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  1. Internet of Things (IoT) devices left behind when a home is sold create security and privacy concerns for both prior and new residents. We envision a specialized “building inspector for IoT” to help securely facilitate transfer of the home. 
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    Free, publicly-accessible full text available January 1, 2025
  2. The number of African American females participating in cyber fields is significantly low. Science, technology, engineering, and mathematics (STEM) education requires a new approach to student engagement to increase African American female participation in cybersecurity. The most common approach to engaging more African American females in STEM is to provide students access to professional images or role models active in STEM; however, more is needed. More race-centered strategies beyond role modeling are necessary to attract and retain African American females in STEM. Research studies show that integrating personal experiences and making cultural connections can help improve student participation in STEM from underrepresented populations. In 2021, faculty in the Center for Cybersecurity Assurance and Policy at Morgan State University developed and implemented the GenCyber ‘‘Females are Cyber Stars’’ (FACS) Summer Camp. This initiative targeted female African American students in Baltimore public middle schools. Thirty-nine girls participated in the virtual program during the summer of 2021, and 25 girls engaged in the in-person program during the summer of 2022. The program’s goals were to increase female students’ interest in cybersecurity and exposure to the security of IoT (Internet of Things) devices in a smart home environment. The GenCyber FACS Summer Camp incorporated culturally responsive strategies to engage the participants in an inclusive and interactive setting. Participants were given pre- and post-program surveys to assess learning outcomes and examine the impact of using culturally responsive teaching strategies. The results showed that the girls reported increased knowledge and a gain in interest in cybersecurity and computing. This paper discusses the summer program and curriculum, culturally responsive teaching strategies deployed, student learning outcomes, and perceptions of cultural responsiveness assessed in the GenCyber FACS Summer Camp. 
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    Free, publicly-accessible full text available January 1, 2025
  3. Researchers are looking into solutions to support the enormous demand for wireless communication, which has been exponentially increasing along with the growth of technology. The sixth generation (6G) Network emerged as the leading solution for satisfying the requirements placed on the telecommunications system. 6G technology mainly depends on various machine learning and artificial intelligence techniques. The performance of these machine learning algorithms is high. Still, their security has been neglected for some reason, which leaves the door open to various vulnerabilities that attackers can exploit to compromise systems. Therefore, it is essential to evaluate the security of machine learning algorithms to prevent them from being spoofed by malicious hackers. Prior research has shown that the decision tree is one of the most popular algorithms used by 80% of researchers for classification problems. In this work, we collect the dataset from a laboratory testbed of over 100 Internet of things (IoT) devices. The devices include smart cameras, smart light bulbs, Alexa, and others. We evaluate classifiers using the original dataset during the experiment and record a 98% accuracy. We then use the label-flipping attack approach to poison our dataset and record the output. As a result, flipping 10%, 20%, 30%, 40%, and 50% of the poison data generated accuracies of 86%, 74%, 64%, 54%, and 50%, respectively. 
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  4. Security and trust of Information Systems are critical in its design as they directly influence users' view and acceptance of such systems. Security can be said to be a contextual and dynamic term as there has not been a holistic, universal, and eternal security measure to date. Recent years have seen a lot of confidential and sensitive information being sent, received, and analyzed on the Internet, and a plethora of investigations on ways of developing comprehensive security solutions like encryptions, pattern recognition, and anomaly detection. This work reviews the human inspired algorithms that are particularly employed in pattern recognition and anomaly detection problems. The work discusses the components of the immune system that inspired the artificial Immune System (AIS) based algorithms for pattern and intrusion detection (IDS) problems. A detailed comparison is made between negative selection, clonal selection, and dendritic cell algorithms (danger theory) which are the three major AIS algorithms. AIS is ubiquitous in computer and information security because it is based on the theories developed through years of study and understanding of the human immune system by immunologist. The strengths and weaknesses of these algorithms are also discussed, and possible improvement suggested. 
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