Pub Crawl #57
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.
The proliferation and increased capability of “smart phones” has also increased security issues for users. For the Science of Security community, these small computing platforms have the same hard problems to solve as main frames, data centers, or desktops. The research cited here looked at encryption issues specific to the Android operating system. For the Science of Security community, this research is relevant to scalability, human behavior, metrics, and resilience.
Artificial Intelligence Security 2021 (all)
John McCarthy, coined the term "Artificial Intelligence" in 1955 and defined it as "the science and engineering of making intelligent machines." (as quoted in Poole, Mackworth & Goebel, 1998) AI research is highly technical and specialized, and has been characterized as "deeply divided into subfields that often fail to communicate with each other." (McCorduck, Pamela (2004), Machines Who Think (2nd ed.) These divisions are attributed to both technical and social factors. For the Science of Security community, AI research has implications for resilience, composability, metrics, and human behavior.
Artificial Neural Networks 2021 (all)
Artificial neural networks have been used to solve a wide variety of tasks that are hard to solve using ordinary rule-based programming. What has attracted much interest in neural networks is the possibility of learning. Tasks such as function approximation, classification pattern and sequence recognition, anomaly detection, filtering, clustering, blind source separation and compression and controls all have security implications. Cyber physical systems, resiliency, policy-based governance and metrics are the Science of Security interests.
Asymmetric Encryption 2021 (all)
Asymmetric, or public key, encryption is a cornerstone of cybersecurity. The research presented here looks at key distribution, compares symmetric and asymmetric security, and evaluates cryptographic algorithms, among other approaches. For the Science of Security community, encryption is a primary element for resiliency, compositionality, metrics, and behavior.
Security analysts use attack graphs for detection, defense and forensics. An attack graph is defined as a representation of all paths through a system that end in a state where an intruder has successfully breached the system. They are an important tool for the Science of Security related to predictive metrics, resiliency, and composability.
Keeping the attack surface as small as possible is a basic security measure. That attack surface is the sum of the different points where an adversary or unauthorized user can attempt to access in order to try to enter data to or extract data. For the Science of Security community, attack surface is a key concept for scalability, resilience, and metrics.
Attack vectors are paths or means by which an adversary can gain access to a computer or network server to deliver malware. Attack vectors enable exploitation of system vulnerabilities, including the human element. For the Science for Security community, this problem is related to resiliency and scalability, as well as human behavior.
Attestation is the verification of changes to software as part of trusted computing. For the Science of Security community, it is relevant to composability, resilience, and human behavior.
Attribution of the source of an attack or the author of malware is a continuing problem in computer forensics. For the Science of Security community, it is an important issue related to human behavior, metrics, and composability.
Attribute-based Encryption 2021 (all)
In an attribution-based encryption system, the decryption of a ciphertext should be possible only if the set of attributes of the user key matches the attributes of the ciphertext. The two types of attribute-based encryption schemes are key-policy attribute-based encryption and ciphertext-policy attribute-based encryption. For the Science of Security community, this research is relevant to the hard problems of scalability, human behavior, and policy-based governance.
Augmented Reality (AR) offers a combination of physical and virtual objects. It differs from virtual reality by allowing users to sight the real world enhanced with virtual objects. In certain applications, security breaches could morph those enhancements into liabilities. For the Science of Security community, research into this subject is relevant to the hard problems of scalability, resilience, privacy, and human behavior.
Automated Response Actions 2021 (all)
A recurring problem in cybersecurity is the need to automate systems to reduce human effort and error and to be able to react rapidly and accurately to an intrusion or insertion. The articles cited here describe a number of interesting approaches related to the Science of Security hard topics, including resilience and composability.
Automated Secure Software Engineering 2021 (all)
Automation of secure software engineering holds promise for reducing coding errors which can be exploited. For the Science of Security community, such processes can be keys to composability and resiliency.
A recurring problem in cybersecurity is the need to automate systems to reduce human effort and error and to be able to react rapidly and accurately to an intrusion or insertion. The articles cited here describe a number of interesting approaches related to the Science of Security hard topics, including resilience and composability.
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.
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.