Index
A
- ACNS Conference, How to Find More Information
- address space layout randomization (ASLR), What Is Cybersecurity Science?
- adversarial models, Adversarial Models-Adversarial Models, Provably Secure Cryptography and Security Assumptions
- AES-128 algorithm, A New Experiment
- AlienVault Open Threat Exchange, Scientific Data Collection for Simulators and Sandboxes
- alternative hypothesis, Creating a Hypothesis-Creating a Hypothesis, A New Experiment
- Amazon
- analysis, An Example Scientific Experiment in Software Assurance
- Anscombe's quartet, Visualization
- Apache Hive software, An Example Scientific Experiment in Situational Awareness
- ARMOR algorithm, Game Theory for Malware Analysis
- artifacts, An Example Scientific Experiment in System Security
Engineering
- ASLR (address space layout randomization), What Is Cybersecurity Science?
- Axelsson, Stefan, False Positives and False Negatives
- axioms, defined, Cybersecurity Theory and Practice
- Azure Machine Learning, Machine Learning and Data Mining for Network Monitoring
B
- Bacon, Francis, The Scientific Method
- bad science, Understanding Bad Science, Scientific Claims, and Marketing
Hype, Clarifying Questions for Salespeople, Researchers, and
Developers
- Bagle malware, Building on Previous Work
- base-rate fallacy, False Positives and False Negatives
- A Beautiful Mind
(film), Game Theory for Malware Analysis
- Bell-La Padula confidentiality policy, Security and Testability
- beta testing, Usability Measures: Effectiveness, Efficiency, and
Satisfaction
- biases, human cognitive, Human Cognitive Biases
- big data, situational awareness and, Situational Awareness and Data Analytics
- block ciphers, Cryptographic Security and the Internet of Things
- botnets, Analyzing Your Results, Cybersecurity Experimentation and Test
Environments, Background
- Box, George, Regression Analysis
- BPP (Binary Packet Protocol), Provably Secure Cryptography and Security Assumptions
- brute-force attacks, Experimental Evaluation of Cryptographic Designs and
Implementation
- buffer overflow attacks, What Is Cybersecurity Science?
- Bugcrowd, Scientific Data Collection for Simulators and Sandboxes
C
- CAIDA (Center for Applied Internet Data
Analysis), Open Datasets for Testing
- case studies
- cat-and-mouse games, Game Theory for Malware Analysis, Moving Target Defense
- causation, correlation and, Analyzing Your Results
- CCS Conference, How to Find More Information
- Celsius-Fahrenheit temperature conversion, Regression Analysis
- Center for Applied Internet Data Analysis
(CAIDA), Open Datasets for Testing
- CERT Coordination Center, Intrusion Detection and Incident Response
- CERT Insider Threat Center, Case Study: Defending Against Unintentional Insider Threats
- Chaos Monkey program, Moving Target Defense
- CHI Conference, How to Find More Information
- chi-squared statistic, Analyzing Your Results
- chosen-ciphertext attacks, Experimental Evaluation of Cryptographic Designs and
Implementation
- chosen-plaintext attacks, Experimental Evaluation of Cryptographic Designs and
Implementation
- ciphertext attacks, Experimental Evaluation of Cryptographic Designs and
Implementation
- Cisco Registered Envelope Service (CRES), Case Study: An Interface for User-Friendly Encrypted Email-A New Experiment
- classification, Analyzing Your Results, Machine Learning and Data Mining for Network Monitoring, Machine Learning and Data Mining for Network Monitoring
- cloud computing, Cloud Computing, Machine Learning and Data Mining for Network Monitoring
- CloudLab instrument, Cloud Computing
- clustering (machine learning), Machine Learning and Data Mining for Network Monitoring
- colorize tool, An Example Scientific Experiment in Cybersecurity
Visualization
- Common Criteria, Software Assurance
- common sense, What Is Cybersecurity Science?
- Common Vulnerability Scoring System (CVSS), Case Study: The Risk of Software Exploitability
- Communications of the ACM, Scientific Reproducibility and Repeatability
- composable security, Background-A New Experiment
- Concurrent Probing technique, Testing Usability During Design
- Concurrent Think Aloud technique, Testing Usability During Design
- Conficker malware, Experimental Results to Assist Human Network Defenders
- confirmation bias, Human Cognitive Biases
- controlled experiments, Experimental Evaluation of Security Visualization
- conversion, Fahrenheit-Celsius, Regression Analysis
- Conway, Drew, Experimental Results to Assist Human Network Defenders
- cor command (R), Regression Analysis
- correlation and causation, Analyzing Your Results
- correlation coefficients, Regression Analysis
- CRES (Cisco Registered Envelope Service), Case Study: An Interface for User-Friendly Encrypted Email-A New Experiment
- cross-validation, Regression Analysis
- CRYPTO Conference, How to Find More Information
- cryptography
- CryptoLUX Wiki, Cryptographic Security and the Internet of Things
- CVSS (Common Vulnerability Scoring System), Case Study: The Risk of Software Exploitability
- Cyber Genome project, Building on Previous Work
- CyberSA Conference, How to Find More Information
- cybersecurity
- cybersecurity experimentation, An Example Scientific Experiment in Software Assurance
- (see also scientific experiments)
- about, Cybersecurity Experimentation and Test
Environments-Cybersecurity Experimentation and Test
Environments
- analyzing results, Analyzing Your Results-Analyzing Your Results
- asking good questions, Asking Good Questions and Formulating Hypotheses-Security and Testability
- checklists for, A Checklist for Conducting Experimentation-A Checklist for Conducting Experimentation, A Checklist for Selecting an Experimentation and Test
Environment
- designing fair tests, Designing a Fair Test-Designing a Fair Test
- examples of, What Is Cybersecurity Science?
- formulating hypotheses, Asking Good Questions and Formulating Hypotheses-Security and Testability
- project management for, A Checklist for Conducting Experimentation
- putting results to work, Putting Results to Work
- security and testability, Security and Testability
- test environments for, Open Datasets for Testing-Cybersecurity Testbeds
- cybersecurity science
- Cynomix technology, Building on Previous Work
D
- DARPA
- data loss prevention (DLP) technology, Case Study: Defending Against Unintentional Insider Threats-Case Study: Defending Against Unintentional Insider Threats
- data mining for network monitoring, Machine Learning and Data Mining for Network Monitoring-Machine Learning and Data Mining for Network Monitoring
- datasets, public, Open Datasets for Testing, Machine Learning and Data Mining for Network Monitoring, Scientific Reproducibility and Repeatability
- Daubert standard, Scientific Validity and the Law
- DDoS (distributed denial-of-service), Background
- DECREE, Desktop Testing
- deduction, What Is Cybersecurity Science?
- denial-of-service attacks, Cybersecurity Theory and Practice, False Positives and False Negatives
- Denning, Dorothy, Intrusion Detection and Incident Response
- dependent variables, Creating a Hypothesis, Analyzing Your Results
- Descartes (philosopher), The Scientific Method
- descriptive statistics, Analyzing Your Results
- designing
- desktop testing, Desktop Testing-Desktop Testing
- DFRWS (Digital Forensics Research Workshop), How to Find More Information
- DGAs (domain generation algorithms), Experimental Results to Assist Human Network Defenders
- digital forensics
- Digital Forensics Research Workshop (DFRWS), How to Find More Information
- DigitalCorpora.org website, Scientific Reproducibility and Repeatability
- DIMVA Conference, How to Find More Information
- distributed denial-of-service (DDoS), Background
- DLP (data loss prevention) technology, Case Study: Defending Against Unintentional Insider Threats-Case Study: Defending Against Unintentional Insider Threats
- DNA profiling, Building on Previous Work
- domain generation algorithms (DGAs), Experimental Results to Assist Human Network Defenders
- double-blind experiments, Double-Blind Experimentation
- DSN (Dependable Systems and Networks) Conference, How to Find More Information
- dynamic analysis, An Example Scientific Experiment in Software Assurance, Scientific Data Collection for Simulators and Sandboxes
E
- EAL (evaluation assurance level), Software Assurance
- ecological validity, Cybersecurity Experimentation and Test
Environments
- effectiveness (usability), Usability Measures: Effectiveness, Efficiency, and
Satisfaction, Case Study: Is My Visualization Helping Users Work More
Effectively?-Case Study: Is My Visualization Helping Users Work More
Effectively?
- efficiency (usability), Usability Measures: Effectiveness, Efficiency, and
Satisfaction
- ElGamal crypto algorithm, Experimental Evaluation of Cryptographic Designs and
Implementation
- email encryption, Case Study: An Interface for User-Friendly Encrypted Email-A New Experiment
- emergent properties, Background
- empirical method, The Scientific Method
- EnCase software, Scientific Validity and the Law, Case Study: Is My Visualization Helping Users Work More
Effectively?-Case Study: Is My Visualization Helping Users Work More
Effectively?
- encryption
- Enron Corpus public dataset, Open Datasets for Testing
- evaluation assurance level (EAL), Software Assurance
- experimentation (see cybersecurity experimentation; scientific experiments)
- !exploitable crash
analyzer, Case Study: The Risk of Software Exploitability
- exploratory data analysis, Analyzing Your Results
- external validity, Designing a Fair Test
F
- Fahrenheit-Celsius temperature conversion, Regression Analysis
- fair tests, Designing a Fair Test-Designing a Fair Test
- false negatives, False Positives and False Negatives-False Positives and False Negatives
- false positives, False Positives and False Negatives-False Positives and False Negatives, Scientific Validity and the Law
- falsifiability (scientific method), The Importance of Cybersecurity Science, The Scientific Method
- Farid, Hany, Scientific Validity and the Law
- file-path translator, An Example Scientific Experiment in Digital Forensics
- FireEye provider, Scientific Data Collection for Simulators and Sandboxes, Recognizing and Understanding Scientific Claims
- FlowMonitor module (ns-3), Scientific Data Collection for Simulators and Sandboxes
- forensics, digital (see digital forensics)
- formal methods, Fuzzing for Software Assurance
- Frye standard, Scientific Validity and the Law
- FTK tool, Case Study: Is My Visualization Helping Users Work More
Effectively?
- fuzzing method, An Example Scientific Experiment in Software Assurance, Fuzzing for Software Assurance-Fuzzing for Software Assurance
G
- Galileo utility, A New Experiment
- Gambit software, Game Theory for Malware Analysis
- game theory
- GameSec Conference, How to Find More Information
- Gams software, Game Theory for Malware Analysis
- Gauss, Carl Friedrich, Cryptography
- Gershengorn, Dana, Scientific Validity and the Law
- get-aduser cmdlet, An Example Scientific Experiment in System Security
Engineering
- GitHub repository, Putting Results to Work
- GNU Privacy Guard (GPG), Experimental Evaluation of Cryptographic Designs and
Implementation
- Google
- Gordin, Michael, Pseudoscience
- GPG (GNU Privacy Guard), Experimental Evaluation of Cryptographic Designs and
Implementation
- graphical representations of data, Graphical Representations of Cybersecurity Data-Graphical Representations of Cybersecurity Data, Dangers of Manipulative Graphics and Visualizations-Dangers of Manipulative Graphics and Visualizations
- grep tool, Visualization
- GUARDS algorithm, Game Theory for Malware Analysis
- guessing, untested, What Is Cybersecurity Science?
H
- HackerOne, Scientific Data Collection for Simulators and Sandboxes
- HDFS (Hadoop Distributed File System), An Example Scientific Experiment in Situational Awareness, Case Study: Scientific Comparison of Forensic Tool
Performance
- Heartbleed bug, Case Study: The Risk of Software Exploitability
- hindsight bias, Human Cognitive Biases
- Homeland Security, Department of, Software Assurance, Scientific Data Collection for Simulators and Sandboxes
- Honeynet Project, Scientific Data Collection for Simulators and Sandboxes
- honeypots, Game Theory for Malware Analysis
- hping3 tool, False Positives and False Negatives
- HSR (human subjects research), Open Datasets for Testing
- Huff, Darrell, Recognizing and Understanding Scientific Claims
- human factors
- human subjects research (HSR), Open Datasets for Testing
- hypotheses
I
- IDA Pro disassembler, Malware Analysis
- IDSs (intrusion detection systems)
- incident response (see intrusion detection and incident response)
- independent variables, Creating a Hypothesis, Analyzing Your Results
- inferential statistics, Analyzing Your Results
- information theory, Provably Secure Cryptography and Security Assumptions
- insider threats, unintentional, Case Study: Defending Against Unintentional Insider Threats-Case Study: Defending Against Unintentional Insider Threats
- institutional review board (IRB), A Checklist for Conducting Experimentation
- internal validity, Designing a Fair Test
- International Standards Organization (ISO), Usability Measures: Effectiveness, Efficiency, and
Satisfaction-Usability Measures: Effectiveness, Efficiency, and
Satisfaction
- Internet of Things (IoT), Cryptographic Security and the Internet of Things-Cryptographic Security and the Internet of Things, A New Experiment
- Interset (company), Experimental Results to Assist Human Network Defenders
- intrusion detection and incident response
- about, Intrusion Detection and Incident Response
- false positives and false negatives, False Positives and False Negatives-False Positives and False Negatives
- performance and, Performance, Scalability, and Stress Testing-A New Experiment
- scalability and, Performance, Scalability, and Stress Testing-Performance, Scalability, and Stress Testing
- scientific experiments in, An Example Scientific Experiment in Intrusion Detection-An Example Scientific Experiment in Intrusion Detection, An Example Scientific Experiment in Malware Analysis
- stress testing and, Performance, Scalability, and Stress Testing-Performance, Scalability, and Stress Testing
- intrusion detection systems (see IDSs)
- intuition, What Is Cybersecurity Science?
- IoT (Internet of Things), Cryptographic Security and the Internet of Things-Cryptographic Security and the Internet of Things, A New Experiment
- IRB (institutional review board), A Checklist for Conducting Experimentation
- IRIS algorithm, Game Theory for Malware Analysis
- ISO (International Standards Organization), Usability Measures: Effectiveness, Efficiency, and
Satisfaction-Usability Measures: Effectiveness, Efficiency, and
Satisfaction
- issue-tracking systems, Case Study: The Risk of Software Exploitability
K
- k-means clustering algorithm, Machine Learning and Data Mining for Network Monitoring
- Kaggle website, Machine Learning and Data Mining for Network Monitoring
- Kahneman, Daniel, Human Cognitive Biases
- Kaspersky Labs, Cryptographic Security and the Internet of Things
- Kerckhoffs's principle, Experimental Evaluation of Cryptographic Designs and
Implementation
- key management, A New Experiment, System Security Engineering
- Kibana platform, Graphical Representations of Cybersecurity Data
- knowledge
- known-plaintext attacks, Experimental Evaluation of Cryptographic Designs and
Implementation
L
- lablets, Cybersecurity Theory and Practice
- legal cases, digital evidence and, Scientific Validity and the Law-Scientific Validity and the Law
- LibVMI tool, Scientific Data Collection for Simulators and Sandboxes
- Lightweight Mesh protocol, A New Experiment
- linear regression, Analyzing Your Results, Regression Analysis
- LISA Conference, Case Study: Measuring Snort Detection Performance
- lm command (R), Regression Analysis
- The Logic of
Scientific Discovery (Popper), The Importance of Cybersecurity Science
M
- machine learning, A New Experiment, Machine Learning and Data Mining for Network Monitoring-Machine Learning and Data Mining for Network Monitoring
- Machine Learning for Hackers (Conway), Experimental Results to Assist Human Network Defenders
- MALCON Conference, How to Find More Information
- malware analysis
- about, The Importance of Cybersecurity Science, Malware Analysis
- classification challenge, Machine Learning and Data Mining for Network Monitoring
- game theory for, Game Theory for Malware Analysis-Game Theory for Malware Analysis
- identifying malware families, Case Study: Identifying Malware Families with Science-A New Experiment
- scientific experiments in, An Example Scientific Experiment in Malware Analysis
- scientific method and, The Scientific Method
- simulators and sandboxes for, Scientific Data Collection for Simulators and Sandboxes-Scientific Data Collection for Simulators and Sandboxes
- system security engineering and, An Example Scientific Experiment in System Security
Engineering-An Example Scientific Experiment in System Security
Engineering
- testing scalability, Creating a Hypothesis
- malware images, visualization showing, An Example Scientific Experiment in Cybersecurity
Visualization-An Example Scientific Experiment in Cybersecurity
Visualization
- man-in-the-middle attacks, Experimental Evaluation of Cryptographic Designs and
Implementation, Provably Secure Cryptography and Security Assumptions
- marketing
- A
Mathematical Theory of Cryptography (Shannon), Provably Secure Cryptography and Security Assumptions
- MATLAB software, Regression Analysis
- Maxion, Roy, Situational Awareness and Data Analytics
- McAfee ePolicy Orchestrator, An Example Scientific Experiment in System Security
Engineering
- mean (analytical method), Analyzing Your Results
- measurements (metrics) (see metrics (measurements))
- Mechanical Turk (Amazon), Cybersecurity Testbeds
- median (analytical method), Analyzing Your Results
- metrics (measurements)
- CVSS scores, Case Study: The Risk of Software Exploitability
- false negative rate, False Positives and False Negatives
- false positive rate, False Positives and False Negatives
- for encryption, Experimental Evaluation of Cryptographic Designs and
Implementation
- performance benchmarks, Performance, Scalability, and Stress Testing
- role of, The Role of Metrics
- Snort detection performance, Case Study: Measuring Snort Detection Performance-A New Experiment
- usability, Usability Measures: Effectiveness, Efficiency, and
Satisfaction-Usability Measures: Effectiveness, Efficiency, and
Satisfaction
- Microsoft Research, What Is Cybersecurity Science?, Fuzzing for Software Assurance
- mode (analytical method), Analyzing Your Results
- modeling
- Morris worm, Intrusion Detection and Incident Response
- moving target defense, The Importance of Cybersecurity Science, Game Theory for Malware Analysis, Moving Target Defense
- mutually assured destruction, Game Theory for Malware Analysis
- Mytob malware family, Building on Previous Work
N
- Nagios monitoring program, Case Study: How Quickly Can You Find the Needle in the
Haystack?-A New Experiment
- Nash equilibrium, Game Theory for Malware Analysis
- Nash, John Forbes, Jr., Game Theory for Malware Analysis
- National Science Board, Recognizing and Understanding Scientific Claims
- National Science Foundation, Putting Results to Work
- National Security Agency
- National Vulnerability Database, A New Experiment
- NDSS (symposium), How to Find More Information
- Netflix and Chaos Monkey, Moving Target Defense
- network monitoring
- neural networks, Machine Learning and Data Mining for Network Monitoring-Machine Learning and Data Mining for Network Monitoring
- Nielsen, Jakob, An Example Scientific Experiment in Usable Security
- no free lunch theorems, Machine Learning and Data Mining for Network Monitoring
- Norse attack map, Graphical Representations of Cybersecurity Data
- Novum Organum (Bacon), The Scientific Method
- ns-3 simulator, Scientific Data Collection for Simulators and Sandboxes
- NSS Labs, Vendor Marketing
- NStreamAware system, An Example Scientific Experiment in Situational Awareness
- null hypothesis, Creating a Hypothesis-Creating a Hypothesis, A New Experiment, Case Study: Is My Visualization Helping Users Work More
Effectively?
- NVisAware application, An Example Scientific Experiment in Situational Awareness
P
- p-value, Analyzing Your Results
- PageRank algorithm, The Importance of Cybersecurity Science
- password cracking, Cloud Computing
- penetration testing, An Example Scientific Experiment in Software Assurance
- perfect secrecy notion, Provably Secure Cryptography and Security Assumptions
- performance
- Petroski, Henry, Cybersecurity Theory and Practice
- PGP (Pretty Good Privacy), Case Study: An Interface for User-Friendly Encrypted Email
- pie charts, Graphical Representations of Cybersecurity Data, Dangers of Manipulative Graphics and Visualizations
- Pinoccio Scouts, A New Experiment
- PKI (public key infrastructure), System Security Engineering
- plaintext attacks, Experimental Evaluation of Cryptographic Designs and
Implementation
- PlanetLab testbed, Cloud Computing
- plot command (R), Regression Analysis
- PointToPointHelper class, Scientific Data Collection for Simulators and Sandboxes
- Popper, Karl, The Importance of Cybersecurity Science
- Practical Malware Analysis (Sikorski), Malware Analysis
- PREDICT datasets, Open Datasets for Testing
- predictability (scientific method), The Scientific Method
- Pretty Good Privacy (PGP), Case Study: An Interface for User-Friendly Encrypted Email
- project management, A Checklist for Conducting Experimentation
- PROTECT algorithm, Game Theory for Malware Analysis
- provably secure cryptography, Provably Secure Cryptography and Security Assumptions-Provably Secure Cryptography and Security Assumptions
- pseudoscience, Pseudoscience
- The Pseudoscience Wars
(Gordin), Pseudoscience
- public datasets, Open Datasets for Testing, Machine Learning and Data Mining for Network Monitoring, Scientific Reproducibility and Repeatability
- public key infrastructure (PKI), System Security Engineering
- Pwn2Own contest, Scientific Data Collection for Simulators and Sandboxes
- PyVMI library, Scientific Data Collection for Simulators and Sandboxes
R
- R software, Machine Learning and Data Mining for Network Monitoring, Regression Analysis-Regression Analysis
- RAID Symposium, How to Find More Information
- ranges (testbeds), Cybersecurity Testbeds
- Reamde (Stephenson), An Example Scientific Experiment in Intrusion Detection
- receiver operating characteristic (ROC) curve, False Positives and False Negatives-False Positives and False Negatives
- REcon Conference, How to Find More Information
- Recursive Feature Elimination (RFE), A New Experiment
- regression analysis, Regression Analysis-Regression Analysis
- repeatability, The Scientific Method, Scientific Reproducibility and Repeatability
- reproducibility (scientific method), The Scientific Method, Cloud Computing, Scientific Reproducibility and Repeatability
- results of experimentation
- Retrospective Probing technique, Testing Usability During Design
- Retrospective Think Aloud technique, Testing Usability During Design
- reverse engineering, How to Find More Information
- RFE (Recursive Feature Elimination), A New Experiment
- rigor
- ROC (receiver operating characteristic) curve, False Positives and False Negatives-False Positives and False Negatives
- RSA Conference, Cryptographic Security and the Internet of Things
- RStudio IDE, Machine Learning and Data Mining for Network Monitoring
S
- sample sizes, Designing a Fair Test
- sandboxes, scientific data collection for, Scientific Data Collection for Simulators and Sandboxes-Scientific Data Collection for Simulators and Sandboxes
- Sandia National Laboratories, Adversarial Models
- satisfaction (usability), Usability Measures: Effectiveness, Efficiency, and
Satisfaction
- scalability
- Schneier, Bruce, Cryptography
- Science of Security Virtual Organization (SoS VO), Cybersecurity Theory and Practice
- scientific claims, Understanding Bad Science, Scientific Claims, and Marketing
Hype, Recognizing and Understanding Scientific Claims-Recognizing and Understanding Scientific Claims
- scientific experiments, An Example Scientific Experiment in Software Assurance
- (see also cybersecurity experimentation)
- double-blind, Double-Blind Experimentation
- in cryptography, An Example Scientific Experiment in Cryptography-Experimental Evaluation of Cryptographic Designs and
Implementation
- in digital forensics, An Example Scientific Experiment in Digital Forensics-An Example Scientific Experiment in Digital Forensics
- in intrusion
detection, An Example Scientific Experiment in Intrusion Detection-An Example Scientific Experiment in Intrusion Detection, An Example Scientific Experiment in Malware Analysis
- in malware analysis, An Example Scientific Experiment in Malware Analysis
- in situational
awareness, An Example Scientific Experiment in Situational Awareness-An Example Scientific Experiment in Situational Awareness
- in software
assurance, An Example Scientific Experiment in Software Assurance-An Example Scientific Experiment in Software Assurance
- in system security
engineering, An Example Scientific Experiment in System Security
Engineering-An Example Scientific Experiment in System Security
Engineering
- in usable security, An Example Scientific Experiment in Usable Security-An Example Scientific Experiment in Usable Security
- in visualization, An Example Scientific Experiment in Cybersecurity
Visualization-An Example Scientific Experiment in Cybersecurity
Visualization
- scientific method
- about, The Scientific Method
- cryptography and, Cryptography
- elements of, The Scientific Method, Conducting Your Own Cybersecurity Experiments, Scientific Reproducibility and Repeatability
- Frye standard and, Scientific Validity and the Law
- governing principles, The Scientific Method
- motivations for, The Importance of Cybersecurity Science
- research methods supported, The Scientific Method
- SDLC and, The Scientific Method and the Software Development Life
Cycle
- scientific rigor, The Scientific Method
- SciStarter website, Scientific Data Collection for Simulators and Sandboxes
- Scott, David Meerman, Vendor Marketing
- SDDR protocol, An Example Scientific Experiment in Cryptography-An Example Scientific Experiment in Cryptography
- SDLC (software development life cycle), The Scientific Method and the Software Development Life
Cycle
- Security Architect job description, Cryptographic Security and the Internet of Things
- security resource allocation, game theory for, Game Theory for Malware Analysis
- SecurityMetrics.org website, The Role of Metrics
- Sen, Souyma, Building on Previous Work
- Shannon, Claude, Provably Secure Cryptography and Security Assumptions
- Shneiderman, Ben, Usability Measures: Effectiveness, Efficiency, and
Satisfaction, Graphical Representations of Cybersecurity Data
- Sikorski, Michael, Malware Analysis
- Simon block ciphers, Cryptographic Security and the Internet of Things
- simulation
- Siri speech recognition, Machine Learning and Data Mining for Network Monitoring
- situational awareness
- SLAM project, Fuzzing for Software Assurance
- The Sleuth Kit for
Hadoop, Case Study: Scientific Comparison of Forensic Tool
Performance
- Snort intrusion detection package, Case Study: Measuring Snort Detection Performance-A New Experiment
- software assurance
- software development life cycle (SDLC), The Scientific Method and the Software Development Life
Cycle
- SoS VO (Science of Security Virtual Organization), Cybersecurity Theory and Practice
- SOUPS (symposium), How to Find More Information
- SourceForge repository, Putting Results to Work
- Speck block ciphers, Cryptographic Security and the Internet of Things
- speech recognition, Machine Learning and Data Mining for Network Monitoring
- Splunk package, Graphical Representations of Cybersecurity Data
- Spurious Correlations (Vigen), Recognizing and Understanding Scientific Claims
- SSH protocol, Provably Secure Cryptography and Security Assumptions
- Stackelberg games, Game Theory for Malware Analysis, Game Theory for Malware Analysis
- static analysis, An Example Scientific Experiment in Software Assurance, Scientific Data Collection for Simulators and Sandboxes
- statistical power, Designing a Fair Test
- statistics (overview), Analyzing Your Results-Analyzing Your Results
- Stephenson, Neal, An Example Scientific Experiment in Intrusion Detection
- stress testing, Performance, Scalability, and Stress Testing-Performance, Scalability, and Stress Testing
- summative testing, Testing Usability During Validation and Verification
- supervised learning, Machine Learning and Data Mining for Network Monitoring
- surveys, Usability Measures: Effectiveness, Efficiency, and
Satisfaction-Usability Measures: Effectiveness, Efficiency, and
Satisfaction, Experimental Evaluation of Security Visualization-Experimental Evaluation of Security Visualization, Recognizing and Understanding Scientific Claims
- Symantic provider, Scientific Data Collection for Simulators and Sandboxes
- Synack, Scientific Data Collection for Simulators and Sandboxes
- sysstat tools, Performance, Scalability, and Stress Testing
- system security engineering
T
- temperature conversion, Regression Analysis
- test environments
- testbeds (ranges), Cybersecurity Testbeds
- testing considerations
- designing fair tests, Designing a Fair Test-Designing a Fair Test
- for intrusion
detection, Performance, Scalability, and Stress Testing-Performance, Scalability, and Stress Testing
- testability of security, Security and Testability
- testing scalability, Creating a Hypothesis
- testing usability, Usability Measures: Effectiveness, Efficiency, and
Satisfaction-Testing Usability During Validation and Verification
- Thinking Fast and Slow (Kahneman), Human Cognitive Biases
- TLS (Transport Layer Security) protocol, Provably Secure Cryptography and Security Assumptions, Background
- translation methods, An Example Scientific Experiment in Digital Forensics
- Transport Layer Security (TLS) protocol, Provably Secure Cryptography and Security Assumptions, Background
- Trusted Computer System Evaluation Criteria, Software Assurance, System Security Engineering
- TRUSTS algorithm, Game Theory for Malware Analysis
- Tufte, Edward, Graphical Representations of Cybersecurity Data
- Tukey, John, Analyzing Your Results
- Twitter social media site, Machine Learning and Data Mining for Network Monitoring
U
- UC Irvine Machine Learning Repository, Machine Learning and Data Mining for Network Monitoring
- United States of America v. Rudy Frabizio, Scientific Validity and the Law
- universal composability, Background
- unsupervised learning, Machine Learning and Data Mining for Network Monitoring
- untested guessing, What Is Cybersecurity Science?
- usability
- about, Human-Computer Interaction and Usable
Security
- double-blind experiments and, Double-Blind Experimentation
- five myths of, An Example Scientific Experiment in Usable Security
- measurement characteristics, Usability Measures: Effectiveness, Efficiency, and
Satisfaction-Usability Measures: Effectiveness, Efficiency, and
Satisfaction
- methods for gathering data, Methods for Gathering Usability Data-Testing Usability During Validation and Verification
- scientific experiments in security, An Example Scientific Experiment in Usable Security-An Example Scientific Experiment in Usable Security
- testing, Usability Measures: Effectiveness, Efficiency, and
Satisfaction-Testing Usability During Validation and Verification
- user-friendly encrypted email interface, Case Study: An Interface for User-Friendly Encrypted Email-A New Experiment
- Usability Engineering (Nielsen), An Example Scientific Experiment in Usable Security
- USEC Workshop, How to Find More Information
- USENIX Security Symposium, How to Find More Information
- user studies, Experimental Evaluation of Security Visualization
- UX Myths website, An Example Scientific Experiment in Usable Security
V
- validation
- validity
- variables
- VAST Challenge, An Example Scientific Experiment in Situational Awareness
- VAST Conference, How to Find More Information
- vendor marketing, Understanding Bad Science, Scientific Claims, and Marketing
Hype, Vendor Marketing-Clarifying Questions for Salespeople, Researchers, and
Developers
- verifiability (scientific method), The Scientific Method
- verification, testing usability during, Testing Usability During Validation and Verification
- Verizon Data Breach Investigations Report, Human Factors, Situational Awareness and Data Analytics
- Vigen, Tyler, Recognizing and Understanding Scientific Claims
- Vincenti, Walter, What Is Cybersecurity Science?
- virtual machine introspection (VMI), Scientific Data Collection for Simulators and Sandboxes
- virtualization, desktop solutions, Desktop Testing
- VIS Conference, How to Find More Information
- Visual Analytics Benchmark Repository, How to Find More Information
- visualization
- VizSec Workshop, How to Find More Information
- VMI (virtual machine introspection), Scientific Data Collection for Simulators and Sandboxes
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