scholarly journals Reviewing Effectiveness of Artificial Intelligence Techniques Against Cyber Security Risks: In Case of It Industry in Saudi Arabia

2020 ◽  
Vol 1 (1) ◽  
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Sample Size ◽  
Cyber Security ◽  
Discriminant Validity ◽  
Geographical Area ◽  
Primary Data ◽  
It Industry ◽  
Security Risks ◽  
Artificial Intelligence Techniques

Aim: The aim of the researcher was to determine the effectiveness of artificial intelligence techniques against cyber security risks particularly in case of Saudi Arabia Method: Researcher has opted for quantitative method of research design along with primary data. The researcher collected the data from employees working in this I.T industry of Saudi Arabia. The sample size for this study was 468 and confirmatory factor analysis, discriminant validity, basic analysis of model and lastly, hypothesis assessment was carried out. Findings: The P-values of all variables were obtained as significant apart from expert system which had no significant relation with artificial intelligence and cyber security. Limitations: Geographical area, sample size, less variables and accessibility was the main issue.

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.

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.

scholarly journals Artificial Intelligence Techniques for Cyber Security Applications

2020 ◽  
pp. 89-94
Author(s):  
Shanqi Pang ◽  
Yongmei Li
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Significant Role ◽  
Cyber Security ◽  
Cyber Defense ◽  
Artificial Intelligence Techniques ◽  
Security Applications ◽  
The Future

Considering the enhancement in technology, criminals have been using cyberspace in order to commit many crimes. Therefore, it should be noted that cybercrimes are exposed to a number of threats and intrusions if not safeguarded well. Human and physical intervention tend not to be very adequate for the protection and tracking of such infrastructure, that is why there should be the establishment of multifaceted cyber defense networks, which are flexible, robust, and adjustable in order sense a massive collection of invasion and creation of real-time choices. Nevertheless, significant number of bio-related computing techniques of AI (artificial intelligence) tend to be increasing hence a significant role is played in detecting and preventing cybercrime. The main aim of this paper is outlining the actual advancement that have been made possible due to the application of AI methods for the fight against cybercrimes, in order to reveal how the methods are efficient in sensing and preventing cyber invasions, also providing a brief overview of the future works.

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.

Critical Analysis of Patient and Family Rights in JCI Accreditation and Cbahi Standards for Hospitals

2018 ◽  
Vol 6 (7) ◽  
pp. 324
Author(s):  
Zuber Mujeeb Shaikh
Keyword(s):  
Health Care ◽  
Saudi Arabia ◽  
Critical Analysis ◽  
Secondary Data ◽  
Joint Commission ◽  
Primary Data ◽  
Kingdom Of Saudi Arabia ◽  
Accreditation Standards ◽  
Joint Commission International ◽  
Central Board

Patient and Family Rights (PFR) is a common chapter available in the Joint Commission International (JCI) Accreditation[i] (fifth edition) and Central Board for Accreditation of Healthcare Institutions (CBAHI) Standards for hospitals (second edition)[ii]. JCI Accreditation is a USA based international healthcare accrediting organization, whereas CBAHI is the Kingdom of Saudi Arabia based national health care accrediting organization. However, both these standards are accredited by Ireland based International Society for Quality in Health Care (ISQua), which is the only accrediting organization who “accredit the accreditors' in the world. In Patient and Family Rights (PFR) chapter of JCI Accreditation for hospitals, there are nineteen (19) standards and seventy-seven (77) measurable elements (ME) whereas in CBAHI Accreditation there are thirty one (31) standards, ninety nine (99) sub-standards and fifty (50) evidence(s) of compliance (EC). The scoring mechanism is totally different in both these accrediting organizations. The researcher has identified thirty two (32) common parameters from JCI Accreditation and CBAHI standards, intent statement, measurable elements, sub-standard and evidence of compliance. On the basis of these identified common parameters, the researcher has compared the Patient and Family Rights chapter in JCI Accreditation and CBAHI Standards. Methods: This is a comparison study (normative comparison) in which the researcher has critically analyzed and compared the Patient and Family Rights (PFR) standards of JCI (Joint Commission International) Accreditation of USA (United States of America) and CBAHI (Central Board for Accreditation of Healthcare Institutions) of the Kingdom of Saudi Arabia. Data Collection: Primary data are collected from the JCI Accreditation Standards for hospitals, fifth edition, 2013 and CBAHI Standards for hospitals of Kingdom of Saudi Arabia, second edition, 2011. Secondary data are collected from relevant published journals, articles, research papers, academic literature and web portals. Objectives of the Study: The aim of this study is to analyze critically Patient and Family Rights (PFR) Standards in JCI Accreditation and CBAHI Standards to point out the best in among both these standards. Conclusion: This critical analysis of Patient and Family Rights (PFR) Standards in JCI Accreditation and CBAHI Standards for hospitals clearly show that the PFR Standards in CBAHI Standards are very comprehensive than the JCI Accreditation standards.

SISTEM PAKAR MENDIAGNOSA VIRUS MAYORA DENGAN METODE VARIABLE CENTERED INTELLIGENT RULE SYSTEM (VCIRS)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Siti Nurhena ◽  
Nelly Astuti Hasibuan ◽  
Kurnia Ulfa
Keyword(s):  
Artificial Intelligence ◽  
Immune System ◽  
Expert System ◽  
Expert Systems ◽  
Dengue Hemorrhagic Fever ◽  
Hemorrhagic Fever ◽  
Visual Basic ◽  
Artificial Intelligence Techniques ◽  
Individual Needs ◽  
Rule System

The diagnosis process is the first step to knowing a type of disease. This type of disease caused by mosquitoes is one of the major viruses (MAVY), dengue hemorrhagic fever (DHF) and malaria. Sometimes not everyone can find the virus that is carried by this mosquito, usually children who are susceptible to this virus because the immune system that has not been built perfectly is perfect. To know for sure which virus is infected by mosquitoes, it can diagnose by seeing symptoms perceived symptoms. Expert systems are one of the most used artificial intelligence techniques today because expert systems can act as consultations. In this case the authors make a system to start a diagnosis process with variable centered intelligent rule system (VCIRS) methods through perceived symptoms. With the facilities provided for users and administrators, allowing both users and administrators to use this system according to their individual needs. This expert system is made with the Microsoft Visual Basic 2008 programming language.Keywords: Expert System, Mayora Virus, Variable Centered Intelligent Rule System (VCIRS)The diagnosis process is the first step to knowing a type of disease. This type of disease caused by mosquitoes is one of the major viruses (MAVY), dengue hemorrhagic fever (DHF) and malaria. Sometimes not everyone can find the virus that is carried by this mosquito, usually children who are susceptible to this virus because the immune system that has not been built perfectly is perfect. To know for sure which virus is infected by mosquitoes, it can diagnose by seeing symptoms perceived symptoms.Expert systems are one of the most used artificial intelligence techniques today because expert systems can act as consultations. In this case the authors make a system to start a diagnosis process with variable centered intelligent rule system (VCIRS) methods through perceived symptoms.With the facilities provided for users and administrators, allowing both users and administrators to use this system according to their individual needs. This expert system is made with the Microsoft Visual Basic 2008 programming language.Keywords: Expert System, Mayora Virus, Variable Centered Intelligent Rule System (VCIRS)

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