Random flip-flop: adding quantum randomness to digital circuits for improved cyber security, artificial intelligence and more

2021 ◽  
Author(s):  
Mario Stipčević ◽  
Mateja Batelić ◽  
Edoardo Charbon ◽  
Claudio Bruschini ◽  
Michel I. Antolović
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Digital Circuits ◽  
Flip Flop ◽  
Quantum Randomness

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.

Artificial Intelligence-Based Solutions for Cyber Security Problems

2021 ◽  
pp. 68-86
Author(s):  
Merve Yildirim
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Cyber Attacks ◽  
Network Systems ◽  
Security Systems ◽  
Artificial Intelligence Techniques ◽  
Security Issues ◽  
Security Applications ◽  
Cyber Threats ◽  
Legal Risks

Due to its nature, cyber security is one of the fields that can benefit most from the techniques of artificial intelligence (AI). Under normal circumstances, it is difficult to write software to defend against cyber-attacks that are constantly developing and strengthening in network systems. By applying artificial intelligence techniques, software that can detect attacks and take precautions can be developed. In cases where traditional security systems are inadequate and slow, security applications developed with artificial intelligence techniques can provide better security against many complex cyber threats. Apart from being a good solution for cyber security problems, it also brings usage problems, legal risks, and concerns. This study focuses on how AI can help solve cyber security issues while discussing artificial intelligence threats and risks. This study also aims to present several AI-based techniques and to explain what these techniques can provide to solve problems in the field of cyber security.

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