With recent progress in the development of large-scale, general-purpose, fault-tolerant quantum computing (QC), significant effort is being made in the cybersecurity community to create viable long-term solutions mitigating the threat of quantum computers breaking classical public-key based security schemes. The current post-quantum cryptography (PQC) standardization process led by the National Institute of Standards and Technology (NIST) has standardized cryptographic protocols designed to be resistant to QC. PQC education is still in its early stages, with limited curricular materials available for broad distribution in an appropriate academic format. Another challenge is developing curricula for students with different levels of computing and cryptographic preparedness. The modular approach to curriculum development has been proven to be an effective method for introducing new concepts. The authors of this work have several years of experience teaching cryptography and PQC courses at two academic institutions. We introduce two types of PQC instruction modules at varying levels of complexity: Awareness and Proficiency. The suggested contents, learning outcomes, and duration for each module are presented.

With recent progress in the development of cryptographically relevant Quantum Computing (QC), significant effort is being made in the cryptography community to create viable long-term solutions against the threat of QC breaking classical public-key security schemes. The current Post-Quantum Cryptography (PQC) standardization process led by the NIST has made some selections and is about to recommend new cryptographic protocols resistant to QC. This work reports our experiences teaching a first-in-kind module- based course in Quantum-Resistant Cryptography (QRC) at two universities.

Modern society has a compelling need for computer science (CS) graduates to have sufficient knowledge and skills in Security. The recently released Computer Science Curricula 2023 (CS2023) by the ACM, IEEE Computer Society, and AAAI has a revamped Security knowledge area that inherently aims to make security unavoidable in a program curriculum. That is, by incorporating appropriate topics from the CS2023 Security Area, a CS program can prepare graduates capable of designing and developing secure computing infrastructure for modern societal functioning As there are challenges in modifying existing CS program curricula, proposing security-related changes is easier said than done.

Numerical data with bounded domains is a common data type in personal devices, such as wearable sensors. While the collection of such data is essential for third-party platforms, it raises significant privacy concerns. Local differential privacy (LDP) has been shown as a framework providing provable individual privacy, even when the third-party platform is untrusted. For numerical data with bounded domains, existing state-of-the-art LDP mechanisms are piecewise-based mechanisms, which are not optimal, leading to reduced data utility. This paper investigates the optimal design of piecewise-based mechanisms to maximize data utility under LDP. We demonstrate that existing piecewise-based mechanisms are heuristic instances of the 3-piecewise mechanism, which is far from enough to study optimality. We generalize the 3-piecewise mechanism to its most general form, i.e. m-piecewise mechanism with no pre-defined form of each piece. Under this form, we derive the closed-form optimal mechanism by combining analytical proofs and off-the-shelf optimization solvers. Next, we extend the generalized piecewise-based mechanism to the circular domain (along with the classical domain), defined on a cyclic range where the distance between the two endpoints is zero. By incorporating this property, we design the optimal mechanism for the circular domain, achieving significantly improved data utility compared with existing mechanisms. Our proposed mechanisms guarantee optimal data utility under LDP among all generalized piecewise-based mechanisms. We show that they also achieve optimal data utility in two common applications of LDP: distribution estimation and mean estimation. Theoretical analyses and experimental evaluations prove and validate the data utility advantages of our proposed mechanisms.

Vehicle-to-vehicle (V2V) communication systems in the U.S. rely on IEEE 1609.2 security protocols for message authentication using digital signatures. A key requirement for trust management in such systems is the ability to detect misbehaving vehicles, e.g., when vehicles are repeatedly forging signatures. However, this creates a new attack surface where receivers cannot determine whether the causes of signature verification failures are indeed malicious attacks. In this paper, we present our novel, open-source, USRP-based testbed and utilize it to demonstrate how a stealthy reactive jammer can exploit this vulnerability. Our novel, targeted attack is highly efficient (even given the short validity period for vehicle pseudonyms) and difficult to detect. Our experimental results show that our attack can successfully discredit a victim in prominent misbehavior detection schemes with just two minutes of jamming. Finally, we discuss the capabilities and extensibility of our testbed as well as the challenges of potential attack mitigation techniques.

Smart grid requires granular smart metering data collection at frequent time intervals. However, this introduces unique risks to consumer privacy. To address this challenge, several privacy-preserving data collection frameworks have been proposed. Data aggregation-based frameworks show promise in terms of privacy preservation. However, the related frameworks in the literature either have a high computational overhead on the smart meters or rely on architectures that may lead to single points of compromise. Also, most studies focus on solving the privacy problem and do not consider the integration of accurate billing in the framework. In this paper, we study a multiple aggregator based distributed privacy-preserving framework to address these challenges. The aggregators carry out the bulk of the computational load, thus making the framework lightweight for the smart meters. Our proposed framework and two other related schemes are deployed in an embedded environment for assessing the computational overhead on the smart meters due to temporal aggregation. The schemes are also studied via simulation to assess their end-to-end delay for spatial aggregation and scalability, and it is shown that our scheme outperforms the other two schemes. In addition, we analyze the resilience of our scheme against passive threats to privacy. A qualitative analysis of our scheme against other aggregation-based schemes in the literature is also presented in this paper.

The demand for cybersecurity professionals is projected to grow substantially, with the US Bureau of Labor Statistics reporting that employment in cybersecurity within the US will grow by 18% from 2014 to 2024, much faster than the average for all occupations. As creating a cyberspace workforce has become a matter of national security for every country, cybersecurity needs to be taught at all levels, to all students, in the educational system. The good news is that cybersecurity is also a topic that students from a wide variety of backgrounds find interesting, and as a result, it motivates them to study computing too. Over the past two decades, there has been an increased effort worldwide to incorporate computer science and computational thinking into the middle and high school curriculum. The CS10K initiative in the US has led to projects to introduce computer science at the K-12 educational level. One of these initiatives, the new Advanced Placement (AP) course in Computer Science Principles (CSP), was designed to introduce computer science in an engaging way, show students how computing is relevant in their lives, and to attract a diverse group of students to computing. The CSP Curriculum Framework allows for multiple implementations of the CSP course, permitting course designers to develop courses to engage and attract specific groups of students and that focus on specific themes in computing. This paper describes an approach to develop a new CSP course, CyberCSP, which integrates cybersecurity first principles throughout the course. The approach builds on an CSP course that was created from a previous collaboration between the Computer Science Department at Rochester Institute of Technology, Rochester, New York, and the Webster Central School District in Webster, New York. The paper discusses the background, details of the earlier CSP course, how relevant cybersecurity content was identified, and then integrated into the CSP course to create the CyberCSP variant of the Computer Science Principles course.

The growing shortage of skilled professionals in cybersecurity and forensics has increased global demand for information systems professionals. To identify and attract more students to cybersecurity and forensics programs, the authors developed a game engine along with a sequence of entertaining, engaging, and educational games, suitable for forensics and cybersecurity courses. This paper focuses on the design and development of a modular educational game framework composed of a game engine and a GUI-based game creator. Following narrative and storylines of the game via interactive dialogs and visualized abstract concepts, students are motivated and engaged to obtain the necessary knowledge. Students will also develop their problem solving skills by using real tools and technologies while playing the game. The GUI-based game creator allows educators to create and develop new educational games by only focusing on game content.

The United States Department of Homeland Security has identified 16 critical infrastructure sectors that employ computing, technology and engineering students. However, most undergraduate curricula in these disciplines do not incorporate the fundamentals of critical infrastructure protection (CIP) into their curricula in a meaningful way. This paper describes the design, development, and usage of a modular curricular framework for integrating CIP into undergraduate programs via self-contained interdisciplinary course modules; a course module is a distinct curricular unit such as a lab or teaching component for use by an instructor in existing courses without requiring any course or program modifications. The framework is designed for use in multiple disciplines, and the modules are designed for presentation at different levels of the undergraduate experience, with subsequent modules built on those presented earlier. In addition, the paper discusses assessment results obtained from the validation of the framework and modules over the past three years that covered 345 students at the community college and university levels.

The 16 critical infrastructure sectors identified by the US Department of Homeland Security employ many engineering, technology and computing graduates who increasingly face critical infrastructure protection (CIP) issues. However, most undergraduate curricula in these disciplines do not incorporate CIP in any meaningful way. This paper proposes a flexible curricular framework for integrating CIP into undergraduate education via self-contained inter-disciplinary CIP course modules; a course module is a distinct curricular unit such as a lab or teaching component for use by an instructor in existing courses without requiring any course or program modifications. The proposed course modules cover physical, human, and cyber aspects of CIP. The framework is designed for use in multiple disciplines, and the modules are designed for presentation at different levels of the undergraduate experience, with subsequent modules building on those presented earlier. This approach is intended to prepare students for careers solving problems in design, implementation, and maintenance of robust, sustainable infrastructure assets.

The mobile user population connected to the Internet continues to grow in number and hence provisioning seamless Internet service to such user is a topic of major interest. With new mobility architectures being investigated, it is important to have consistent comparative platforms and metrics. In this article, we introduce a novel and user-centric handoff cost framework to analyze handoff performance of different mobility schemes. The proposed framework helps examine the impacts of registration costs, signaling overhead, and data loss for Internet connected mobile users employing a unified cost metric. We first applied the framework to our future Internet mobility architecture, called Virtual Mobility Domains (VMDs). This architecture is user centric as it allows mobile users to avail services from overlapping mobility domains based on their mobility profiles. Next, the framework is applied to IPv6-based mobility protocols such as Hierarchical Mobile IPv6 and Proxy Mobile IPv6 to show the framework's flexibility and adaptability. Using the framework, we compare the handoff performance of IPv6-based mobility protocols to the VMD based mobility scheme. The results indicate that the handoff performance achieved with VMD is three and nine times superior to Proxy Mobile IPv6 and Hierarchical Mobile IPv6 respectively.

Wireless ad-hoc networks are vulnerable to various kinds of security threats and attacks due to relative ease of access to wireless medium and lack of a centralized infrastructure. In this paper, we seek to detect and mitigate the denial of service (DoS) attacks that prevent authorized users from gaining access to the networks. These attacks affect the service availability and connectivity of the wireless networks and hence reduce the network performance. To this end, we propose a novel cross-layer based intrusion detection system (CIDS) to identify the malicious node(s). Exploiting the information available across different layers of the protocol stack by triggering multiple levels of detection, enhances the accuracy of detection. We validate our design through simulations and also demonstrate lower occurrence of false positives

Designing a key management system is both important and challenging for wireless ad hoc networks. We have developed a secure, scalable, decentralized and robust key management solution using a hybrid (symmetric/asymmetric) key based methodology that is well suited for ad hoc networks. The nodes are grouped into clusters, and keys are distributed such that intra-cluster communication is secured using a symmetric cryptosystem and inter-cluster communication is secured using an asymmetric cryptosystem. We present a detailed analysis of the solution and simulation results. We observe that the hybrid solution provides a significant improvement in the performance of the key management solution in a highly hostile environment, and scales well to large networks.

One of the common problems faced by the wireless service providers worldwide is coping with congestion or hot spots. To handle this hot spot problem, methods that combine the existing cellular networks with ad hoc networks have been proposed. Integrated Cellular and Ad Hoc Relay (iCAR) system employs ad hoc relay stations (ARSs) within the cellular network to balance traffic loads efficiently and to share channels between cells via primary and secondary relaying. These ARSs operate in the ISM band, and therefore, do not cause interference to the cellular band. When analyzing the performance of WAR systems, there are several factors that should be taken into account These factors include the coverage area of the ARSs, the number of ARS channels, the placement of ARSs, etc. In this paper, the impact of the number of ARS channels on the performance of WAR systems is studied. To this end, a multi-dimensional Markov-chain analysis is performed for a simplified two-cell system model. Results show that, with a proper amount of ARS coverage within each cell the call blocking probabilities can be decreased significantly with a small number of channels. Results also suggest that by increasing the number of ARS channels perfect load balancing can be achieved.

The impact of random user motion on intelligent paging schemes is examined and quantified. To this end, a straight-line motion pattern and two Markov chains are presented to model the random movement of mobile users (MUs) within the location area (LA). The first Markov chain describes a two-dimensional random walk. The second gives a bias to a particular section of the LA. Results show that the cost of intelligent paging in the two cases of Markovian motion is more expensive than that of a simple straight-line motion. In this work, we also consider all-step intelligent paging and show that if intelligence is applied in all steps, a substantial reduction of at least 60% in paging cost can be achieved over sequential and one-step intelligent paging schemes.

Efficient mobility management for mobile (MS) or portable stations (PS-hand-off, channel assignment, and location management-will play an important role in future personal communication systems (PCS). Among these tasks, location management plays a critical role for wide area roaming. The key elements of location management are location registration/updating, and paging. Efficient paging algorithms may generate relatively less paging traffic such that larger location areas may become plausible to reduce location updating and signalling traffic. Deciding optimum location area size is also affected by the call arrival rate to the cell, cell boundary crossing rate of portable stations, cell size, and the allocated number of voice channels per cell. In this paper, different paging techniques are compared to find the optimum location management method for future PCS environment. To this end, a new technique called paging area updating method (PAUM) is introduced and its performance is analysed. It is shown that, for a low cell boundary crossing rate of portable stations, the proposed PAUM technique outperforms other paging techniques, especially when the call arrival rate is high.