Pub Crawl #59
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.
Malware Analysis and Graph Theory 2021 (all)
Malware analysis, along with detection and classification, is a major issue cybersecurity. For the Science of Security community, malware classification is related to privacy, predictive metrics, human behavior and resiliency.
MANET Attack Prevention 2021 (all)
Security is an important research issue for mobile ad hoc networks (MANETs). The work cited here looks at attack prevention. For the Science of Security community, this work relates to the hard problems of resilience, metrics, and compositionality.
Measurement and Metrics Testing 2021 (all)
Measurement and metrics are hard problems in the Science of Security. The research cited here looks at methods and techniques for testing the validity of measurement and metrics techniques.
Metadata Discovery Problem 2021 (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.
Middleware Security 2021 (all)
Middleware facilitates distributed processing and is of significant interest to the security world with the development of cloud and mobile applications. It is important to the Science of Security community relative to resilience, policy-based governance and composability.
Moving Target Defense 2021 (all)
Moving Target Defense (MTD) research focuses on the presentation of a dynamic attack surface to an adversary, increasing the work factor necessary to successfully attack and exploit a cyber target. For the Science of Security community, MTD is related to scalability, resilience and predictive metrics.
Multicore Computing 2021 (all)
As high-performance computing has evolved into larger and faster computing solutions, new approaches to security have been identified. The articles cited here focus on security issues related to multicore environments. Multicore computing relates to the Science of Security hard topics of scalability, resilience, and metrics.
Multifactor Authentication 2021 (all)
Multifactor authentication is of general interest within cryptography. For the Science of Security community, it relates to human factors, resilience, and metrics.
Multiple Fault Diagnosis 2021 (all)
According to Shakeri, “the computational complexity of solving the optimal multiple-fault isolation problem is super exponential.” Most processes and procedures assume that there will be only one fault at any given time. Many algorithms are designed to do sequential diagnostics. With the growth of cloud computing and multicore processors and the ubiquity of sensors, the problem of multiple fault diagnosis has grown even larger. For the Science if Security community, multiple fault diagnosis is relevant to cyber physical systems, resiliency, metrics, and human factors.
Named Data Networking 2021 (all)
Named Data Networking (NDN) is one of five research projects funded by the U.S. National Science Foundation under its Future Internet Architecture Program. Its goal is to make it easier to develop, manage, secure, and use networks and the Internet. For the Science of Security community, these efforts are relevant to the hard problems of resilience, human behavior, and scalability.
Natural Language Processing 2021 (all)
Natural language processing research focuses on developing efficient algorithms to process texts and to make their information accessible to computer applications. Texts can contain information with different complexities ranging from simple word or token-based representations to rich hierarchical syntactic representations, to high-level logical representations across document collections. For the Science of Security community, this work is relevant to scalability, resilience, and human behavior.
Nearest Neighbor Search 2021 (all)
The search for secure privacy protecting nearest neighbor searches is an issue in cybersecurity related to the Science of Security community hard problems of measurement and predictive metrics.
Network Accountability 2021 (all)
The term “accountability’ suggests that an entity should be held responsible for its own specific actions. Once an event has transpired, the events that took place need to be traceable so that the causes can be determined afterwards. The goal of network accountability research is to provide accountability within networks and computers by building trace files of events. For the Science of Security community, it is relevant to composability, resilience, and metrics.
Network coding methods are used to improve a network's throughput, efficiency and scalability. It can also be a method for dealing with attacks and eavesdropping. For the Science of Security community, research into network coding is relevant to the general network problems associated with the hard problems of resiliency, composability, and predictive metrics, as well as cyber physical systems.
Networked Control Systems Security 2021 (all)
Network control systems (NCS) offer a relatively inexpensive way for communications networks to provide diagnostics, flexibility, and robustness. To the Science of Security community, NCS research is relevant to the hard problems of resiliency, composability, and predictive metrics.
Network Intrusion Detection 2021 (all)
Network intrusion detection is one of the chronic problems in cybersecurity. The growth of cellular and ad hoc networks has increased the threat and risks and research into this area of concern reflects its importance. For the Science of Security community, NID is relevant to metrics, composability, and resilience.
Network on Chip Security 2021 (all)
Network on chip (NoC or NOC) is a communication subsystem on an integrated circuit. NOC technology applies networking theory and methods to on-chip communication and brings improvements over conventional interconnections. From a Science of Security perspective, NOC security is relevant to scalability, resilience, and metrics.
Network Reconnaissance 2021 (all)
The capacity to survey, analyze and assess a network is a critical aspect of developing resilient systems. The work cited here addresses multiple methods and approaches to network reconnaissance. These are related to the Science of Security hard problems of resilience and scalability.
The requirement for security and resilience in networks is one of the hard problems in the Science of Security.
Neural Network Security 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.
Neural Style Transfer 2021 (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.
Peer to Peer Security 2021 (all)
Peer-to-peer systems pose considerable challenges for computer security. Like other forms of software, P2P applications can contain vulnerabilities, but what makes security particularly dangerous for P2P software is that peer-to-peer applications act as servers as well as clients, making them more vulnerable to remote exploits. For the Science of Security community, this work is relevant to the hard problems of scalability, resilience, metrics, and human factors.
Predictive Security Metrics 2021 (all)
Measurement is at the core of science. The development of accurate metrics is a major element for achieving a true Science of Security. It is also one of the hard problems to solve.
The technical implementation of privacy problems is fraught with challenges. For the Science of Security community, this research is relevant to the hard problems of scalability and to human behavior.
Privacy Policies and Measurement 2021 (all)
Measuring the impact and technical implementation of privacy problems is fraught with challenges. For the Science of Security community, this research is relevant to the hard problems of metrics, scalability and to human behavior.
Protocol Verification 2021 (all)
Verifying the accuracy of security protocols is a primary goal of cybersecurity. Research into the area has sought to identify new and better algorithms and to identify better methods for verifying security protocols in myriad applications and environments. Verification has implications for compositionality and composability and for policy–based collaboration, as well as for privacy alone.
The term “provable security” refers to those security methods which can be confirmed mathematically through a formal process. For the Science of Security community, these methods are important to solving the problems of resiliency, predictive metrics, and compositionality.
Provenance refers to information about the origin and activities of system data and processes. With the growth of shared services and systems, including social media, cloud computing, and service-oriented architectures, finding tamperproof methods for tracking files is a major challenge. Provenance is important to the Science of Security relative to human behavior, metrics, resilience, and composability.
Memory corruption attacks account for many security breaches afflicting software systems. Return-oriented programming (ROP) techniques are often used to bypass the most common memory protection systems. For the Science of Security community, this research is related to resilience, scalability, composability and human factors.
Router Systems Security 2021 (all)
Routers are among the most ubiquitous electronic devices in use. Basic security from protocols and encryption can be readily achieved, but routing has many leaks. For the Science of Security community, they are related to the hard problems of resiliency and predictive metrics.
Coding standards encourage programmers to follow a set of uniform rules and guidelines determined by the requirements of the project and organization, rather than by the programmer's personal familiarity or preference. Developers and software designers apply these coding standards during software development to create secure systems. The development of secure coding standards is a work in progress by security researchers, language experts, and software developers. The articles cited here cover topics related to the Science of Security hard problems of resilience, metrics, human factors, and policy-based governance.
Sandboxing is an important tool for the Science of Security, particularly with regard to developing composable systems and policy-governed systems. To many researchers, it is a promising method for preventing and containing damage. Sandboxing, frequently used to test unverified programs that may contain malware, allows the software to run without harming the host device.
SCADA Systems Security 2021 (all)
SCADA system security issues have been identified as a problem for more than a decade. The work cited here addresses the issue relevant to the Science of Security hard problems of resiliency, compositionality, and human behavior.
Scalability is one of the hard problems in the Science of Security. Applied to larger data sets, increases in interoperability, and greater computing capacity, particularly in critical infrastructures and the Internet of Things, the development of effective automated scalable systems is compounded.
Scalable Verification 2021 (all)
Verification of software and its security features can be done statically or dynamically. A challenge is to conduct verifications at scale to determine whether all the features do what they are intended to do. For the Science of Security community, scalable verification relates to scalability and compositionality, resilience, and predictive metrics.
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.
Smart Grid Security 2021 (all)
The primary value of published research in smart grid technologies--the use of cyber-physical systems to coordinate the generation, transmission, and use of electrical power and its sources-- is because of its strategic importance and the consequences of intrusion. Smart grid is of particular importance to the Science of Security and its problems embrace several of the hard problems, notably resiliency, scalability, and metrics.
Sensors represent are both a point of vulnerability in the Smart Grid and a means of detection of intrusions. For the Science of Security community, research work into these industrial control systems is relevant to resiliency, compositionality, and human factors.
Agent-based modeling of human social behavior is an increasingly important research area. Efficient, scalable and robust social systems are difficult to engineer, both from the modeling perspective and the implementation perspective. The work cited here addresses these problems. It is relevant to the Science of Security community relative to human factors and scalability.
Support Vector Machines 2021 (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.
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.
System recovery following an attack is a core cybersecurity issue. Current research into methods to undo data manipulation and to recover lost or extruded data in distributed, cloud-based or other large scale complex systems is discovering new approaches and methods. For the Science of Security community, it is an essential element of resiliency.
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.
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.