research paper on artificial intelligence in cyber security

Artificial Intelligence in Cyber Security

15 Pages Posted: 18 Jan 2024

Md Fazley Rafy

West Virginia University - Benjamin M. Statler College of Engineering and Mineral Resources

Date Written: January 1, 2024

The unprecedented pace of technology has been significantly influenced by the integration of Artificial Intelligence (AI). The ubiquity of AI spans various domains, garnering both criticism and acclaim. Its growing application presents both advantages and drawbacks in cybersecurity, as it becomes a standard component in the development and operational phases of contemporary technologies. This paper provides a comprehensive overview of AI utilization in cybersecurity, exploring its benefits, challenges, and potential negative impacts. In addition to that, it explores AI-based models that enhance or compromise security across various infrastructures and cyber networks. The paper critically examines the role of AI in developing cybersecurity applications, proposes strategies for leveraging emerging technologies to counteract AI-generated threats and vulnerabilities, and addresses the socio-economic repercussions of the involvement of AI in cybersecurity.

Keywords: Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Expert Systems, Natural Language Processing, Threat Detection, Real-time Mitigation, Social Media Security, AI-driven Threat Intelligence, Predictive Analytics, Adversarial Attacks, Privacy Concerns, Ethical Considerations

Suggested Citation: Suggested Citation

Md Fazley Rafy (Contact Author)

West virginia university - benjamin m. statler college of engineering and mineral resources ( email ).

United States

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Artificial Intelligence in CyberSecurity

Submission Deadline: 30 July 2019

IEEE Access invites manuscript submissions in the area of Artificial Intelligence in CyberSecurity.

Recent studies show that Artificial Intelligence (AI) has resulted in advances in many scientific and technological fields, i.e., AI-based medicine, AI-based transportation, and AI-based finance. It can be imagined that the era of AI will be coming to us soon. The Internet has become the largest man-made system in human history, which has a great impact on people’s daily life and work. Security is one of the most significant concerns in the development of a sustainable, resilient and prosperous Internet ecosystem. Cyber security faces many challenging issues, such as intrusion detection, privacy protection, proactive defense, anomalous behaviors, advanced threat detection and so on. What’s more, many threat variations emerge and spread continuously. Therefore, AI-assisted, self-adaptable approaches are expected to deal with these security issues. Joint consideration of the interweaving nature between AI and cyber security is a key factor for driving future secure Internet.

The use of AI in cybersecurity creates new frontiers for security research. Specifically, the AI analytic tools, i.e., reinforcement learning, big data, machine learning and game theory, make learning increasingly important for real-time analysis and decision making for quick reactions to security attacks. On the other hand, AI technology itself also brings some security issues that need to be solved. For example, data mining and machine learning create a wealth of privacy issues due to the abundance and accessibility of data. AI-based cyber security has a great impact on different industrial applications if applied in appropriate ways, such as self-driving security, secure vehicular networks, industrial control security, smart grid security, etc. This Special Section in IEEE Access will focus on AI technologies in cybersecurity and related issues. We also welcome research on AI-related theory analysis for security and privacy.

The topics of interest include, but are not limited to:

• Reinforcement learning for cybersecurity
• Machine learning for proactive defense
• Big data analytics for security
• Big data anonymization
• Big data-based hacking incident forecasting
• Big data analytics for secure network management
• AI-based intrusion detection and prevention
• AI approaches to trust and reputation
• AI-based anomalous behavior detection
• AI-based privacy protection
• AI for self-driving security
• AI for IoT security
• AI for industrial control security
• AI for smart grid security
• AI for security in innovative networking
• AI security applications

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August 8, 2024

CISA, DARPA officials see cyber advantages among the risks posed by artificial intelligence

LAS VEGAS. Senior officials from the Cybersecurity and Infrastructure Security Agency and the Pentagon’s advanced research agency discussed the beneficial roles artificial intelligence can play for securing data and systems, as well as concerns over a “rush to market” with AI products that haven’t been fully vetted for security weaknesses, in presentations at the AI Summit at Black Hat.

The Tuesday AI summit featured discussions with Lisa Einstein, the new chief AI officer at CISA, and Kathleen Fisher, director of...

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Investigating the applications of artificial intelligence in cyber security

• Published: 09 September 2019
• Volume 121 , pages 1189–1211, ( 2019 )

Cite this article

• Naveed Naeem Abbas 1 , 2 ,
• Tanveer Ahmed 3 ,
• Syed Habib Ullah Shah 1 , 4 ,
• Muhammad Omar   ORCID: orcid.org/0000-0002-7071-5760 1 &
• Han Woo Park 5  

6011 Accesses

29 Citations

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Artificial Intelligence (AI) provides instant insights to pierce through the noise of thousands of daily security alerts. The recent literature focuses on AI’s application to cyber security but lacks visual analysis of AI applications. Structural changes have been observed in cyber security since the emergence of AI. This study promotes the development of theory about AI in cyber security, helps researchers establish research directions, and provides a reference that enterprises and governments can use to plan AI applications in the cyber security industry. Many countries, institutions and authors are densely connected through collaboration and citation networks. Artificial neural networks, an AI technique, gave birth to today’s research on cloud cyber security. Many research hotspots such as those on face recognition and deep neural networks for speech recognition may create future hotspots on emerging technology, such as on artificial intelligence systems for security. This study visualizes the structural changes, hotspots and emerging trends in AI studies. Five evaluation factors are used to judge the hotspots and trends of this domain and a heat map is used to identify the areas of the world that are generating research on AI applications in cyber security. This study is the first to provide an overall perspective of hotspots and trends in the research on AI in the cyber security domain.

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Acknowledgements

I wish to acknowledge someone who means a lot to me, my father (Mr. Irshad Hussain), for showing faith in me and giving me the liberty to make my own choices. I salute you for the selfless love, care, pain and sacrifice you offered to me in order to shape my life.

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Naveed Naeem Abbas, Syed Habib Ullah Shah & Muhammad Omar

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Abbas, N.N., Ahmed, T., Shah, S.H.U. et al. Investigating the applications of artificial intelligence in cyber security. Scientometrics 121 , 1189–1211 (2019). https://doi.org/10.1007/s11192-019-03222-9

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Received : 16 June 2019

Published : 09 September 2019

Issue Date : November 2019

DOI : https://doi.org/10.1007/s11192-019-03222-9

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Big Data, Artificial Intelligence, and Financial Economics

The proliferation of large unstructured datasets along with advances in artificial intelligence (AI) technology provides researchers in financial economics with new opportunities for data analysis, and it also changes the set of subjects these researchers are studying. As AI becomes increasingly important in making decisions using financial market data, it becomes crucial to study how AI interacts with both data resources and with human decisionmakers. 

To promote research on emerging issues related to the methodology, applications, and socioeconomic implications of the growing availability of large datasets and AI tools, the National Bureau of Economic Research (NBER), with the generous support of the Office of Financial Research (OFR) and in collaboration with the Review of Financial Studies (RFS) , will convene a research conference on December 13, 2024. The program will be organized by RFS  Executive Editor Tarun Ramadorai of Imperial College London, and NBER Research Associates Itay Goldstein of the University of Pennsylvania, Chester Spatt of Carnegie Mellon University, and Mao Ye of Cornell University.

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 •  Unstructured Data Analysis and AI: The impact on financial markets of the growing use of AI technology to analyze unstructured data, such as text, images, audio, and video.

 •  Trading and AI: The impact of using AI in high-frequency trading, algorithmic trading, and the impacts of this use on financial markets.

 •  Big Data and AI in Investment: The rise of machines in asset management, particularly the growing analysis of high-dimensional datasets using machine learning techniques.

 •  Big Data and AI in Corporate Decisions: The impact of AI as well as other means of analyzing unstructured datasets and automating decision-making on corporate decisions, such as capital budgeting, working capital management, and regulatory compliance and reporting.

 •  Financial Institutions and Financial Intermediation: The impact of AI, fintech, and the analysis of large datasets on traditional financial institutions.

 •  AI and Regulation: The role of AI in detecting improper market conduct, the regulation of algorithms and winner-take-all markets, and strategies for ensuring accountability, fairness and transparency in AI models.

The organizers welcome submissions of both empirical and theoretical research papers and encourage submissions from scholars who are early in their careers, who are not NBER affiliates, and who are from under-represented groups in the financial economics profession.  Papers that are submitted for presentation at the conference may also be submitted to the RFS  under its dual review system at no extra cost. Papers that are rejected at any stage of this process are not considered to have been “rejected” at the RFS .  Authors may submit a future version of the same paper to the RFS , even if the paper is not selected for presentation at the conference. For a paper to be considered under the dual submission option, it may not be under review or invited revision at any journal, including the RFS, until the author has been notified of the outcome of the dual submission process. The details of the dual submission program may be found at http://sfs.org/dualsubmissionpolicy/. To be considered for inclusion on the program, papers must be uploaded by 11:59 pm EDT on Thursday, September 12, 2024 to one of the following sites:

For submissions to both the conference and the Review of Financial Studies

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Please do not submit papers that have been accepted for publication or that will be published before the conference. Authors chosen to present papers will be notified in October, 2024. All presenters are expected to attend the meeting in person. The NBER will cover the travel and lodging cost of up to two presenters per paper. 

Questions about this conference may be addressed to  [email protected] .

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FACT SHEET: Biden- ⁠ Harris Administration Announces New AI Actions and Receives Additional Major Voluntary Commitment on   AI

Nine months ago, President Biden issued a landmark Executive Order to ensure that America leads the way in seizing the promise and managing the risks of artificial intelligence (AI). This Executive Order built on the voluntary commitments he and Vice President Harris received from 15 leading U.S. AI companies last year. Today, the administration announced that Apple has signed onto the voluntary commitments, further cementing these commitments as cornerstones of responsible AI innovation. In addition, federal agencies reported that they completed all of the 270-day actions in the Executive Order on schedule, following their on-time completion of every other task required to date . Agencies also progressed on other work directed for longer timeframes. Following the Executive Order and a series of calls to action made by Vice President Harris as part of her major policy speech before the Global Summit on AI Safety, agencies all across government have acted boldly. They have taken steps to mitigate AI’s safety and security risks, protect Americans’ privacy, advance equity and civil rights, stand up for consumers and workers, promote innovation and competition, advance American leadership around the world, and more. Actions that agencies reported today as complete include the following: Managing Risks to Safety and Security: Over 270 days, the Executive Order directed agencies to take sweeping action to address AI’s safety and security risks, including by releasing vital safety guidance and building capacity to test and evaluate AI. To protect safety and security, agencies have:

• Released for public comment new technical guidelines from the AI Safety Institute (AISI) for leading AI developers in managing the evaluation of misuse of dual-use foundation models. AISI’s guidelines detail how leading AI developers can help prevent increasingly capable AI systems from being misused to harm individuals, public safety, and national security, as well as how developers can increase transparency about their products.
• Published final frameworks on managing generative AI risks and securely developing generative AI systems and dual-use foundation models. These documents by the National Institute of Standards and Technology (NIST) will provide additional guidance that builds on NIST’s AI Risk Management Framework, which offered individuals, organizations, and society a framework to manage AI risks and has been widely adopted both in the U.S. and globally. NIST also submitted a report to the White House outlining tools and techniques to reduce the risks from synthetic content.
• Developed and expanded AI testbeds and model evaluation tools at the Department of Energy (DOE). DOE, in coordination with interagency partners, is using its testbeds to evaluate AI model safety and security, especially for risks that AI models might pose to critical infrastructure, energy security, and national security. DOE’s testbeds are also being used to explore novel AI hardware and software systems, including privacy-enhancing technologies that improve AI trustworthiness. The National Science Foundation (NSF) also launched an initiative to help fund researchers outside the federal government design and plan AI-ready testbeds.
• Reported results of piloting AI to protect vital government software.  The Department of Defense (DoD) and Department of Homeland Security (DHS) reported findings from their AI pilots to address vulnerabilities in government networks used, respectively, for national security purposes and for civilian government. These steps build on previous work to advance such pilots within 180 days of the Executive Order.
• Issued a call to action from the Gender Policy Council and Office of Science and Technology Policy to combat image-based sexual abuse, including synthetic content generated by AI. Image-based sexual abuse has emerged as one of the fastest growing harmful uses of AI to-date, and the call to action invites technology companies and other industry stakeholders to curb it. This call flowed from Vice President Harris’s remarks in London before the AI Safety Summit, which underscored that deepfake image-based sexual abuse is an urgent threat that demands global action.

Bringing AI Talent into Government Last year, the Executive Order launched a government-wide AI Talent Surge that is bringing hundreds of AI and AI-enabling professionals into government. Hired individuals are working on critical AI missions, such as informing efforts to use AI for permitting, advising on AI investments across the federal government, and writing policy for the use of AI in government.

• To increase AI capacity across the federal government for both national security and non-national security missions, the AI Talent Surge has made over 200 hires to-date, including through the Presidential Innovation Fellows AI cohort and the DHS AI Corps .
• Building on the AI Talent Surge 6-month report , the White House Office of Science and Technology Policy announced new commitments from across the technology ecosystem, including nearly $100 million in funding, to bolster the broader public interest technology ecosystem and build infrastructure for bringing technologists into government service.

Advancing Responsible AI Innovation President Biden’s Executive Order directed further actions to seize AI’s promise and deepen the U.S. lead in AI innovation while ensuring AI’s responsible development and use across our economy and society. Within 270 days, agencies have:

• Prepared and will soon release a report on the potential benefits, risks, and implications of dual-use foundation models for which the model weights are widely available, including related policy recommendations. The Department of Commerce’s report draws on extensive outreach to experts and stakeholders, including hundreds of public comments submitted on this topic.
• Awarded over 80 research teams’ access to computational and other AI resources through the National AI Research Resource (NAIRR) pilot —a national infrastructure led by NSF, in partnership with DOE, NIH, and other governmental and nongovernmental partners, that makes available resources to support the nation’s AI research and education community. Supported projects will tackle deepfake detection, advance AI safety, enable next-generation medical diagnoses and further other critical AI priorities.
• Released a guide for designing safe, secure, and trustworthy AI tools for use in education. The Department of Education’s guide discusses how developers of educational technologies can design AI that benefits students and teachers while advancing equity, civil rights, trust, and transparency. This work builds on the Department’s 2023 report outlining recommendations for the use of AI in teaching and learning.
• Published guidance on evaluating the eligibility of patent claims involving inventions related to AI technology,  as well as other emerging technologies. The guidance by the U.S. Patent and Trademark Office will guide those inventing in the AI space to protect their AI inventions and assist patent examiners reviewing applications for patents on AI inventions.
• Issued a report on federal research and development (R&D) to advance trustworthy AI over the past four years. The report by the National Science and Technology Council examines an annual federal AI R&D budget of nearly $3 billion.
• Launched a $23 million initiative to promote the use of privacy-enhancing technologies to solve real-world problems, including related to AI.  Working with industry and agency partners, NSF will invest through its new Privacy-preserving Data Sharing in Practice program in efforts to apply, mature, and scale privacy-enhancing technologies for specific use cases and establish testbeds to accelerate their adoption.
• Announced millions of dollars in further investments to advance responsible AI development and use throughout our society. These include $30 million invested through NSF’s Experiential Learning in Emerging and Novel Technologies program—which supports inclusive experiential learning in fields like AI—and $10 million through NSF’s ExpandAI program, which helps build capacity in AI research at minority-serving institutions while fostering the development of a diverse, AI-ready workforce.

Advancing U.S. Leadership Abroad President Biden’s Executive Order emphasized that the United States lead global efforts to unlock AI’s potential and meet its challenges. To advance U.S. leadership on AI, agencies have:

• Issued a comprehensive plan for U.S. engagement on global AI standards.  The plan, developed by the NIST, incorporates broad public and private-sector input, identifies objectives and priority areas for AI standards work, and lays out actions for U.S. stakeholders including U.S. agencies. NIST and others agencies will report on priority actions in 180 days. 
• Developed guidance for managing risks to human rights posed by AI. The Department of State’s “Risk Management Profile for AI and Human Rights”—developed in close coordination with NIST and the U.S. Agency for International Development—recommends actions based on the NIST AI Risk Management Framework to governments, the private sector, and civil society worldwide, to identify and manage risks to human rights arising from the design, development, deployment, and use of AI. 
• Launched a global network of AI Safety Institutes and other government-backed scientific offices to advance AI safety at a technical level. This network will accelerate critical information exchange and drive toward common or compatible safety evaluations and policies.
• Launched a landmark United Nations General Assembly resolution . The unanimously adopted resolution, with more than 100 co-sponsors, lays out a common vision for countries around the world to promote the safe and secure use of AI to address global challenges.
• Expanded global support for the U.S.-led Political Declaration on the Responsible Military Use of Artificial Intelligence and Autonomy.   Fifty-five nations now endorse the political declaration, which outlines a set of norms for the responsible development, deployment, and use of military AI capabilities.

The Table below summarizes many of the activities that federal agencies have completed in response to the Executive Order:

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