The need to consider both object identity and behavior in establishing the trustworthiness of network devices within a Smart Grid

McCusker, Owen; Gittins, Benjamin; Glanfield, Joel; Brunza, Scott; Brooks, Stephen

doi:10.1145/1852666.1852724

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…For instance, papers [7]- [9] examine students' engagement, attention, and other teaching and learning-related problems through body language. The recognition of human activities, gestures, and emotional expressions from security perspectives is studied in [10], [11]. Articles [12], [13] discuss the effect of body language on political aspects.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Analysis of Patients’ Body Language in Healthcare: A Comprehensive Review

Turaev,

Babu,

Al-Dabet

et al. 2024

IEEE Access

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Body language refers to the unspoken communication conveyed through human body actions like body movements and postures, limb gestures, and facial and other bodily expressions. It acts as a transparent medium, exposing an individual's emotions, attitudes, true thoughts, intentions, and physical and mental health states. A person may express pain using hand movements or other bodily cues, their facial expressions potentially offering insights into the intensity of the pain. Additionally, various diseases and pains can induce abnormalities in body movements, postures, and expressions, signaling distress or discomfort. Therefore, investigating the cause-effect relationships between diseases/pains and patients' abnormal body language holds significant relevance, promising to enhance our understanding and management of these conditions. This importance has been reflected in numerous healthcare and artificial intelligence (AI) research articles. AI studies investigate this and related topics by detecting, recognizing, and analyzing patients' abnormal activities and body actions using machine-learning techniques. However, most AI studies do not consider comprehensive domain knowledge that describes a complete and accurate list of patients' abnormal actions caused by a disease or pain. Though these results appear consistent and stable from an AI outlook, they fall short when viewed through the prism of healthcare, primarily because the limited domain knowledge incorporated in the AI studies makes the findings partially incomplete. To overcome these drawbacks, this paper comprehensively reviews healthcare and medical studies centered on patients' body language from an AI outlook. It presents a thorough descriptive and exploratory analysis of the findings, yielding a more accurate and comprehensive understanding of the causational connections between diseases and abnormal body actions and the strength of the evidence supporting these connections. The analysis enables us to define "disease-to-abnormality" and "abnormality-to-disease" mappings that result in building exhaustive and accurate lists of abnormal body actions induced by diseases and pains as well as lists of diseases and pains causing particular abnormal body actions. The generation of these lists is assisted by the concepts of "correlation strength index" and "strongly correlated selection" defined in this paper. The paper's results have significant implications for developing machine learning systems that can more accurately analyze patients' physical and mental health states, correctly identify external signs and symptoms of diseases, and effectively monitor health conditions.

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Section: Introductionmentioning

confidence: 99%

Data-Driven Analysis of Patients’ Body Language in Healthcare: A Comprehensive Review

Turaev,

Babu,

Al-Dabet

et al. 2024

IEEE Access

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“…On the other hand, understanding students' body language is also important as it reveals students' involvement, attention, understanding, thinking, and feeling during class activities [12], [13], [14], [15], [16]. The ability to interpret body postures, facial expressions, and other bodily cues is crucial in security services, criminal intelligence, and law enforcement [17], [18], [19], [20], [21], [22]. Politicians, in addition to verbal skills, communicate effectively through their body language as it is a powerful tool for expressing their personalities, connecting with people, and influencing the audience's perception through their good public appearance, postures, facial expressions, hand gestures and tone of voice [23], [24], [25], [26], [27].…”

Section: Introductionmentioning

confidence: 99%

Review and Analysis of Patients’ Body Language From an Artificial Intelligence Perspective

et al. 2023

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Body language is a nonverbal communication process consisting of movements, postures, gestures, and expressions of the body or body parts. Body language expresses human feelings, thoughts, and intentions. It also reveals physical and psychological health conditions: abnormal activities inform peoples' health conditions, facial expressions indicate their emotional states and abnormal body actions convey specific diseases' external signs and symptoms. We can observe the importance of studying the body language of people with health conditions through many reports in literature written by healthcare (medical) and artificial intelligence researchers. This paper comprehensively reviews artificial intelligence-based articles that have studied patients' body language. We also conduct different descriptive and exploratory examinations of the findings using data analysis techniques, which provide more authentic domain knowledge of abnormal activities, abnormal body actions, and more precise analysis of methodologies used in machine learning tasks for studying these abnormalities. The paper's results are essential for developing intelligent automated systems that accurately evaluate patients' physical and psychological conditions, precisely identify external signs and symptoms of diseases, and adequately monitor patients' health conditions.

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A combined discriminative and generative behavior model for cyber physical system defense

McCusker

Brunza

Dasgupta

et al. 2013

2013 6th International Symposium on Resilient Control Systems (ISRCS)

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In this position paper we explore the use of behavior models as an enabling methodology in the promotion of a more holistic understanding of CPS that can bridge both cyber and physical domains. Thus, we investigate the use of aggregate behavior analysis techniques combined in both cyber and physical domains. Ultimately, our work focuses on the development of a cyber-physical behavior model that leverages behavior aggregation promoting the creation of a long-view sense-making capability driven by both cyber and physical observations. We look to the use of this approach to establish the ability to anticipate malicious activity in CPS, rather that react.

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The need to consider both object identity and behavior in establishing the trustworthiness of network devices within a Smart Grid

Cited by 3 publications

References 12 publications

Data-Driven Analysis of Patients’ Body Language in Healthcare: A Comprehensive Review

Data-Driven Analysis of Patients’ Body Language in Healthcare: A Comprehensive Review

Review and Analysis of Patients’ Body Language From an Artificial Intelligence Perspective

A combined discriminative and generative behavior model for cyber physical system defense

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