Pub Crawl #62
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.
Hashing algorithms are used extensively in information security and forensics. Research focuses on new methods and techniques to optimize security. For the Science of Security community, this work is relevant to compositionality and resilience.
Homomorphic Encryption 2021 (all)
Homomorphic encryption shows promise but continues to demand a heavy processing load in practice. Research into homomorphism is focused on creating greater efficiencies, as well as elaborating on the underlying theory. For the Science of Security community, this work is relevant to resiliency, scalability, human factors, and metrics.
Honeypots are traps set up to detect, deflect, or in some manner, counteract attempts at unauthorized use of information systems. Generally, a honeypot consists of a computer, data, or a network site that appears to be part of a network, but is actually isolated and monitored, and which seems to contain information or a resource of value to attackers. With increased network size and complexity, the need for advanced methods is growing. Specifically, cloud and virtual security need advanced methods for malware detection and collection. For the Science of Security community, this work is relevant to resiliency, scalability, and human factors.
Human-in-the-loop (HITL) machine learning is a blend of supervised machine learning and active learning. A human influences the outcome in such a way that is difficult to reproduce. The practice of uniting human and machine intelligence to create effective machine learning algorithms is relevant to the Science of Security hard problems of Human Factors and Scalability.
Human-in-the-loop (HITL) machine learning is a blend of supervised machine learning and active learning. A human influences the outcome in such a way that is difficult to reproduce. The practice of uniting human and machine intelligence to create effective machine learning algorithms is relevant to the Science of Security hard problems of Human Factors and Scalability.
Human-in-the-loop (HITL) machine learning is a blend of supervised machine learning and active learning. A human influences the outcome in such a way that is difficult to reproduce. The practice of uniting human and machine intelligence to create effective machine learning algorithms is relevant to the Science of Security hard problems of Human Factors 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.
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.
Industrial Control Systems 2021 (all)
Industrial control systems are a vital part of the critical infrastructure. Anomaly detection in these systems is requirement to successfully build resilient and scalable systems. The work cited here addresses these two hard problems in the Science of Security.
Insider threats are a difficult problem. The research cited here looks at both intentional and accidental threats, including the effects of social engineering, and methods of identifying potential threats. For the Science of Security, insider threat relates to human behavior, as well as metrics, policy-based governance, and resilience.
Intellectual Property Security 2021 (all)
Intellectual Property protection continues to be a matter of major research interest. The topic is related to the Science of Security regarding resilience, policy-based governance, and composability.
Intelligent Data and Security 2021 (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 of Vehicles Security 2021 (all)
The term “Internet of Vehicles” refers to a system of the Internet of Things related to automobiles and other vehicles. It may include Vehicular Ad-hoc Networks (VANETs). For the Science of Security community, it is important relative to cyber physical systems, resilience, human factors and metrics.
Internet-scale Computing Security 2021 (all)
Addressing security at Internet scale relates to all of the Hard Problems of the Science of Security.
Intrusion Tolerance 2021 (all)
Intrusion tolerance refers to a fault-tolerant design approach to defending communications, computer and other information systems against malicious attack. Rather than detecting all anomalies, tolerant systems only identify those intrusions which lead to security failures. The topic relates to the Science of Security issues of resilience and composability.
The Internet of Battlefield Things (IoBT) is distinct from the general Internet of Things due to the nature of the hardened specific networks employed under battlefield conditions. For the Science of Security community, this work is relevant to scalability, resilience, and human factors.
Science of Security 2020 (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.
Taint analysis is an important method for analyzing software to determine possible paths for exploitation. As such, it relates to the problems of composability and metrics.
Tamper resistance is an important element for composability of software systems and for security of cyber physical system resilience. For the Science of Security community, it is also relevant to scalability, metrics, and human factors.
The term “text analytics” refers to linguistic, statistical, and machine learning techniques that model and structure the information content of textual sources for intelligence, exploratory data analysis, research, or investigation. The research cited here focuses on large volumes of text mined to identify insider threats, intrusions, and malware detection. It is of interest to the Science of Security community relative to metrics, scalability and composability, and human factors.
Theoretical Cryptography 2021 (all)
Cryptography can only exist if there is a mathematical hardness to it constructed to maintain a desired functionality, even under malicious attempts to change or destroy the prescribed functionality. The foundations of theoretical cryptography are the paradigms, approaches and techniques used to conceptualize, define and provide solutions to natural ``security concerns' mathematically using probability-based definitions, various constructions, complexity theoretic primitives and proofs of security. For the Science of Security community, this work is relevant to the broad problem of developing a science, as well as contributing to the solution of the hard problems of composability and compositionality.
Threat mitigation is a continuous need in cybersecurity. For the Science of Security community, threat mitigation is related to resiliency, metrics, and human behavior.
As systems become larger and more complex, the surface that hackers can attack also grows. Is this set of recent research articles, topics are explored that include smartphone malware, zero-day polymorphic worm detection, source identification, drive-by download attacks, two-factor face authentication, semantic security, and code structures. Of particular interest to the Science of Security community are the research articles focused on measurement and on privacy.
Trojan Horse Detection 2021 (all)
Detection and neutralization of hardware-embedded Trojans is a difficult problem. Current research is attempting to find ways to develop detection methods and processes and to automate the process. This research is relevant to cyber physical systems security, resilience and composability, as well as being an issue in supply chain security.
Ubiquitous Computing 2021 (all)
Ubiquitous computing is a concept in software engineering and computer science where computing is made to appear anytime and everywhere. In contrast to desktop computing, ubiquitous computing can occur using any device, in any location, and in any format. Incorporating all aspects of the cyber world, including the internet, the processor, the Cloud, and so on, ubiquitous computing has significant security challenges. The Science of Security community, the work cited here is relevant to scalability, metrics, human factors and resilience.
Underwater Networks Security 2021 (all)
Underwater networks have some unique security issues related to the environment they operate in. For the Science of security community, the research conducted and presented here is relevant to cyber-physical systems and work on resiliency, metrics, and scalability.
User Privacy in the Cloud 2021 (all)
Privacy is a major problem for distributed file systems, that is, in the Cloud. For the Science of Security community, this work is relevant to scalability, resilience, and metrics.
Video surveillance is a fast-growing area of public security. With it have come policy issues related to privacy. Technical issues and opportunities have also arisen, including the potential to use advanced methods to provide positive identification, abnormal behaviors in crowds, intruder detection, and information fusion with other data. For the Science of Security community, it is relevant to human behavior, metrics, and resiliency.
Virtual Machine Security 2021 (all)
Arguably, virtual machines are more secure than actual machines. This idea is based on the notion that an attacker cannot jump the gap between the virtual and the actual. The growth of interest in cloud computing suggest it is time for a fresh look at the vulnerabilities in virtual machines. In the articles presented below, security concerns are addressed in some interesting ways. For the Science of Security community, virtualization is related to composability, resiliency, cyber physical systems, and cryptography.
Visible Light Communications Security 2021 (all)
Visible light communication (VLC) offers an unregulated and free light spectrum and potentially could be a solution for overcoming overcrowded radio spectrum, especially for wireless communication systems, and doing it securely. For the Science of Security community, this work is relevant to resiliency, scalability, and metrics.
Vulnerability Detection 2021 (all)
Vulnerability detection is a topic for which a great deal of research is being done. For the Science of Security community, vulnerability detection research is relevant to human behavior, resiliency, compositionality, and metrics.
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.