Artificial Intelligence Security Issues and Responses

2020 ◽  
Author(s):  
Haining Zhao ◽  
Liquan Chen
Keyword(s):  
Artificial Intelligence ◽  
Security Issues

Data Security for Connected Governments and Organisations

2021 ◽  
pp. 229-251
Author(s):  
Heru Susanto ◽  
Leu Fang Yie ◽  
Didi Rosiyadi ◽  
Akbari Indra Basuki ◽  
Desi Setiana
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Data Security ◽  
Data Privacy ◽  
Government Agencies ◽  
Security Measures ◽  
Security Issues ◽  
The Impact ◽  
Distributed Technologies

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

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 and ISO 26000 (Guidance on Social Responsibility)

2021 ◽  
Author(s):  
Weiwei Zhao
Keyword(s):  
Artificial Intelligence ◽  
Social Responsibility ◽  
Community Involvement ◽  
Rapid Development ◽  
Final Conclusion ◽  
Privacy And Security ◽  
Organizational Governance ◽  
Iso 26000 ◽  
Security Issues ◽  
Labor Practices

With the rapid development of artificial intelligence, it has a more and more far-reaching impact on social, economic, cultural, and other fields. At the same time, artificial intelligence faces ethical, moral, privacy, and security issues. In order to realize the healthy development of artificial intelligence, it is urgent to apply the social responsibility management system to artificial intelligence. Based on the seven core subjects of social responsibility proposed by ISO 26000: organizational governance, human rights, labor practices, the environment, fair operating practices, consumer issues, and community involvement and development. In this chapter, the possible risks of artificial intelligence in these seven aspects are analyzed, and the corresponding countermeasures are discussed according to the causes of these problems. The final conclusion is the aspects that artificial intelligence should pay attention to when fulfilling its social responsibility.

Help Me Invest

2020 ◽  
pp. 257-269
Author(s):  
Manish Kumar ◽  
Mukul Sharma ◽  
Ivy Raina ◽  
Mehak Kawatra ◽  
Shubhanshu Sharma ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Investment Decision ◽  
Security Issues ◽  
Internet News ◽  
Time Period ◽  
The World ◽  
Different Types

Making an investment is very important. According to a recent study, people used to hold a commodity for about 8 years, but now the time period has reduced to about 4 months. The market is really volatile; with the help of internet, news travels really fast and is reachable to everyone in every part of the world. Buying any commodity cannot be easier, as the number of options available is very large. Different investment options bring different types of profit and risk. One of the major issues involved is the security in using such tools and applications. A good investor always makes an investment decision by calculating and analyzing various factors that could affect his profits. The advancement in artificial intelligence and computation plays an important role while analyzing these factors. Few simple lines of code can analyze the market and help evaluate various investment options. Most of these tools are available online, but they all come with security issues associated with them.

Data Security for Connected Governments and Organisations

2022 ◽  
pp. 191-213
Author(s):  
Heru Susanto ◽  
Leu Fang Yie ◽  
Didi Rosiyadi ◽  
Akbari Indra Basuki ◽  
Desi Setiana
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Data Security ◽  
Data Privacy ◽  
Government Agencies ◽  
Security Measures ◽  
Security Issues ◽  
The Impact ◽  
Distributed Technologies

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

scholarly journals Digital Technologies in the Analysis of the State of Crime in the Prosecutor's Office

2021 ◽  
Vol 8 (1) ◽  
pp. 37-44
Author(s):  
Eduard B. Khatov
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Information Security ◽  
Digital Technologies ◽  
Technical Support ◽  
The State ◽  
Crime Analysis ◽  
Security Issues

The article is devoted to the perspectives of digital technologies in crime analysis. According to the author, the key role of such analysis performed by prosecutors is played by artificial intelligence technologies, extra-big data, and electronic voice assistants. The need for their implementation, appropriate material and technical support, solutions for information security issues, as well as the training of prosecutors in the use of digital technologies, including the basics of programming and visualization of big data, were emphasized.

scholarly journals IoT Security Challenges: Cloud and Blockchain, Postquantum Cryptography, and Evolutionary Techniques

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2647
Author(s):  
Stefan Balogh ◽  
Ondrej Gallo ◽  
Roderik Ploszek ◽  
Peter Špaček ◽  
Pavol Zajac
Keyword(s):  
Artificial Intelligence ◽  
Quantum Computing ◽  
Internet Of Things ◽  
Iot Security ◽  
Security Issues ◽  
Security Challenges ◽  
Rapid Changes ◽  
The Future ◽  
Iot Devices ◽  
Security Of Iot

Internet of Things connects the physical and cybernetic world. As such, security issues of IoT devices are especially damaging and need to be addressed. In this treatise, we overview current security issues of IoT with the perspective of future threats. We identify three main trends that need to be specifically addressed: security issues of the integration of IoT with cloud and blockchains, the rapid changes in cryptography due to quantum computing, and finally the rise of artificial intelligence and evolution methods in the scope of security of IoT. We give an overview of the identified threats and propose solutions for securing the IoT in the future.

Internet of Things in Cyber Security Scope

2022 ◽  
pp. 146-187
Author(s):  
Mazoon Hashil Alrubaiei ◽  
Maiya Hamood Al-Saadi ◽  
Hothefa Shaker ◽  
Bara Sharef ◽  
Shahnawaz Khan
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Cyber Security ◽  
Rapid Evolution ◽  
The Internet ◽  
Future Directions ◽  
Iot Security ◽  
Security Issues ◽  
The World ◽  
New Challenges

IoT represents a technologically bright future where heterogeneously connected devices will be connected to the internet and make intelligent collaborations with other objects to extend the borders of the world with physical entities and virtual components. Despite rapid evolution, this environment is still facing new challenges and security issues that need to be addressed. This chapter will give a comprehensive view of IoT technologies. It will discuss the IoT security scope in detail. Furthermore, a deep analysis of the most recent proposed mechanisms is classified. This study will be a guide for future studies, which direct to three primary leading technologies—machine learning (ML), blockchain, and artificial intelligence (AI)—as intelligent solutions and future directions for IoT security issues.

scholarly journals Cyber Security in IoT-Based Cloud Computing: A Comprehensive Survey

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 16
Author(s):  
Waqas Ahmad ◽  
Aamir Rasool ◽  
Abdul Rehman Javed ◽  
Thar Baker ◽  
Zunera Jalil
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Deep Learning ◽  
Cyber Security ◽  
Industrial Applications ◽  
Future Research ◽  
Cloud Infrastructure ◽  
Security Issues ◽  
Comprehensive Survey ◽  
Security Concerns

Cloud computing provides the flexible architecture where data and resources are dispersed at various locations and are accessible from various industrial environments. Cloud computing has changed the using, storing, and sharing of resources such as data, services, and applications for industrial applications. During the last decade, industries have rapidly switched to cloud computing for having more comprehensive access, reduced cost, and increased performance. In addition, significant improvement has been observed in the internet of things (IoT) with the integration of cloud computing. However, this rapid transition into the cloud raised various security issues and concerns. Traditional security solutions are not directly applicable and sometimes ineffective for cloud-based systems. Cloud platforms’ challenges and security concerns have been addressed during the last three years, despite the successive use and proliferation of multifaceted cyber weapons. The rapid evolution of deep learning (DL) in the artificial intelligence (AI) domain has brought many benefits that can be utilized to address industrial security issues in the cloud. The findings of the proposed research include the following: we present a comprehensive survey of enabling cloud-based IoT architecture, services, configurations, and security models; the classification of cloud security concerns in IoT into four major categories (data, network and service, applications, and people-related security issues), which are discussed in detail; we identify and inspect the latest advancements in cloud-based IoT attacks; we identify, discuss, and analyze significant security issues in each category and present the limitations from a general, artificial intelligence and deep learning perspective; we provide the technological challenges identified in the literature and then identify significant research gaps in the IoT-based cloud infrastructure to highlight future research directions to blend cybersecurity in cloud.

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