-1
Andrea Bobbio, Lelio Campanile, Marco Gribaudo, Mauro Iacono, Fiammetta Marulli, Michele Mastroianni
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引用次数: 3

摘要

广泛使用信息技术资源来评估和管理最近的新冠肺炎大流行,有助于提高应对措施的有效性以及监测和预防的普遍性。不幸的是,文献报道称,物联网设备是这些应用中广泛采用的技术,其特点是存在难以在国家层面管理的安全漏洞。利用智能手机的相关技术也存在类似的问题,如接触者追踪应用程序和非医疗健康监测设备。在类似的情况下,这些漏洞可能会在网络领域被利用,给危机管理系统带来虚假警报,干扰目标国家的利益,对其经济和政治平衡产生影响。在本文中,我们分析了示例子系统的潜在威胁,以显示这些影响可能对其产生的影响,并评估可能的后果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A cyber warfare perspective on risks related to health IoT devices and contact tracing.

The wide use of IT resources to assess and manage the recent COVID-19 pandemic allows to increase the effectiveness of the countermeasures and the pervasiveness of monitoring and prevention. Unfortunately, the literature reports that IoT devices, a widely adopted technology for these applications, are characterized by security vulnerabilities that are difficult to manage at the state level. Comparable problems exist for related technologies that leverage smartphones, such as contact tracing applications, and non-medical health monitoring devices. In analogous situations, these vulnerabilities may be exploited in the cyber domain to overload the crisis management systems with false alarms and to interfere with the interests of target countries, with consequences on their economy and their political equilibria. In this paper we analyze the potential threat to an example subsystem to show how these influences may impact it and evaluate a possible consequence.

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来源期刊
Neural Computing & Applications
Neural Computing & Applications 工程技术-计算机:人工智能
CiteScore
11.40
自引率
8.30%
发文量
1280
审稿时长
6.9 months
期刊介绍: Neural Computing & Applications is an international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms, fuzzy logic and neuro-fuzzy systems. All items relevant to building practical systems are within its scope, including but not limited to: -adaptive computing- algorithms- applicable neural networks theory- applied statistics- architectures- artificial intelligence- benchmarks- case histories of innovative applications- fuzzy logic- genetic algorithms- hardware implementations- hybrid intelligent systems- intelligent agents- intelligent control systems- intelligent diagnostics- intelligent forecasting- machine learning- neural networks- neuro-fuzzy systems- pattern recognition- performance measures- self-learning systems- software simulations- supervised and unsupervised learning methods- system engineering and integration. Featured contributions fall into several categories: Original Articles, Review Articles, Book Reviews and Announcements.
期刊最新文献
Stress monitoring using wearable sensors: IoT techniques in medical field. A new hybrid model of convolutional neural networks and hidden Markov chains for image classification. Analysing sentiment change detection of Covid-19 tweets. Normal vibration distribution search-based differential evolution algorithm for multimodal biomedical image registration. Special issue on deep learning and big data analytics for medical e-diagnosis/AI-based e-diagnosis.
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