CSIAC JOURNAL

Step into the future with the latest advancements and trends in cybersecurity. 

We blend research with subject matter expertise to provide an outlet for publicly releasable articles on new and emerging science, engineering, and technology within the cybersecurity community.

Latest Articles

Lantern: An Interactive Adversarial AI Workbench

Lantern, an innovative adversarial artificial intelligence (AI) workbench with unique features, is presented in this article. Lantern allows users to evaluate adversarial attacks quickly and interactively against artificial intelligence (AI) systems to protect them better.

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Exploiting Alpha Transparency in Images to Manipulate AI Recommender Systems

This article examines the vulnerability of artificial intelligence (AI) systems to alpha transparency attacks through a simulated cyber tabletop scenario. The research demonstrates how manipulated images with hidden content in alpha layers can exploit the discrepancy between human and machine perception and compromise various AI-driven technologies from social media algorithms to critical infrastructure analysis.

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Implementing Cybersecurity Solutions for Space Network Protection

This article focuses on improving the security of space networks by using multiple layers of protection to guard against cyberthreats and ensure the systems remain strong and reliable. It highlights the need for new encryption methods for smaller satellites, which have limited hardware capabilities, to keep their data safe. The study emphasizes the defense-in-depth model, which involves using several independent security measures to protect against different types of attacks.

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A Quantum Good Authentication Protocol

This article presents a novel network protocol that incorporates a quantum photonic channel for symmetric key distribution, a Dilithium signature to replace factor-based public key cryptography for enhanced authentication, security, and privacy. The protocol uses strong hash functions to hash original messages and verify heightened data integrity at the destination.

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Quantum Machine Learning as a Future Battlefield Multiplier

Today’s battlefield includes all types of equipment, manned and unmanned. However, in the future, battles will be relatively quiet, yet lightning fast in operations and outcomes. For example, in a remote training site, the U.S. Army is practicing the use of newly developed quantum machine-learning (QML)-enabled aerial and ground manned/unmanned systems. The form factor for the QML has decreased by orders of magnitude such that QML algorithms execute on micropayloads hosted on hypersonic platforms. Since opposing forces have similar capabilities, the goal is to deplete each other’s combat power in nanoseconds. Spread over thousands of kilometers in all directions, the QML-driven battle ends in less than five minutes, leaving thousands of drones and robotic vehicles with multiple multiprocessors decimated and neutralized.

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A Relevance Model for Threat-Centric Ranking of Cybersecurity Vulnerabilities

The relentless process of tracking and remediating vulnerabilities is a top concern for cybersecurity professionals. The key challenge is trying to identify a remediation scheme specific to in-house, organizational objectives. Without a strategy, the result is a patchwork of fixes applied to a tide of vulnerabilities, any one of which could be the point of failure in an otherwise formidable defense. Given that few vulnerabilities are a focus of real-world attacks, a practical remediation strategy is to identify vulnerabilities likely to be exploited and focus efforts toward remediating those vulnerabilities first.

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Transforming Military Leadership and Organizational Health With Artificial Intelligence

Artificial intelligence (AI) fuels not only the technological advancements in our businesses and homes but also redefines the operational frameworks of governments, military, and the broader societal constructs. The essence of this transformative power, however, finds its most compelling narrative in leadership and organizational health, where machine learning (ML), a subset of AI, plays a pivotal role. AI/ML can be used to support leaders in their efforts to manage and monitor initiatives and drive decisions. ML algorithms using continuous data collection activities can assist and support organization’s leaders through understanding if implemented initiatives are impacting operations by improving staff cross-collaboration and productivity while improving product and service innovation. Using predictive analytics to analyze trending data to predict future outcomes, leaders can determine if staying the course or pivoting in a certain direction is needed.

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Development, Test, and Evaluation of Small-Scale Artificial Intelligence Models

As data becomes more commoditized across all echelons of the U.S. Department of Defense, developing artificial intelligence/machine-learning (AI/ML) solutions allows for advanced data analysis and processing. However, these solutions require intimate knowledge of the relevant data as well as robust test and evaluation (T&E) procedures to ensure performance and trustworthiness. This article presents a case study and recommendations for developing and evaluating small-scale AI solutions. The model automates an acoustic event location system.

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Artificial Intelligence as a Force Multiplier in U.S. Military Information Campaigns

Military commanders have used information throughout warfare to influence, mislead, disrupt, or otherwise affect the enemy’s decision-making and capabilities. This article discusses the history of information operations (IOs) and enduring importance of incorporating actions in the information environment in military strategy.

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Note From the Editor-in-Chief

Artificial intelligence (AI) and machine learning (ML) represent an increasingly exciting field of computer science. A term originally coined by John McCarthy in 1956,1 AI is becoming increasingly pervasive in today’s world.

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