[AISWorld] CFP HICSS 2024 Mini-track - Information Security in the era of Artificial General Intelligence (AGI)

[Kang, Dae Youp]

--- apologies for cross postings ---

We invite you to submit your manuscripts to the "Information Security in the era of Artificial General Intelligence (AGI)" Mini-track at HICSS 2024 in Honolulu, Hawaii, January 2024.
Decision Analytics and Service Science - HICSS (hawaii.edu)<https://hicss.hawaii.edu/tracks-57/decision-analytics-and-service-science/#information-security-in-the-era-of-artificial-general-intelligence-agi-minitrack>

Conference dates:

January 3-6, 2024
For more details see:

https://hicss.hawaii.edu/

In the past decade, ICT literature experienced an increased interest in two major areas: Information and cybersecurity (ISEC), and Artificial Intelligence (AI) and machine learning (ML).
The two streams differ in that AI is a process used to achieve organizational outcomes, while ISEC is a desirable outcome that organizations try to achieve. Despite the explosive interest in the two streams of research, there has been little work in the intersection of these two streams.
Computer scientists have been exploring the use of AI and ML in ISEC technology such as anti-malware, firewalls, and IDS. These are early attempts, and much is needed to improve not only the algorithms but also the organizational implications of these approaches such as balancing type I and type II errors with work processes and user behavior.
Recent work also focused on the use of AI and machine learning to improve fraud detection. For example, some studies have employed existing machine learning techniques (e.g., support vector machine, logit, genetic algorithm, and associations) to decern fraudulent activities in financial while others have employed deep neural networks by incorporating artificial neural network, autoencoder, long short-term memory, and gated recurrent units. More recently, machine learning techniques have been used to increase the rigor and credibility of fraud detection.
In addition, there has been some work on using ML to better quantify cyber-risk and to optimize investments in ISEC. For example, recent work has developed a set of machine learning methods to identify a benchmarking peer for establishing optimal information security policies. In addition, ISEC studies used machine learning to develop efficient and autonomous information security systems such as Intrusion detection systems, mobile transaction and signal security, and federated machine learning.
This mini-track goal is two folds. First, we would like to explore ways that AI and ML could improve ISEC by (a partial list)

  1.  Exploring ways to align advanced security algorithms with organizational constraints.
  2.  Developing mechanisms to better quantify ISEC risk.
  3.  Enabling organizations to optimize their investments in ISEC.
  4.  Investigating misuse behavior patterns.
  5.  Proposing measures to prevent misuse behavior by insiders.
  6.  Investigating attack patterns.
  7.  Combating zero-day attacks.
Second, as technology progresses from traditional AI to Artificial General Intelligence (AGI), society is going to rely on AGI-type services (robotic physicians, lawyers, education). In this mini track, we would like to explore the unique ISEC challenges of these trends, such as:

  1.  Do data warehouses require different ISEC approaches than traditional databases?
  2.  What are the risks of reusable APIs?
  3.  Are AI-based security appliances easier to attack?
  4.  What would an attack on an AI-based appliance (i.e., a robot) look like?
  5.  What security mechanisms are used in AGI-based applications?

Important Dates for Paper Submission
June 15, 2023:           Submission Deadline
August 17, 2023:        Notification of Acceptance/Rejection
September 22, 2023:  Deadline for Submission of Final Manuscript for Publication
January 3-6, 2024:      HICSS Conference
For more information, please see:
Decision Analytics and Service Science - HICSS (hawaii.edu)<https://hicss.hawaii.edu/tracks-57/decision-analytics-and-service-science/#information-security-in-the-era-of-artificial-general-intelligence-agi-minitrack>

We look forward to your submissions.
Mini-track co-chairs:
Dr. Martin Kang
Dr. Anat Z. Hovav