Adoption of artificial intelligence and machine learning in banking systems: a qualitative survey of board of directors DOI Creative Commons

Abdullah Eskandarany

Frontiers in Artificial Intelligence, Год журнала: 2024, Номер 7

Опубликована: Ноя. 27, 2024

The aim of the paper is twofold. First to examine role board directors in facilitating adoption AI and ML Saudi Arabian banking sector. Second, explore effectiveness artificial intelligence machine learning protection sector from cyberattacks. A qualitative research approach was applied using in-depth interviews with 17 prominent banks. present study highlights both opportunities challenges integrating advanced technologies this highly regulated industry. Findings reveal that offer substantial benefits, particularly areas like threat detection, fraud prevention, process automation, enabling banks meet regulatory standards mitigate cyber threats efficiently. However, also identifies significant barriers, including limited technological infrastructure, a lack cohesive strategies, ethical concerns around data privacy algorithmic bias. Interviewees emphasized directors' critical providing strategic direction, securing resources, fostering partnerships technology providers. further importance aligning initiatives national development goals, such as Vision 2030, ensure sustained growth competitiveness. findings valuable implications for policymakers navigating complexities financial services, emerging markets.

Язык: Английский

Integrating contextual intelligence with mixture of experts for signature and anomaly-based intrusion detection in CPS security DOI
Kashif Rahim, Zia Ul Islam Nasir,

Nassar Ikram

и другие.

Neural Computing and Applications, Год журнала: 2025, Номер unknown

Опубликована: Янв. 7, 2025

Язык: Английский

Процитировано

1
Enhancing Intrusion Detection Systems with Adaptive Neuro-Fuzzy Inference Systems DOI Creative Commons
Jitender Sharma,

Sonia Sonia,

Karan Kumar

и другие.

Deleted Journal, Год журнала: 2025, Номер 5(1), С. 1 - 10

Опубликована: Янв. 10, 2025

Network security has become increasingly critical in recent years. Among the various aspects of network and considering several approaches to security, intrusion detection systems (IDSs) have gained considerable attention. The prominence this factor, among other factors is due its ability address complex uncertain nature breaches. Whenever data flow over network, precise categorization normal malicious necessary. Past IDS lack categorization. Thus, present study focuses on use adaptive neuro-fuzzy inference system (ANFIS) as a classifier categorize instances into types behavior. Using KDD99 dataset, performance ANFIS evaluated compared with that traditional machine learning models such decision trees multilayer perceptrons. Through experimentation different membership functions, Gaussian, triangular, bell-shaped, sigmoidal Gaussian functions are identified optimal for specific task. results underscore effectiveness ANFIS, leveraging strengths both artificial neural networks (ANNs) fuzzy reasoning systems. demonstrates superior capabilities understanding nonlinear interaction patterns, adapting evolving threats, facilitating rapid applications.

Язык: Английский

Процитировано

0
Intrusion detection in smart grids using artificial intelligence-based ensemble modelling DOI Creative Commons
Amjad Alsirhani, Noshina Tariq, Mamoona Humayun

и другие.

Cluster Computing, Год журнала: 2025, Номер 28(4)

Опубликована: Фев. 25, 2025

Язык: Английский

Процитировано

0
Protecting digital assets in Fintech: Essential cybersecurity measures and best practices DOI Creative Commons

Anwuli Nkemchor Obiki-Osafiele,

Edith Ebele Agu,

Njideka Rita Chiekezie

и другие.

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(8), С. 1884 - 1896

Опубликована: Авг. 23, 2024

Cybersecurity is paramount for protecting digital assets and maintaining consumer trust in the rapidly evolving fintech sector. This review paper explores essential cybersecurity measures best practices, focusing on encryption, multi-factor authentication, security audits, secure software development, network security. The also examines threat landscape, highlighting common cyber threats such as phishing, malware, insider threats, data breaches their impact operations. Future trends cybersecurity, including role of emerging technologies like artificial intelligence (AI) blockchain, are discussed, along with predictions future challenges. Strategic recommendations companies emphasize importance employee training, incident response planning, collaboration experts, regulatory compliance, continuous monitoring. concludes by underscoring necessity proactive to safeguard financial ensure integrity services. Keywords: Fintech Encryption, Multi-factor Authentication, Artificial Intelligence, Blockchain, Threat Intelligence.

Язык: Английский

Процитировано

1
Adoption of artificial intelligence and machine learning in banking systems: a qualitative survey of board of directors DOI Creative Commons

Abdullah Eskandarany

Frontiers in Artificial Intelligence, Год журнала: 2024, Номер 7

Опубликована: Ноя. 27, 2024

The aim of the paper is twofold. First to examine role board directors in facilitating adoption AI and ML Saudi Arabian banking sector. Second, explore effectiveness artificial intelligence machine learning protection sector from cyberattacks. A qualitative research approach was applied using in-depth interviews with 17 prominent banks. present study highlights both opportunities challenges integrating advanced technologies this highly regulated industry. Findings reveal that offer substantial benefits, particularly areas like threat detection, fraud prevention, process automation, enabling banks meet regulatory standards mitigate cyber threats efficiently. However, also identifies significant barriers, including limited technological infrastructure, a lack cohesive strategies, ethical concerns around data privacy algorithmic bias. Interviewees emphasized directors' critical providing strategic direction, securing resources, fostering partnerships technology providers. further importance aligning initiatives national development goals, such as Vision 2030, ensure sustained growth competitiveness. findings valuable implications for policymakers navigating complexities financial services, emerging markets.

Язык: Английский

Процитировано

1