Pub Crawl #44
Pub Crawl summarizes, by hard problems, sets of publications that have been peer reviewed and presented at SoS conferences or referenced in current work. The topics are chosen for their usefulness for current researchers. Select the topic name to view the corresponding list of publications. Submissions and suggestions are welcome.
6LoWPAN, IPv6 over Low power Wireless Personal Area Networks, is an architecture intended to allow low power devices to participate in the Internet of Things. The IEEE specification allows for operation in either a secure or non-secure mode. For the Science of Security community, the creation of secure process in low power and ad hoc environments relates to the hard problems of resilience and composability. In the IoT context, it also relates to cyber physical system security.
As the power of digital signal processors has increased, adaptive filters are now routinely used in many devices as varied as mobile phones, printers, cameras, power systems, GPS devices and medical monitoring equipment. An adaptive filter uses an optimization algorithm in a system with a linear filter to adjust parameters that have a transfer function controlled by variable parameter. Because of the complexity of the optimization algorithms, most of these adaptive filters are digital filters. They are required for some applications because some parameters of the desired processing operation are not known in advance or are changing. The works cited here are articles about adaptive filtering as it relates to the Science of Security hard problems of scalability, resilience, and metrics.
Ad Hoc Network Security 2020 (all)
Ad Hoc Network Security 2020 Security is an important research issue for ad hoc networks (MANETs). For the Science of Security community, this work relates to the hard problems of resilience, metrics, and compositionality.
Privacy issues related to Big Data are a growing area of interest for researchers. The work presented here addresses methodologies to protect personal information using both technical and policy solutions. For the Science of Security community, this work is relevant to human factors, resilience, scalability, and metrics.
Bluetooth is a standard for short-range wireless interconnection of cellular phones, computers, and other electronic devices. In common use, it is important to the Science of Security because of its relevance to human behavior, resilient architectures, cyber physical systems, and composability.
Coding Theory and Security 2020 (all)
Coding theory examines the properties of codes and their aptness for a specific application. For the Science of Security, coding theory is relevant to compositionality, resilience, cryptography, and metrics.
Computing Theory and Trust 2019 (all)
The works cited here combine research into computing theory with research into trust between humans and humans, humans and computers, and between computers.
Coupled Congestion Control 2018 (all)
Congestion control algorithms are used to quickly restore normal operation of a network when congestion occurs. For the Science of Security community, this work is relevant to resilience and scalability.
Coupled Congestion Control 2019 (all)
Congestion control algorithms are used to quickly restore normal operation of a network when congestion occurs. For the Science of Security community, this work is relevant to resilience and scalability.
Human behavior is complex. That complexity creates a tremendous problem for cybersecurity. The works cited here address a range of human trust issues related to behaviors, deception, enticement, sentiment and other factors difficult to isolate and quantify. For the Science of Security community, human behavior is a Hard Problem.
Human behavior is complex. That complexity creates a tremendous problem for cybersecurity. The works cited here address a range of human trust issues related to behaviors, deception, enticement, sentiment and other factors difficult to isolate and quantify. For the Science of Security community, human behavior is a hard problem.
Intrusion detection systems defend communications, computer and other information systems against malicious attacks by identifying attacks and attackers. The topic relates to the Science of Security issues of resilience and composability.
Intelligent Data Security 2018 (all)
The term “intelligent data” refers to data that directly feeds decision-making processes. It has real time critical importance and therefore needs a high degree of integrity. For the Science of Security community, it is important to the hard problems of resilience, scalability, and compositionality.
Intelligent Data Security 2019 (all)
The term “intelligent data” refers to data that directly feeds decision-making processes. It has real time critical importance and therefore needs a high degree of integrity. For the Science of Security community, it is important to the hard problems of resilience, scalability, and compositionality.
Internet-scale Computing Security 2018 (all)
Addressing security at Internet scale relates to all of the hard problems of the Science of Security.
Internet-scale Computing Security 2019 (all)
Addressing security at Internet scale relates to all of the hard problems of the Science of Security.
Magnetic remanence is the property that allows an attacker to recreate files that have been overwritten. For the Science of Security community, it is a topic relevant to the hard problems of resilience and compositionality and has major implications for the Internet of Things and other cyber physical systems.
Magnetic remanence is the property that allows an attacker to recreate files that have been overwritten. For the Science of Security community, it is a topic relevant to the hard problems of resilience and compositionality and has major implications for the Internet of Things and other cyber physical systems.
Malware Analysis and Graph Theory 2019 (all)
Malware analysis is generally signature based. Graph theory has the potential to provide more rigor in analyzing malware as a tool for mining large data sets. For the Science of Security community, malware classification is related to privacy, predictive metrics, human behavior and resiliency.
Metadata Discovery Problem 2019 (all)
Metadata is often described as “data about data.” Usage varies from virtualization to data warehousing to statistics. Because of its volume and complexity, metadata has the potential to tax security procedures and processes. For the Science of Security community, work in this area is relevant to the problems of scalability, resilience, and compositionality.
Neural Style Transfer 2018 (all)
Neural style transfer is receiving significant attention and showing results. One approach trains by defining and optimizing perceptual loss functions in feed-forward convolutional neural networks. Work in this area addresses security issues relative to AI and ML and the hard problems of scalability, resilience, and predictive metrics.
Neural Style Transfer 2019 (all)
Neural style transfer is receiving significant attention and showing results. One approach trains by defining and optimizing perceptual loss functions in feed-forward convolutional neural networks. Work in this area addresses security issues relative to AI and ML and the hard problems of scalability, resilience, and predictive metrics.
Robot Operating Systems Security 2018 (all)
The Robot Operating System (ROS) is a widely adopted standard robotic middleware that is devoid of native security features. With the increased use of robots and the risk to both the machine and the interacting human, consideration of this topic has become important. To the Science of Security community, it is relevant to the hard problems of resilience, policy-based governance, and human factors.
Robot Operating Systems Security 2019 (all)
The Robot Operating System (ROS) is a widely adopted standard robotic middleware that is devoid of native security features. With the increased use of robots and the risk to both the machine and the interacting human, consideration of this topic has become important. To the Science of Security community, it is relevant to the hard problems of resilience, policy-based governance, and human factors.
Robot Operating Systems Security 2020 (all)
The Robot Operating System (ROS) is a widely adopted standard robotic middleware that is devoid of native security features. With the increased use of robots and the risk to both the machine and the interacting human, consideration of this topic has become important. To the Science of Security community, it is relevant to the hard problems of resilience, policy-based governance, and human factors.
The proliferation of robots in the form of personal assistants, medical support devices, and other applications has heighted awareness of security issues with them. Of particular interest here is trust—the confidence the human has that the machine has not been compromised, nor the ones it has been linked to are compromised. For the Science of Security community, this relates to the hard problems of resilience and of human factors.
The proliferation of robots in the form of personal assistants, medical support devices, and other applications has heighted awareness of security issues with them. Of particular interest here is trust—the confidence the human has that the machine has not been compromised, nor the ones it has been linked to are compromised. For the Science of Security community, this relates to the hard problems of resilience and of human factors.
Science of Security 2019 (all)
Many more articles and research studies are appearing with “Science of Security” as a keyword. The articles cited here discuss the degree to which security is a science and various issues surrounding its development, ranging from basic approach to essential elements. The articles cited here address the fundamental concepts of the Science of Security.
Support Vector Machines 2020 (all)
The Support Vector Machine (SVM) algorithm has been used to analyze data for classification and to perform regression analysis. For the Science of Security community, SVM is related to machine learning and relevant to solving the hard problems of composability, resilience and predictive metrics.
Swarm Intelligence is a concept using the metaphor of insect colonies to describe decentralized, self-organized systems. The method is often used in artificial intelligence, and there are about a dozen variants ranging from ant colony optimization to stochastic diffusion. For cybersecurity, these systems have significant value both offensively and defensively. For the Science of Security, swarm intelligence relates to composability and compositionality.
A Sybil attack occurs when a node in a network claims multiple identities. The attacker may subvert the entire reputation system of the network by creating a large number of false identities and using them to gain influence. For the Science of Security community, these attacks are relevant to resilience, metrics, and composability.
Time Frequency Analysis and Security 2019 (all)
Time-frequency analysis is a useful method that allows simultaneous consideration of both the time and frequency domains. It is useful to the Science of Security community for analysis in cyber-physical systems and toward solving the hard problems of resilience, predictive metrics, and scalability.
Trusted Platform Modules 2019 (all)
A Trusted Platform Module (TPM) is a computer chip that can securely store artifacts used to authenticate a network or platform. These artifacts can include passwords, certificates, or encryption keys. A TPM can also be used to store platform measurements that help ensure that the platform remains trustworthy. Interest in TPMs is growing due to their potential for solving hard problems in security such as composability and cyber-physical system security and resilience.
Trustworthiness is created in information security through cryptography to assure the identity of external parties. They are essential to cybersecurity and to the Science of Security hard problem of composability.
Trustworthiness is created in information security through cryptography to assure the identity of external parties. They are essential to cybersecurity and to the Science of Security hard problem of composability.
Articles listed on these pages have been found on publicly available internet pages and are cited with links to those pages. Some of the information included herein has been reprinted with permission from the authors or data repositories. Direct any requests for removal via email of the links or modifications to specific citations. Please include the URL of the specific citation in your correspondence.
Pub Crawl contains bibliographical citations, abstracts if available, links on specific topics, and research problems of interest to the Science of Security community.
How recent are these publications?
These bibliographies include recent scholarly research on topics that have been presented or published within the stated year. Some represent updates from work presented in previous years; others are new topics.
How are topics selected?
The specific topics are selected from materials that have been peer reviewed and presented at SoS conferences or referenced in current work. The topics are also chosen for their usefulness for current researchers.
How can I submit or suggest a publication?
Researchers willing to share their work are welcome to submit a citation, abstract, and URL for consideration and posting, and to identify additional topics of interest to the community. Researchers are also encouraged to share this request with their colleagues and collaborators.
What are the hard problems?
Select a hard problem to retrieve related publications.
- - Scalability and Composability: Develop methods to enable the construction of secure systems with known security properties from components with known security properties, without a requirement to fully re-analyze the constituent components.
- - Policy-Governed Secure Collaboration: Develop methods to express and enforce normative requirements and policies for handling data with differing usage needs and among users in different authority domains.
- - Security Metrics Driven Evaluation, Design, Development, and Deployment: Develop security metrics and models capable of predicting whether or confirming that a given cyber system preserves a given set of security properties (deterministically or probabilistically), in a given context.
- - Resilient Architectures: Develop means to design and analyze system architectures that deliver required service in the face of compromised components.
- - Understanding and Accounting for Human Behavior: Develop models of human behavior (of both users and adversaries) that enable the design, modeling, and analysis of systems with specified security properties.