The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Guide to Intrusion Detection and Prevention Systems (IDPS)
Open accessAbstract
The Information Technology Laboratory (ITL) at the National Institute of Standards and Technology (NIST) promotes the U.S. economy and public welfare by providing technical leadership for the nation's measurement and standards infrastructure.ITL develops tests, test methods, reference data, proof of concept implementations, and technical analysis to advance the development and productive use of information technology.ITL's responsibilities include the development of technical, physical, administrative, and management standards and guidelines for the cost-effective security and privacy of sensitive unclassified information in Federal computer systems.This Special Publication 800-series reports on ITL's research, guidance, and outreach efforts in computer security and its collaborative activities with industry, government, and academic organizations.Certain commercial entities, equipment, or materials may be identified in this document in order to describe an experimental procedure or concept adequately.Such identification is not intended to imply recommendation or endorsement by the National Institute of Standards and Technology, nor is it intended to imply that the entities, materials, or equipment are necessarily the best available for the purpose.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“At the process layer, protection technologies like firewalls, intrusion detection systems, and role-based access controls are required to align with defined policies to provide concrete safeguards [7].”
From Seamless Industry 4.0 Integration: A Multilayered Cyber-Security Framework for Resilient SCADA Deployments in CPPS (2023) · cites this paper as [7]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Part of this paper’s reference list could not be split into single entries.
Use of the Common Vulnerabilities and Exposures (CVE) vulnerability naming scheme
Mell, P., & Grance, T. (2002) · doi:10.6028/nist.sp.800-51 · Cited by 50
Self-citationIngenhoven, C. (2010) · De Gruyter eBooks · doi:10.11129/detail.9783955531713.18 · Cited by 4
Cited by
Sorted by citations
Items 801–900 of 1,000
Automated Analyses of Malicious Code
Krister, K. M. (2009) · Cited by 2
Liparas, D., & Pantraki, E. (2014) · Lecture notes in business information processing · doi:10.1007/978-3-319-07869-4_2 · Cited by 2
Augmenting cost-SVM with gaussian mixture models for imbalanced classification
He, M., Wu, T., Silva, A., Zhao, D.-Y., & Qian, W. (2015) · Artificial Intelligence Research · doi:10.5430/air.v4n2p93 · Cited by 2
Enhancement of forensic capabilities of the linux kernel via file timestamp preservation
Das, S., Kumar, M., & Ghosh, D. (2012) · Journal of Computational Methods in Sciences and Engineering · doi:10.3233/jcm-2012-0438 · Cited by 2
Al-Khanjari, Z. A. S., AL-Anee, A. A., Kraïem, N., & Jamoussi, Y. (2014) · European Scientific Journal ESJ · Cited by 2
Structuration analysis of factors influencing Risk Management System deployment
Odejide, A. A., & Iyamu, T. (2012) · IEEE International Conference on Management of Innovation and Technology (ICMIT) · doi:10.1109/icmit.2012.6225840 · Cited by 2
A Forensic Model for Forecasting Alerts Workload and Patterns of Intrusions
Nehinbe, J. O., & Ige, N. J. (2012) · UKSim International Conference on Computer Modelling and Simulation (UKSim) · doi:10.1109/uksim.2012.122 · Cited by 2
Signature-based IDS using Boolean Weighted Score multiple classifiers
Saelee, P., & Viriyaphol, P. (2012) · doi:10.1109/iccisci.2012.6297119 · Cited by 2
Optimised clustering method for reducing challenges of network forensics
Nehinbe, J. O. (2010) · Computer Science and Electronic Engineering Conference · doi:10.1109/ceec.2010.5606495 · Cited by 2
Concurrent reduction of false positives and redundant alerts
Nehinbe, J. O. (2010) · International Conference on Information Society · doi:10.1109/i-society16502.2010.6018721 · Cited by 2
Emerging threats, risks and mitigation strategies in network forensics
Nehinbe, J. O. (2011) · Conference proceedings - Canadian Conference on Electrical and Computer Engineering · doi:10.1109/ccece.2011.6030658 · Cited by 2
On the Value of Coordination in Distributed Self-Adaptation of Intrusion Detection System
Reh´k, M., Grill, M., & Stiborek, J. (2011) · IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) · doi:10.1109/wi-iat.2011.172 · Cited by 2
Some experimental results about security solutions against DDoS attacks
Petac, E., Alzoubaidi, A. R., & Duma, P. (2013) · International Symposium on Signals, Circuits and Systems · doi:10.1109/isscs.2013.6651193 · Cited by 2
Increasing the Efficiency of IDS Systems by Hardware Implementation of Packet Capturing
Latifi, Z., Jamshidi, K., & Bohlooli, A. (2013) · International Journal of Computer Network and Information Security · doi:10.5815/ijcnis.2013.10.05 · Cited by 2
Pontes, E., & Guelfi, A. E. (2009) · International Conference for Internet Technology and Secured Transactions · doi:10.1109/icitst.2009.5402622 · Cited by 2
A distributed monitoring architecture for AMIs
Shin, I., Huh, J. H., Jeon, Y., & Nicol, D. M. (2013) · doi:10.1145/2516930.2516948 · Cited by 2
A Proposed Model for Datacenter in -Depth Defense to Enhance Continual Security
Mohamed, H. A. R. (2013) · Cited by 2
A Study of Different Intrusion Detection and Prevension System
Mittal, M., Khan, A., & Agrawal, C. (2013) · Cited by 2
Toward Agent Based Inter-VM Traffic Authentication in a Cloud Environment
Benzidane, K., Khoudali, S., & Sekkaki, A. (2014) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-319-11569-6_42 · Cited by 2
Ennahbaoui, M., Idrissi, H., & Hajji, S. E. (2015) · International Conference on Innovations in Information Technology · doi:10.1109/innovations.2015.7381560 · Cited by 2
Development and Validation of the Air Force Cyber Intruder Alert Testbed (CIAT)
Funke, G. J., Dye, G., Borghetti, B. J., Mancuso, V., Greenlee, E. T., Miller, B. T., Menke, L. E., Brown, R. D., & Vieane, A. Z. (2016) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-41932-9_30 · Cited by 2
Pontes, E., Silva, A., Guelfi, A. E., & Kofuji, S. T. (2011) · Cited by 2
Computer network security: Then and now
Witzke, E. L. (2016) · IEEE International Carnahan Conference on Security Technology (ICCST) · doi:10.1109/ccst.2016.7815710 · Cited by 2
A Secure Cloud-Based IDPS Using Cryptographic Traces and Revocation Protocol
Idrissi, H., Ennahbaoui, M., Hajji, S. E., & Souidi, E. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-55589-8_24 · Cited by 2
A Novel Algorithm for Feature Selection Used in Intrusion Detection
Hao, Y., Hou, Y., & Li, L. (2017) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-61542-4_98 · Cited by 2
Intrusion Detection Using End-to-End Memory Network
Long, C., Xiaoxian, G., Zhao, J., Wan, W., Shen, H., & Gao, P. (2017) · International Conference on Communication and Information Systems (ICCIS) · doi:10.1145/3158233.3159367 · Cited by 2
Intrusion Detection System Modeling Based on Learning from Network Traffic Data
Midžić, A., Avdagić, Z., & Omanović, S. (2018) · KSII Transactions on Internet and Information Systems · doi:10.3837/tiis.2018.11.022 · Cited by 2
Blockchain technologies for leveraging security and privacy
Vassilakis, C. (2019) · Homo Virtualis · doi:10.12681/homvir.20188 · Cited by 2
Cybersecurity Considerations for Image Pattern Recognition Applications
Straub, J. (2018) · IEEE Applied Imagery Pattern Recognition Workshop · doi:10.1109/aipr.2018.8707427 · Cited by 2
A survey and taxonomy of techniques used for alerts of Intrusion Detection Systems
Amine, A. M., Khamlichi, Y. I., & Chakir, E. M. (2019) · International Conference on Big Data and Internet of Things (BDIOT) · doi:10.1145/3372938.3372990 · Cited by 2
Defending Critical Infrastructure: Insights from Recommender Systems
Gillard, S. (2020) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-3-030-41826-7_12 · Cited by 2
Current Works on IDS Development Strategies for IoT
Bamou, A., Ouadghiri, D. E., & Aghoutane, B. (2021) · Lecture notes in electrical engineering · doi:10.1007/978-981-33-6893-4_2 · Cited by 2
Rearguard: A Novel Blockchain-based Automatic Worm Containment System
Elsayed, M. (2021) · International Telecommunications Conference (ITC-Egypt) · doi:10.1109/itc-egypt52936.2021.9513932 · Cited by 2
Heuristic-based Intrusion Detection Functionality in a Snort Environment
Gdowski, B., Kościej, R., & Niemiec, M. (2021) · Information & Security An International Journal · doi:10.11610/isij.5010 · Cited by 2
A Review Analysis Investigating the Efficacy of Machine Learning in Intrusion Detection
Alshammari, M., & Mezher, M. A. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-030-93464-4_27 · Cited by 2
Security and Privacy in E-Commerce
(2012) · Advances in e-business research series · doi:10.4018/978-1-4666-1800-8.ch010 · Cited by 2
Http Rule Base Intrusion Detection and Prevention System
(2019) · International Journal of Innovative Technology and Exploring Engineering · doi:10.35940/ijitee.i1093.0789s219 · Cited by 2
Estudo comparativo entre tecnicas de deteccao e prevencao de ataques de injecao SQL
Lages, G. P., & Pereira, R. T. (2022) · doi:10.5753/erbd.2022.223544 · Cited by 2
A Semi-automatic Approach for Enhancing the Quality of Automatically Generated Inventories
Bonomi, S., Cuoci, M., & Lenti, S. (2023) · IEEE International Conference on Cyber Security and Resilience (CSR) · doi:10.1109/csr57506.2023.10225003 · Cited by 2
Hayes, J., Aneiba, A., Gaber, M. M., Islam, M. S., & Abozariba, R. (2023) · IEEE International Conference on Communications workshops · doi:10.1109/iccworkshops57953.2023.10283805 · Cited by 2
Recognition Strategies: Intrusion Detection and Prevention
Ids, W. (2014) · Cited by 2
Cybersecurity Management Through Logging Analytics
Muggler, M., Eshwarappa, R., & Cankaya, E. C. (2017) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-60585-2_1 · Cited by 2
Possibilities of methods for IDS testing
Hulič, M., Baláž, A., & Štancel, M. (2019) · International Conference on Emerging eLearning Technologies and Applications (ICETA) · doi:10.1109/iceta48886.2019.9039986 · Cited by 2
Intrusion Detection in the Internet of Things
Bamou, A. (2020) · International Journal of Advanced Trends in Computer Science and Engineering · doi:10.30534/ijatcse/2020/0191.52020 · Cited by 3
Kim, K., Aminanto, M. E., & Tanuwidjaja, H. C. (2018) · SpringerBriefs on cyber security systems and networks · doi:10.1007/978-981-13-1444-5_2 · Cited by 2
Pattern Matching Algorithms for Intrusion Detection and Prevention Systems
Gupta, V., & Bhalla, V. K. (2014) · Cited by 2
Information Warfare on an Evolving Battlefield
Gold, D. L. (2013) · California State University ScholarWorks (system-wide DSpace) · Cited by 2
Knowledge discovery using diffusion maps
Sipola, T. (2013) · Jyväskylä University Digital Archive (University of Jyväskylä) · Cited by 2
Payload based signature generation for DDoS attacks
Fouda, K. M. I. A. (2017) · Cited by 2
Detection and Evaluation of Data Exfiltration
Bortolameotti, R. (2019) · doi:10.3990/1.9789036548243 · Cited by 2
Intrusion detection using machine learning algorithms
Lakshminarayana, D. H. (2019) · The Scholarship East Carolina University's Institutional Repository (East Carolina University) · Cited by 2
Enhanced Security Requirements for Protecting Controlled Unclassified InformationPreprint
Ross, R. (2020) · doi:10.6028/nist.sp.800-172-draft · Cited by 2
RESILIENT CLOUD COMPUTING AND SERVICES
Fargo, F. (2015) · UA Campus Repository (The University of Arizona) · Cited by 2
Krishnan, N. (2014) · VTechWorks (Virginia Tech) · Cited by 2
Host based attack detection using system calls
Joy, J., & John, A. (2012) · International Conference on Computational Science, Engineering and Information Technology (CCSEIT) · doi:10.1145/2393216.2393218 · Cited by 1
On-Device Detection via Anomalous Environmental Factors
Gautier, A. M., Andel, T. R., & Benton, R. (2018) · doi:10.1145/3289239.3289246 · Cited by 1
An Intruder Monitoring System for Improving the Network Security
Thapliyal, S., Gupta, H., & Khatri, S. K. (2019) · International Conference on Information Systems and Computer Networks (ISCON) · doi:10.1109/iscon47742.2019.9036195 · Cited by 1
Distributed Denial Of Service (DDOS) Attack Detection On Zigbee Protocol Using Naive Bayes Algoritm
Mas’ud, I., Kusrini, K., & Prasetio, A. B. (2021) · International Journal of Artificial Intelligence Research · doi:10.29099/ijair.v5i2.214 · Cited by 1
Detecting the Lateral Movement in Cyberattack at the Early Stage Using Machine Learning Techniques
Chacko, A. A., Edwin, B., & Thanka, M. R. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-2177-3_54 · Cited by 1
Systems Engineering Integration and Test Challenges due to Security Measures in a Cloud‐Based System
Dano, E. B. (2022) · INCOSE International Symposium · doi:10.1002/iis2.12927 · Cited by 1
Storm, J.-M., & Hagen, J. M. (2023) · European Safety and Reliability Conference (ESREL) · doi:10.3850/978-981-18-8071-1_p565-cd · Cited by 1
Chen, H. J., & Cheng, B.-C. (2024) · International Conference on Computer Communication and the Internet (ICCCI) · doi:10.1109/iccci62159.2024.10674430 · Cited by 1
High-Performance Network Intrusion Detection Engine
Vishal, D. (2025) · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT · doi:10.55041/ijsrem40768 · Cited by 1
Intrusion Detection in OT/SCADA Cyber Security and Tabular Generative Adversarial Networks
Biswas, H., Kumar, M. M., & Kumar, P. (2024) · International Conference on Developments in eSystems Engineering (DeSE) · doi:10.1109/dese63988.2024.10911912 · Cited by 1
Improving IDS Performance with XGBoost Hyperparameter Optimization and Real-Time Analysis
Zatika, A., & Coffman, J. (2024) · IEEE/ACM International Conference on Utility and Cloud Computing (UCC) · doi:10.1109/ucc63386.2024.00037 · Cited by 1
AI-Augmented Penetration Testing: A New Frontier in Ethical Hacking
Thapaliya, S., & Dhital, S. (2025) · International Journal of Atharva · doi:10.3126/ija.v3i2.80099 · Cited by 1
Enhancing Insider Threat Detection Using Advanced IDPS
Agrawal, S., Nair, K. G., Chandel, P., Fernandes, L. V., & Sujatha, G. (2025) · International Conference on Recent Advances in Information Technology · doi:10.1109/rait65068.2025.11089143 · Cited by 1
A Lightweight Transformer-PNN Model for Efficient Network Intrusion Detection
Fang, Y., Lu, J., Tian, Y., Wu, X., & Fan, S. (2025) · International Conference on Information Management and Computing Technology (ICIMCT) · doi:10.1109/icimct.2025.00020 · Cited by 1
X-Flow: Explanation-Augmented prompting for LLM-Based Intrusion Detection
Pizarro, I., Ñanculef, R., & Valle, C. (2025) · International Conference on Pattern Recognition Systems (ICPRS) · doi:10.1109/icprs66293.2025.11302848 · Cited by 1
Detection of Malicious Network Traffic with Two-Stage XAI Framework
Ciou, Y.-S., Shieh, C., Horng, M., & Chao, Y.-C. (2026) · Smart innovation, systems and technologies · doi:10.1007/978-3-032-13048-8_18 · Cited by 1
CyberNEMO: Enhancing End-to-End Cybersecurity and Privacy in the IoT-Edge-Cloud Continuum
Zahariadis, T. B., Voulkidis, A. C., Seitanidis, I., Papadakis, A. E., del Río, A., Serrano, J., Jiménez, D., Pastor, A., López, D. R., Muñiz, A., et al. (2025) · IEEE Symposium on Reliable Distributed Systems (SRDS) · doi:10.1109/srds69199.2025.00060 · Cited by 1
Intelligent Network Forensics with Transformer Models and ECDSA-Based Evidence Integrity
Abisha, B., & Kumari, V. S. (2026) · International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE) · doi:10.1109/iitcee67948.2026.11394460 · Cited by 1
A Comprehensive Literature Survey on Hybrid Deep Learning Approaches for Network Intrusion Detection
Patel, V., Patel, P., & Khara, S. V. (2026) · International Conference on AI-Driven Smart Systems and Ubiquitous Computing (ICAUC) · doi:10.1109/icauc68182.2026.11440961 · Cited by 1
Singh, A. K., Singh, A., Agnihotri, A. K., Trivedi, A., & Nadeem, M. (2026) · Recent Progress in Science and Engineering · doi:10.21926/rpse.2603014 · Cited by 2
Implementation of Anomaly Based Network Intrusion Detection by Using Q-learning Technique
Srivastava, R., & Richhariya, V. (2013) · Journals & Books Hosting (International Knowledge Sharing Platform) · Cited by 1
Designing cyber warfare information infrastructure resilience
Daskapan, S., & van den Berg, J. (2011) · Australasian Journal of Paramedicine · doi:10.4225/75/57a83d28befac · Cited by 1
String Kernel Based SVM for Internet Security Implementation
Michlovský, Z., Pang, S., Kasabov, N. K., Ban, T., & Kadobayashi, Y. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-10684-2_59 · Cited by 1
PrISM: Automatic Detection and Prevention from Cyber Attacks
Zeeshan, A., Masood, A. M., Zafar, M. F., Azam, K., & Farzana, N. (2008) · Communications in computer and information science · doi:10.1007/978-3-540-89853-5_46 · Cited by 1
An Approach for Cross-Domain Intrusion Detection
Nguyen, T. D., Gondree, M. A., Khosalim, J., Shifflett, D. J., Levin, T. E., & Irvine, C. (2012) · Cited by 1
A Normal Profile Updating Method for False Positives Reduction in Anomaly Detection Systems
Omar, M. N., & Alsharafi, W. M. (2013) · Cited by 1
Network-based Intrusion Prevention System Prototype with Multi-Detection - A Position Paper
Kavan, D., Škodová, K., & Klíma, M. (2014) · International Conference on Security and Cryptography · doi:10.5220/0005102204170425 · Cited by 1
Anomaly Detection in Beacon-Enabled IEEE 802.15.4 Wireless Sensor Networks
Karapistoli, E., & Economides, A. A. (2013) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-319-04283-1_1 · Cited by 1
Privacy and resource protection in personal network federations
Patrikakis, C. Z., Kyriazanos, D. M., Voulodimos, A. S., & Nikolakopoulos, I. G. (2009) · International Conference on PErvasive Technologies Related to Assistive Environments (PETRA) · doi:10.1145/1579114.1579143 · Cited by 1
Protecting Smart-Grid with Breno-Silva fast single pattern match algorithm for small patterns
Pinto, B. S., & Fung, C. C. (2010) · International Conference on Machine Learning and Cybernetics · doi:10.1109/icmlc.2010.5580716 · Cited by 1
Cloud-centric application tracing and user monitoring intrusion prevention system
Tomášek, M., Čajkovský, M., & Klimek, I. (2013) · IEEE International Conference on Intelligent Engineering Systems (INES) · doi:10.1109/ines.2013.6632838 · Cited by 1
Toward inter-VM visibility in a Cloud environment using packet inspection
Benzidane, K., Khoudali, S., Fetjah, L., & Sekkaki, A. (2013) · doi:10.1109/ictel.2013.6632122 · Cited by 1
Marepalli, S. M., Sultana, R., & Christ, A. (2013) · International Journal of E-Entrepreneurship and Innovation · doi:10.4018/ijeei.2013070103 · Cited by 1
A Graphical User Interface Framework for detecting Intrusions using Bro IDS
Gupta, S., & Goel, R. (2012) · International Journal of Computer Applications · doi:10.5120/8813-2409 · Cited by 1
Detection and Classification of Intrusions using Fusion Probability of HMM
Sukhwani, H., Kodesia, S., & Sharma, S. (2014) · International Journal of Computer Applications · doi:10.5120/18127-9213 · Cited by 1
Matryoshka: Tunneled packets breaking the rules
Ghali, C., Hamady, F., Elhajj, I. H., & Kayssi, A. I. (2011) · International Conference on High Performance Computing & Simulation (HPCS) · doi:10.1109/hpcsim.2011.5999864 · Cited by 1
Probabilistic Belief Revision with Structural Constraints
Jones, P. B., Saligrama, V., & Mitter, S. K. (2010) · Cited by 1
Unlimited access to information systems with mobile devices : information security perspective
Bernik, I., & Markelj, B. (2012) · University of Maribor digital library (University of Maribor) · Cited by 1
Bypassing web-based wireless authentication systems
Hassan, A. I., & Zhang, X. (2011) · IEEE Long Island Systems, Applications and Technology Conference (LISAT) · doi:10.1109/lisat.2011.5784246 · Cited by 1
OPEN SOURCE INTRUSION DETECTION SYSTEM USING SNORT
Kinal, I., & Hajdarevic, K. (2013) · IBU Repository · doi:10.13140/2.1.4576.8962 · Cited by 1
An Efficient Management Model of Security Policy in the Unified Threat Management System
Joo, H.-S., & Kim, J. (2010) · Journal of the Korea Society of Computer and Information · doi:10.9708/jksci.2010.15.9.099 · Cited by 1
Algorithm to Detect Intrusions using Multi Layer Signature Based Model
Uddin, M., Rahman, A. A., Memon, J., & Uddin, N. (2012) · The Journal of applied sciences research · Cited by 1
Experimental Studies of the Statistical Properties of Network Traffic Based on the BDS-Statistics
Смирнов, А. В., & Danilenko, D. (2014) · Cited by 1
Improved Life of Watchdog Nodes in Ad hoc Networks
Anitha, M., & Uthariaraj, V. R. (2014) · International Journal of Security and Its Applications · doi:10.14257/ijsia.2014.8.6.24 · Cited by 1
Richhariya, V., Rana, J. L., ey, & ., R. C. J. (2012) · Cited by 1
Metadata
- Authors
- Scarfone, K. A., & Mell, P. M.
- Affiliations
- National Institute of Standards and Technology (US)
- Published
- 2007
- OpenAlex
- W2678934292
- Cited by
- 1,279
- References
- 2
- Citations by year
- 2026: 81 · 2025: 92 · 2024: 64 · 2023: 56 · 2022: 61 · 2021: 63 · 2020: 70 · 2019: 86 · 2018: 77 · 2017: 78 · 2016: 84 · 2015: 76 · 2014: 82 · 2013: 91 · 2012: 71
- Type
- report
- Language
- en
- Open access
- gold
- doi.org
- Licence
- public-domain
- Funders
- U.S. Department of State
- Cisco Systems
- National Institute of Standards and Technology
- Army Research Laboratory
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Hardware and Architecture › Network Packet Processing and Optimization
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Immune Systems Applications
- Keywords
- intrusion detection systems, intrusion prevention systems, network security, cybersecurity, security testing, security standards
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review