Guide to Intrusion Detection and Prevention Systems (IDPS)

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

Design and Implementation

Ingenhoven, C. (2010) · De Gruyter eBooks · doi:10.11129/detail.9783955531713.18 · Cited by 4

Managing Information System Security Under Continuous and Abrupt Deterioration

Bensoussan, A., Mookerjee, V. S., & Yue, W. T. (2020) · Production and Operations Management · doi:10.1111/poms.13198 · Cited by 19

Towards Designing Packet Filter with a Trust-Based Approach Using Bayesian Inference in Network Intrusion Detection

Meng, Y., Kwok, L. F., & Li, W. (2013) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-642-36883-7_13 · Cited by 19

Analytics for Network Security: A Survey and Taxonomy

Grahn, K. J., Westerlund, M., & Pulkkis, G. (2016) · Studies in computational intelligence · doi:10.1007/978-3-319-44257-0_8 · Cited by 19

A Survey of Intrusion Detection Systems Leveraging Host DataPreprint

Glass-Vanderlan, T. R., Iannacone, M. D., Vincent, M. S., Qian, Q., Chen, & Bridges, R. A. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.06070 · Cited by 19

A Systematic Review of the Intrusion Detection Techniques in VANETS

Naqvi, I., Chaudhary, A., & Kumar, A. (2022) · TEM Journal · doi:10.18421/tem112-51 · Cited by 18

An Enhanced Network Security using Machine Learning and Behavioral Analysis

Haricharan, M. G., Govind, S. P., & Kumar, C. N. S. V. (2023) · International Conference for Advancement in Technology (ICONAT) · doi:10.1109/iconat57137.2023.10080157 · Cited by 18

Improving Network Intrusion Detection by Means of Domain-Aware Genetic Programming

Blasco, J., Orfila, A., & Ribagorda, A. (2010) · International Conference on Availability, Reliability and Security (ARES) · doi:10.1109/ares.2010.53 · Cited by 18

Adaptive framework for network traffic classification using dimensionality reduction and clustering

Juvonen, A., & Sipola, T. (2012) · International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT) · doi:10.1109/icumt.2012.6459678 · Cited by 17

On some artificial intelligence methods and technologies for cloud-computing protection

Grusho, A. A., Zabezhailo, M. I., Зацаринный, А. А., & Piskovskii, V. O. (2017) · Automatic Documentation and Mathematical Linguistics · doi:10.3103/s0005105517020029 · Cited by 18

Anomaly-Based Network Intrusion Detection Model Using Deep Learning in Airports

Sezari, B., Möller, D. P. F., & Deutschmann, A. (2018) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom/bigdatase.2018.00261 · Cited by 18

“Network Sentiment” Framework to Improve Security and Privacy for Smart Home

Pecorella, T., Pierucci, L., & Nizzi, F. (2018) · Future Internet · doi:10.3390/fi10120125 · Cited by 19

A Framework of Blockchain-Based Collaborative Intrusion Detection in Software Defined Networking

Li, W., Tan, J., & Wang, Y. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-65745-1_15 · Cited by 19

The Organizational Cybersecurity Success Factors: An Exhaustive Literature Review

Poehlmann, N. M., Caramancion, K. M., Tatar, I., Li, Y., Barati, M., & Merz, T. R. (2021) · Transactions on computational science and computational intelligence · doi:10.1007/978-3-030-71017-0_27 · Cited by 18

Intrusion Detection Using Disagreement-Based Semi-supervised Learning: Detection Enhancement and False Alarm Reduction

Meng, Y., & Kwok, L. F. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-35362-8_36 · Cited by 18

Policy-Based Security Configuration Management, Application to Intrusion Detection and Prevention

Alsubhi, K., Aib, I., François, J., & Boutaba, R. (2009) · International Conference on Communications · doi:10.1109/icc.2009.5199341 · Cited by 18

Detection of Smartphone Malware

Schmidt, A.-D. (2011) · doi:10.14279/depositonce-2885 · Cited by 18

Smart IDS and IPS for Cyber-Physical Systems

Mahboub, S. A., Ali, E. S., & Saeed, R. A. (2020) · Advances in systems analysis, software engineering, and high performance computing book series · doi:10.4018/978-1-7998-5101-1.ch006 · Cited by 17

Comparative Evaluation of Machine Learning Algorithms for Network Intrusion Detection and Attack Classification

León, M., Markovic, T., & Punnekkat, S. (2022) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn55064.2022.9892293 · Cited by 17

Cybersecurity in Aviation: Exploring the Significance, Applications, and Challenges of Cybersecurity in the Aviation Sector

Eleimat, M., & Őszi, A. (2025) · Periodica Polytechnica Transportation Engineering · doi:10.3311/pptr.37153 · Cited by 17

Fitness Function for Genetic Algorithm used in Intrusion Detection System

Alabsi, F., & Naoum, R. S. (2012) · Cited by 17

A Privacy-Preserving Framework for Collaborative Intrusion Detection Networks Through Fog Computing

Wang, Y., Xie, L., Li, W., Meng, W., & Li, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-69471-9_20 · Cited by 17

Multi-tenant intrusion detection system for public cloud (MTIDS)

Hawedi, M., Talhi, C., & Boucheneb, H. (2018) · The Journal of Supercomputing · doi:10.1007/s11227-018-2572-6 · Cited by 17

A fog‐based collaborative intrusion detection framework for smart grid

Li, W., Au, M. H., & Wang, Y. (2020) · International Journal of Network Management · doi:10.1002/nem.2107 · Cited by 17

Intrusion Detection System based on Hybrid Classifier and User Profile Enhancement Techniques

Pokharel, P., Pokhrel, R., & Sigdel, S. (2020) · International Workshop on Big Data and Information Security (IWBIS) · doi:10.1109/iwbis50925.2020.9255578 · Cited by 17

CAMNEP: An intrusion detection system for highspeed networks

Řehák, M., Pěchouček, M., Bartoš, K., Grill, M., Čeleda, P., & Krmíček, V. (2008) · Progress in Informatics · doi:10.2201/niipi.2008.5.7 · Cited by 17

A new adaptive intrusion detection system based on the intersection of two different classifiers

Ahmim, A., & Zine, N. G. (2014) · International Journal of Security and Networks · doi:10.1504/ijsn.2014.065710 · Cited by 17

A DDoS-Aware IDS Model Based on Danger Theory and Mobile Agents

Zamani, M., Movahedi, M., Ebadzadeh, M. M., & Pedram, H. (2009) · International Conference on Computational Intelligence and Security (CIS) · doi:10.1109/cis.2009.215 · Cited by 17

Engineering Intrusion Prevention Services for IaaS Clouds: The Way of the Hypervisor

Laniepce, S., Lacoste, M., Kassi-Lahlou, M., Bignon, F., Lazri, K., & Wailly, A. (2013) · IEEE International Symposium on Service-Oriented System Engineering (SOSE) · doi:10.1109/sose.2013.27 · Cited by 17

A Survey on Intrusion Detection and Prevention Systems

Ghafir, I., Husák, M., & Přenosil, V. (2014) · Cited by 17

Intrusion Detection and Prevention

Möller, D. P. F. (2023) · Advances in information security · doi:10.1007/978-3-031-26845-8_3 · Cited by 18

Network Intrusion Detection and Prevention System Using Hybrid Machine Learning with Supervised Ensemble Stacking Model

Mills, G. A., Acquah, D. K., & Sowah, R. A. (2024) · Journal of Computer Networks and Communications · doi:10.1155/2024/5775671 · Cited by 26

Makine Öğrenmesi Teknikleriyle Saldırı Tespiti: Karşılaştırmalı Analiz

Kaya, Ç., & Yıldız, O. (2014) · International Journal of Advances in Engineering and Pure Sciences · doi:10.7240/mufbed.24684 · Cited by 16

Accountability and Q-Accountable Logging in Wireless Networks

Fu, B., & Xiao, Y. (2014) · Wireless Personal Communications · doi:10.1007/s11277-014-1604-7 · Cited by 16

Effective Intrusion Detection System using Data Mining Technique

Patel, J., & Panchal, K. (2015) · Journal of Emerging Technologies and Innovative Research · Cited by 16

Securing Mobile Ad Hoc Networks

Kumar, S., & Dutta, K. (2016) · International Journal of Handheld Computing Research · doi:10.4018/ijhcr.2016010103 · Cited by 16

Enhancing WPA2-PSK four-way handshaking after re-authentication to deal with de-authentication followed by brute-force attack a novel re-authentication protocol

Ghanem, M. C., & Ratnayake, D. (2016) · International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA) · doi:10.1109/cybersa.2016.7503286 · Cited by 16

A review of scientific research in defensive cyberspace operation tools and technologies

Goethals, P., & Hunt, M. E. (2019) · Journal of Cyber Security Technology · doi:10.1080/23742917.2019.1601889 · Cited by 14

Soft-computing-based false alarm reduction for hierarchical data of intrusion detection system

Singh, P., Krishnamoorthy, S., Nayyar, A., Luhach, A. K., & Kaur, A. (2019) · International Journal of Distributed Sensor Networks · doi:10.1177/1550147719883132 · Cited by 17

SDN based Intrusion Detection and Prevention Systems using Manufacturer Usage Description: A Survey

Mazhar, N., Salleh, R., Asif, M., & Zeeshan, M. (2020) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2020.0111283 · Cited by 16

FCNN: An Efficient Intrusion Detection Method Based on Raw Network Traffic

Wang, Y., Jiang, Y., & Lan, J. (2021) · Security and Communication Networks · doi:10.1155/2021/5533269 · Cited by 16

Securing Cloud Computing from Different Attacks Using Intrusion Detection Systems

Achbarou, O., Kiram, M. A. E., & Elbouanani, S. (2016) · International Journal of Interactive Multimedia and Artificial Intelligence · doi:10.9781/ijimai.2017.439 · Cited by 16

A network-based intrusion detection and prevention system with multi-mode counteractions

Yousufi, R. M., Lalwani, P., & Potdar, M. B. (2017) · International Conference on Innovations in Information, Embedded and Communication Systems · doi:10.1109/iciiecs.2017.8276023 · Cited by 16

AECID: A Self-learning Anomaly Detection Approach based on Light-weight Log Parser Models

Wurzenberger, M., Skopik, F., Settanni, G., & Fiedler, R. (2018) · International Conference on Information Systems Security and Privacy (ICISSP) · doi:10.5220/0006643003860397 · Cited by 16

Practical Bayesian Poisoning Attacks on Challenge-Based Collaborative Intrusion Detection Networks

Meng, W., Li, W., Jiang, L., Choo, K. R., & Su, C. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-29959-0_24 · Cited by 16

New Anomaly Network Intrusion Detection System in Cloud Environment Based on Optimized Back Propagation Neural Network Using Improved Genetic Algorithm

Chiba, Z. (2022) · International Journal of Communication Networks and Information Security (IJCNIS) · doi:10.17762/ijcnis.v11i1.3764 · Cited by 16

Process matters: cyber security in industrial control systems

Hadžiosmanović, D. (2013) · doi:10.3990/1.9789036536042 · Cited by 16

An immune inspired unsupervised intrusion detection system for detection of novel attacks

Jha, M., & Acharya, R. S. (2016) · IEEE International Conference on Intelligence and Security Informatics (ISI) · doi:10.1109/isi.2016.7745493 · Cited by 15

Intrusion Detection of the ICS Protocol EtherCAT

GRANAT, A., Höfken, H., & Schuba, M. (2017) · DEStech Transactions on Computer Science and Engineering · doi:10.12783/dtcse/cnsce2017/8885 · Cited by 15

Setting the threshold for high throughput detectors: A mathematical approach for ensembles of dynamic, heterogeneous, probabilistic anomaly detectors

Bridges, R. A., Jamieson, J. D., & Reed, J. W. (2017) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2017.8258031 · Cited by 15

HFFPNN classifier: a hybrid approach for intrusion detection based OPSO and hybridization of feed forward neural network (FFNN) and probabilistic neural network (PNN)

Kala, T. S., & Christy, A. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09804-7 · Cited by 15

Generating Labeled Training Datasets Towards Unified Network Intrusion Detection Systems

Ishibashi, R., Miyamoto, K., Han, C., Ban, T., Takahashi, T., & Takeuchi, J. (2022) · IEEE Access · doi:10.1109/access.2022.3176098 · Cited by 15

Signature Based Detection of User Events for Post-mortem Forensic Analysis

James, J. I., Gladyshev, P., & Zhu, Y. (2011) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-642-19513-6_8 · Cited by 15

A cost-aware model for risk mitigation in Cloud computing systems

Kholidy, H. A., & Erradi, A. (2015) · IEEE/ACS International Conference on Computer Systems and Applications (AICCSA) · doi:10.1109/aiccsa.2015.7507111 · Cited by 15

Improving Intrusion Detection Systems using Zero-Shot Recognition via Graph Embeddings

Zerhoudi, S., Granitzer, M., & Garchery, M. (2020) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac48688.2020.0-165 · Cited by 15

Intrusion Detection and Prevention System (IDPS) Technology- Network Behavior Analysis System (NBAS)

Tiwari, N., Singh, S. R., & Singh, P. G. (2012) · Cited by 15

MLIDS22- IDS Design by Applying Hybrid CNN-LSTM model on Mixed-Datasets

Abdulmajeed, I. A., & Husien, I. M. (2022) · Informatica · doi:10.31449/inf.v46i8.4348 · Cited by 14

Automated WiFi Incident Detection Attack Tool on 802.11 Networks

Koutras, D., Dimitrellos, P., Kotzanikolaou, P., & Douligeris, C. (2023) · IEEE Symposium on Computers and Communications (ISCC) · doi:10.1109/iscc58397.2023.10218077 · Cited by 14

Is Trust Misplaced? A Zero-Trust Survey

Poirrier, A., Cailleux, L., & Clausen, T. (2025) · Proceedings of the IEEE · doi:10.1109/jproc.2025.3555131 · Cited by 21

A distributed multi-approach intrusion detection system for web services

Najjar, M. S. A., & Azgomi, M. A. (2010) · International Conference on Security of Information and Networks (SIN) · doi:10.1145/1854099.1854147 · Cited by 14

An Overview of the State-of-the-Art of Cloud Computing Cyber-Security

Bennasar, H., Bendahmane, A., & Essaaidi, M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-55589-8_4 · Cited by 14

Network anomaly detection based on probabilistic analysis

Park, J., Choi, D. H., Jeon, Y.-B., Nam, Y., Hong, M., & Park, D.-S. (2017) · Soft Computing · doi:10.1007/s00500-017-2679-3 · Cited by 14

Surveillance and security: protecting electricity utilities and other critical infrastructures

Gouglidis, A., Green, B., Hutchison, D., Alshawish, A., & de Meer, H. (2018) · Energy Informatics · doi:10.1186/s42162-018-0019-1 · Cited by 14

GAN based Augmentation for Improving Anomaly Detection Accuracy in Host-based Intrusion Detection Systems

Kim, K. (2020) · International Journal of Engineering Research and Technology · doi:10.37624/ijert/13.11.2020.3987-3996 · Cited by 15

Multivariable Heuristic Approach to Intrusion Detection in Network Environments

Niemiec, M., Kościej, R., & Gdowski, B. (2021) · Entropy · doi:10.3390/e23060776 · Cited by 14

Automotive Cybersecurity

Möller, D. P. F., & Haas, R. E. (2019) · Computer communications and networks · doi:10.1007/978-3-319-73512-2_6 · Cited by 14

An Evaluation Framework for Machine Learning Methods in Detection of DoS and DDoS Intrusion

Zewdie, T. G., & Girma, A. (2022) · International Conference on Artificial Intelligence in Information and Communication (ICAIIC) · doi:10.1109/icaiic54071.2022.9722661 · Cited by 14

Statistical and Signature Analysis Methods of Intrusion Detection

Радівілова, Т., Kirichenko, L., Alghawli, A. S., Ageyev, D., Мулеса, О. Ю., Baranovskyi, O., Ilkov, A., Kulbachnyi, V., & Bondarenko, O. (2022) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-3-030-95161-0_5 · Cited by 14

Enabling intrusion detection systems with dueling double deep Q-learning

Badr, Y. (2022) · Digital Transformation and Society · doi:10.1108/dts-05-2022-0016 · Cited by 17

DEFIDNET: A framework for optimal allocation of cyberdefenses in Intrusion Detection Networks

Pastrana, S., Tapiador, J., Orfila, A., & Lopez, P. P. (2015) · Computer Networks · doi:10.1016/j.comnet.2015.01.012 · Cited by 14

Honeypots Aiding Network Forensics: Challenges and Notions

Nasir, Q., & Almousa, Z. A. (2013) · Journal of Communications · doi:10.12720/jcm.8.11.700-707 · Cited by 14

Detecting Neighbor Discovery Protocol-Based Flooding Attack Using Machine Learning Techniques

Najjar, F., Kadhum, M. M., & El-Taj, H. R. (2016) · Lecture notes in electrical engineering · doi:10.1007/978-3-319-32213-1_12 · Cited by 14

A Distributed Intrusion Detection Scheme for Cloud Computing

Ibrahim, N. M., & Zainal, A. B. (2019) · International Journal of Distributed Systems and Technologies · doi:10.4018/ijdst.2020010106 · Cited by 14

Artificial intelligence methods used in industry 4.0 in particular industrial control systems

Tsochev, G., & Sharabov, M. (2021) · AIP conference proceedings · doi:10.1063/5.0041610 · Cited by 14

Dynamic information source selection for intrusion detection systems

Řehák, M., Staab, E., Pěchouček, M., Stiborek, J., Grill, M., & Bartoš, K. (2009) · Adaptive Agents and Multi-Agents Systems · doi:10.65109/gygn9048 · Cited by 14

Adaptive context-aware packet filter scheme using statistic-based blacklist generation in network intrusion detection

Meng, Y., & Kwok, L. F. (2011) · International Conference on Information Assurance and Security (IAS) · doi:10.1109/isias.2011.6122798 · Cited by 14

Trust-Based Classifier Combination for Network Anomaly Detection

Řehák, M., Pěchouček, M., Grill, M., & Bartoš, K. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-85834-8_11 · Cited by 14

Cybersecurity in supply chains: Addressing emerging threats with strategic measures

Ibiyemi, M. O., & Olutimehin, D. O. (2024) · International Journal of Management & Entrepreneurship Research · doi:10.51594/ijmer.v6i6.1241 · Cited by 13

Randomized Anagram revisited

Pastrana, S., Orfila, A., Tapiador, J., & Lopez, P. P. (2014) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2013.11.006 · Cited by 13

An Overview of Intrusion Detection and Prevention Systems (IDPS) and Security Issues

Sharif, Sharifi, A., Zad, F. F., Farokhmanesh, F., Noorollahi, A., & Sharif, J. (2014) · IOSR Journal of Computer Engineering · doi:10.9790/0661-16114752 · Cited by 13

Traffic Classification for the Detection of Anonymous Web Proxy Routing

Miller, S., Curran, K., & Lunney, T. (2015) · International Journal for Information Security Research · doi:10.20533/ijisr.2042.4639.2015.0061 · Cited by 13

Toward a Big Data Architecture for Security Events Analytic

Fetjah, L., Benzidane, K., Alloussi, H. E., Warrak, O. E., Andaloussi, S. J., & Sekkaki, A. (2016) · IEEE International Conference on Cyber Security and Cloud Computing (CSCloud) · doi:10.1109/cscloud.2016.53 · Cited by 13

synERGY: Cross-correlation of operational and contextual data to timely detect and mitigate attacks to cyber-physical systems

Skopik, F., Landauer, M., Wurzenberger, M., Vormayr, G., Milošević, J., Fabini, J., Prüggler, W., Kruschitz, O., Widmann, B., Truckenthanner, K., et al. (2020) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2020.102544 · Cited by 13

Intelligent Transportation Systems – Models, Challenges, Security Aspects

Kołodziej, J., Hopmann, C., Coppa, G., Grzonka, D., & Widłak, A. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-04036-8_3 · Cited by 13

An Online Intrusion Detection System to Cloud Computing Based on Neucube Algorithms

Almomani, A., Alauthman, M., Albalas, F. A., Dorgham, O. M., & Obeidat, A. A. (2020) · IGI Global eBooks · doi:10.4018/978-1-7998-2460-2.ch053 · Cited by 13

Review on state of art intrusion detection systems designed for the cloud computing paradigm

Premathilaka, N. A., Aponso, A. C., & Krishnarajah, N. (2013) · IEEE International Carnahan Conference on Security Technology (ICCST) · doi:10.1109/ccst.2013.6922049 · Cited by 13

Security operations center — A need for an academic environment

Aijaz, L., Aslam, B., & Khalid, U. (2015) · World Symposium on Computer Networks and Information Security (WSCNIS) · doi:10.1109/wscnis.2015.7368297 · Cited by 13

Viterbi algorithm for detecting DDoS attacks

Bongiovanni, W., Guelfi, A. E., Pontes, E., Silva, A., Zhou, F., & Kofuji, S. T. (2015) · Conference on Local Computer Networks · doi:10.1109/lcn.2015.7366308 · Cited by 13

Intrusion Prevention/Intrusion Detection System (IPS/IDS) for Wifi Networks

Korcak, M., Lámer, J., & Jakab, F. (2014) · International journal of Computer Networks & Communications · doi:10.5121/ijcnc.2014.6407 · Cited by 13

Cloud computing architectures based IDS

Saad, E. N., Elmahdi, K., & Zbakh, M. (2012) · doi:10.1109/icocs.2012.6458581 · Cited by 13

Increasing the level of network and information security using artificial intelligence

Pavlova, G., Tsochev, G., Yoshinov, R., Trifonov, R. I., & Manolov, S. (2017) · International Conference on Advances in Computing, Communication and Information Technology (CCIT) · doi:10.15224/978-1-63248-131-3-25 · Cited by 13

Trusted Time-Based Verification Model for Automatic Man-in-the-Middle Attack Detection in Cybersecurity

Kang, J. J., Fahd, K., & Venkatraman, S. (2018) · Cryptography · doi:10.3390/cryptography2040038 · Cited by 13

Implementing Security in IoT Ecosystem Using 5G Network Slicing and Pattern Matched Intrusion Detection System: A Simulation Study

Jain, A., Singh, T., Sharma, S., & Prajapati, V. (2021) · Interdisciplinary Journal of Information Knowledge and Management · doi:10.28945/4675 · Cited by 13

Use of Machine Learning Services in Cloud

Pawar, C. S., Ganatra, A. P., Nayak, A., Ramoliya, D., & Patel, R. (2021) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-16-0965-7_5 · Cited by 14

Intelligent Alarm Filter Using Knowledge-Based Alert Verification in Network Intrusion Detection

Meng, Y., Li, W., & Kwok, L. F. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-34624-8_14 · Cited by 13

A High-level Architecture for Intrusion Detection on Heterogeneous Wireless Sensor Networks: Hierarchical, Scalable and Dynamic Reconfigurable

Jadidoleslamy, H. (2011) · Wireless Sensor Network · doi:10.4236/wsn.2011.37026 · Cited by 13

Performance analysis in Intrusion Detection and Prevention Systems

Alsubhi, K., Bouabdallah, N., & Boutaba, R. (2011) · IFIP/IEEE International Symposium on Integrated Network Management (IM) · doi:10.1109/inm.2011.5990713 · Cited by 13

A misuse-based network Intrusion Detection System using Temporal Logic and stream processing

Ahmed, A., Lisitsa, A., & Dixon, C. (2011) · International Conference on Network and System Security (NSS) · doi:10.1109/icnss.2011.6059953 · Cited by 13

Cloud-based machine learning for the detection of anonymous web proxies

Miller, S., Curran, K., & Lunney, T. (2016) · Irish Signals and Systems Conference · doi:10.1109/issc.2016.7528443 · Cited by 13

Dynamic Fuzzy Rule Interpolation

Naik, N. (2015) · Cited by 13

Particle Swarm Optimization-Tuned Deep Neural Network for Cloud Intrusion Detection

Dewangan, O., Devarajan, H. R., Shrivastava, A., Somasekar, J., Al–Fatlawy, R. R., & Yadav, L. (2025) · International Conference on Innovations in Intelligent Systems: Advancements in Computing, Communication, and Cybersecurity (ISAC3) · doi:10.1109/isac364032.2025.11156943 · Cited by 12

Building an Information Technology Security Awareness and Training Program

Wilson, M., & Hash, J. (2003) · doi:10.6028/nist.sp.800-50 · Cited by 318

Contingency planning guide for information technology systems :

Swanson, M., Wohl, A., Pope, L., Grance, T., Hash, J., & Thomas, R. (2002) · doi:10.6028/nist.sp.800-34 · Cited by 30

Guide to test, training, and exercise programs for IT plans and capabilities

Grance, T., Nolan, T., Burke, K., Dudley, R., White, G., & Good, T. (2006) · doi:10.6028/nist.sp.800-84 · Cited by 41

Risk management guide for information technology systems :

Stoneburner, G., Goguen, A. Y., & Feringa, A. (2002) · doi:10.6028/nist.sp.800-30 · Cited by 1,357

DRAFT

Dworkin, M., Dworkin, M., Blank, R. M., Secretary, A., Gallagher, P. D., & -f, D. N. S. P. (2011)