scholarly journals A proposal of ethical competence model for cyber security organization

2021 ◽  
Vol 24 (3) ◽  
pp. 1711
Author(s):  
Nor Hapiza Mohd Ariffin ◽  
Ruhaila Maskat
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Daily Practice ◽  
Competence Assessment ◽  
Competence Model ◽  
Cognitive Intelligence ◽  
Ethical Competence ◽  
Security Organizations ◽  
Competence Models ◽  
Intelligent Quotient

A proactive cyber security plan to safeguard confidential information and privacy still lacks initiatives to avoid frequent harmful attacks. Cybersecurity professionals must possess ethical competence and prove worthy of overseeing valuable information for efficient decision‐making since ethical competence is fundamental for daily practice. There is a need to define what it means to be ethically competent in the era of IR4.0. The previous competence models still lack consideration of both artificial intelligence (AI) and emotional intelligence (EI) skills. AI brings new opportunities to cyber security organizations that focus on AI skills related to cognitive Intelligence or intelligent quotient (IQ). EI, which refers to emotional quotient (EQ), is a good predictor of ethical competence as it can perceive and express emotions precisely to facilitate thought to understand and manage emotions. However, practically, most cyber security organizations focused on AI skills and disregarded EI skills' roles. This research proposes a cyber artemotional model that blends AI skills and EI skills for cyber security employees. This research would benefit cyber security organizations with cyber artemotional model as employees ethical competence assessment, and it is in line with the demand of IR4.0.

Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 67-78
Author(s):  
Guy Barash ◽  
Mauricio Castillo-Effen ◽  
Niyati Chhaya ◽  
Peter Clark ◽  
Huáscar Espinoza ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Cyber Security ◽  
Question Answering ◽  
Intent Recognition ◽  
Affective Content ◽  
Learning Plan ◽  
Dialog System ◽  
Affective Content Analysis ◽  
Games And Simulations

The workshop program of the Association for the Advancement of Artificial Intelligence’s 33rd Conference on Artificial Intelligence (AAAI-19) was held in Honolulu, Hawaii, on Sunday and Monday, January 27–28, 2019. There were fifteen workshops in the program: Affective Content Analysis: Modeling Affect-in-Action, Agile Robotics for Industrial Automation Competition, Artificial Intelligence for Cyber Security, Artificial Intelligence Safety, Dialog System Technology Challenge, Engineering Dependable and Secure Machine Learning Systems, Games and Simulations for Artificial Intelligence, Health Intelligence, Knowledge Extraction from Games, Network Interpretability for Deep Learning, Plan, Activity, and Intent Recognition, Reasoning and Learning for Human-Machine Dialogues, Reasoning for Complex Question Answering, Recommender Systems Meet Natural Language Processing, Reinforcement Learning in Games, and Reproducible AI. This report contains brief summaries of the all the workshops that were held.

A Survey on Artificial Intelligence Techniques to Prevent Cyber Crime

2018 ◽  
Vol 8 (5) ◽  
pp. 80
Author(s):  
Juveriya Afreen
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Data Security ◽  
Human Reasoning ◽  
Cyber Crime ◽  
Artificial Intelligence Techniques

Abstract-- With increase in complexity of data, security, it is difficult for the individuals to prevent the offence. Thus, by using any automation or software it’s not possible by only using huge fixed algorithms to overcome this. Thus, we need to look for something which is robust and feasible enough. Hence AI plays an epitome role to defense such violations. In this paper we basically look how human reasoning along with AI can be applied to uplift cyber security.

scholarly journals Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics in extreme environments – cyber risk in the colonisation of Mars

2021 ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Kevin Page ◽  
Max Van Kleek ◽  
Omar Santos ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Real Time ◽  
Cyber Security ◽  
Extreme Environments ◽  
Learning Technologies ◽  
Cyber Attacks ◽  
Edge Computing ◽  
Mathematical Formulas ◽  
Cyber Risk

AbstractMultiple governmental agencies and private organisations have made commitments for the colonisation of Mars. Such colonisation requires complex systems and infrastructure that could be very costly to repair or replace in cases of cyber-attacks. This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing. The paper presents a new mathematical approach for integrating concepts for cognition engine design, edge computing and Artificial Intelligence and Machine Learning to automate anomaly detection. This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real-time intelligence for predictive cyber risk analytics. This will enhance capacities for risk analytics and assists in the creation of a comprehensive and systematic understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when Artificial Intelligence and Machine Learning technologies are migrated to the periphery of the internet and into local IoT networks.

Artificial intelligence and the radiologist: the future in the Armed Forces Medical Services

2019 ◽  
pp. jramc-2018-001055
Author(s):  
Debraj Sen ◽  
R Chakrabarti ◽  
S Chatterjee ◽  
D S Grewal ◽  
K Manrai
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Cyber Security ◽  
Tertiary Care ◽  
Armed Forces ◽  
Medical Services ◽  
Imaging Biomarkers ◽  
Imaging Data ◽  
Adequate Funding ◽  
Trained Manpower

Artificial intelligence (AI) involves computational networks (neural networks) that simulate human intelligence. The incorporation of AI in radiology will help in dealing with the tedious, repetitive, time-consuming job of detecting relevant findings in diagnostic imaging and segmenting the detected images into smaller data. It would also help in identifying details that are oblivious to the human eye. AI will have an immense impact in populations with deficiency of radiologists and in screening programmes. By correlating imaging data from millions of patients and their clinico-demographic-therapy-morbidity-mortality profiles, AI could lead to identification of new imaging biomarkers. This would change therapy and direct new research. However, issues of standardisation, transparency, ethics, regulations, training, accreditation and safety are the challenges ahead. The Armed Forces Medical Services has widely dispersed units, medical echelons and roles ranging from small field units to large static tertiary care centres. They can incorporate AI-enabled radiological services to subserve small remotely located hospitals and detachments without posted radiologists and ease the load of radiologists in larger hospitals. Early widespread incorporation of information technology and enabled services in our hospitals, adequate funding, regular upgradation of software and hardware, dedicated trained manpower to manage the information technology services and train staff, and cyber security are issues that need to be addressed.

Toward a New Conceptualization of Journalistic Competency: An Analysis of U.S. Broadcasting Job Announcements

2020 ◽  
pp. 107769582092530 ◽  
Author(s):  
Lei Guo ◽  
Yong Volz
Keyword(s):  
Content Analysis ◽  
Professional Values ◽  
Professional Competencies ◽  
Competence Model ◽  
Four Dimensions ◽  
Broadcast Media ◽  
Ethical Competence ◽  
Cognitive Knowledge ◽  
Constitutive Element

Journalistic competency is a constitutive element of professional values and practices in journalism. But what constitutes journalistic competency in today’s ever-changing media landscape? Existing literature lacks theoretical and empirical understandings of journalistic competency, especially in broadcasting. Drawing on Cheetham and Chivers’s competence model, we examine professional competencies as defined by broadcast media through a content analysis of 359 job announcements. Four dimensions of journalistic competency were explicated and empirically assessed: cognitive/knowledge, functional, personal/behavioral, and ethical competence.

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