26.1.6 Network Analysis, Wireless, Network Intrusion

Chapter Contents (Back)
Networks. Security. Intrusion Detection.
See also Sensor Networks. Vehicle Networks:
See also Security in Vehicle Networks, Blockchain, VANET.

Xing, D.S.[Dong-Shan], Girolami, M.A.[Mark A.],
Employing Latent Dirichlet Allocation for fraud detection in telecommunications,
PRL(28), No. 13, 1 October 2007, pp. 1727-1734.
Elsevier DOI 0709
Fraud detection; Telecommunications; User modelling; Data mining; Latent Dirichlet Allocation BibRef

Celikoglu, H.B., Gedizlioglu, E., Dell'Orco, M.,
A Node-Based Modeling Approach for the Continuous Dynamic Network Loading Problem,
ITS(10), No. 1, March 2009, pp. 165-174.
IEEE DOI 0903
BibRef

Beghdad, R.[Rachid],
Modelling intrusion detection as an allocation problem,
PRL(30), No. 8, 1 June 2009, pp. 774-779.
Elsevier DOI 0905
Allocation problem; Attacks database; Modelling attack classes; Misuse detection; Simulation tool BibRef

Thinh, T.N.[Tran Ngoc], Kittitornkun, S.[Surin], Tomiyama, S.[Shigenori],
PAMELA: Pattern Matching Engine with Limited-Time Update for NIDS/NIPS,
IEICE(E92-D), No. 5, May 2009, pp. 1049-1061.
WWW Link. 0907
Network intrusion detection, intrusion prevention. BibRef

Tavallaee, M., Stakhanova, N., Ghorbani, A.A.,
Toward Credible Evaluation of Anomaly-Based Intrusion-Detection Methods,
SMC-C(40), No. 5, September 2010, pp. 516-524.
IEEE DOI 1008
BibRef

Kim, K.J., Tsiftsis, T.A.,
Performance Analysis of Cyclically Prefixed Single-Carrier Transmissions With Outdated Opportunistic User Selection,
SPLetters(17), No. 10, October 2010, pp. 847-850.
IEEE DOI 1008
Transmission issues. BibRef

Taysi, Z.C., Yavuz, A.G.,
Routing Protocols for GeoNet: A Survey,
ITS(13), No. 2, June 2012, pp. 939-954.
IEEE DOI 1206
BibRef

Huang, Y.C.[Yi-Chao], Rao, B.D.,
Sum Rate Analysis of One-Pico-Inside OFDMA Network With Opportunistic Scheduling and Selective Feedback,
SPLetters(19), No. 7, July 2012, pp. 383-386.
IEEE DOI 1206
BibRef

Nguyen, H.X., Roughan, M.,
Improving Hidden Markov Model Inferences With Private Data From Multiple Observers,
SPLetters(19), No. 10, October 2012, pp. 696-699.
IEEE DOI 1209
BibRef

Krishnamurthy, V., Hoiles, W.,
Afriat's Test for Detecting Malicious Agents,
SPLetters(19), No. 12, December 2012, pp. 801-804.
IEEE DOI 1212
BibRef

Li, Y., Jin, D., Wang, Z., Zeng, L., Chen, S.,
Exponential and Power Law Distribution of Contact Duration in Urban Vehicular Ad Hoc Networks,
SPLetters(20), No. 1, January 2013, pp. 110-113.
IEEE DOI 1212
BibRef

Li, Y.[Yong], Jin, D.[Depeng], Hui, P.[Pan], Wang, Z.C.[Zhao-Cheng], Chen, S.[Sheng],
Limits of Predictability for Large-Scale Urban Vehicular Mobility,
ITS(15), No. 6, December 2014, pp. 2671-2682.
IEEE DOI 1412
mobility management (mobile radio) BibRef

Wang, C., Li, Y.[Yong], Jin, D.[Depeng], Chen, S.[Sheng],
On the Serviceability of Mobile Vehicular Cloudlets in a Large-Scale Urban Environment,
ITS(17), No. 10, October 2016, pp. 2960-2970.
IEEE DOI 1610
Cloud computing BibRef

Romero-Zurita, N., McLernon, D., Ghogho, M., Swami, A.,
PHY Layer Security Based on Protected Zone and Artificial Noise,
SPLetters(20), No. 5, May 2013, pp. 487-490.
IEEE DOI 1304
BibRef

Chandrasekaran, S.[Srimathi], Vaideeswaran, J.,
Meta-scheduler using agents for fault tolerance in computational grid,
IJCVR(4), No. 4, 2014, pp. 294-329.
DOI Link 1411
BibRef

Shen, Y.[Yun], Liu, Y.T.[Yi-Tong], Liu, J.[Jing], Yang, H.W.[Hong-Wen], Yang, D.C.[Da-Cheng],
A Novel Structure of HTTP Adaptive Streaming Based on Unequal Error Protection Rateless Code,
IEICE(E97-D), No. 11, November 2014, pp. 2903-2911.
WWW Link. 1412
BibRef

Bhuyan, M.H.[Monowar H.], Bhattacharyya, D.K., Kalita, J.K.,
An empirical evaluation of information metrics for low-rate and high-rate DDoS attack detection,
PRL(51), No. 1, 2015, pp. 1-7.
Elsevier DOI 1412
DDoS attack BibRef

Fu, B.[Bo], Xiao, Y.[Yang], Liang, X.N.[Xian-Nuan], Chen, C.L.P.,
Bio-inspired Group Modeling and Analysis for Intruder Detection in Mobile Sensor/Robotic Networks,
Cyber(45), No. 1, January 2015, pp. 103-115.
IEEE DOI 1502
mobile robots BibRef

Hui, H.[Hui], Swindlehurst, A.L., Li, G.B.[Guo-Bing], Liang, J.L.[Jun-Li],
Secure Relay and Jammer Selection for Physical Layer Security,
SPLetters(22), No. 8, August 2015, pp. 1147-1151.
IEEE DOI 1502
error statistics BibRef

Meng, X.M.[Xiang-Ming], Wu, S.[Sheng], Kuang, L.L.[Lin-Ling], Lu, J.H.[Jian-Hua],
An Expectation Propagation Perspective on Approximate Message Passing,
SPLetters(22), No. 8, August 2015, pp. 1194-1197.
IEEE DOI 1502
approximation theory BibRef

Rawat, D.B., Bajracharya, C.,
Detection of False Data Injection Attacks in Smart Grid Communication Systems,
SPLetters(22), No. 10, October 2015, pp. 1652-1656.
IEEE DOI 1506
Kalman filters BibRef

Rastegarnia, A.[Amir], Khalili, A.[Azam], Bazzi, W.M.[Wael M.], Sanei, S.[Saeid],
An incremental LMS network with reduced communication delay,
SIViP(10), No. 4, April 2016, pp. 769-775.
Springer DOI 1604
BibRef

Brandt, R., Mochaourab, R., Bengtsson, M.,
Globally Optimal Base Station Clustering in Interference Alignment-Based Multicell Networks,
SPLetters(23), No. 4, April 2016, pp. 512-516.
IEEE DOI 1604
Base stations BibRef

Jo, H.G.[Hyeong Gon], Son, T.Y.[Tae Yong], Jeong, S.Y.[Seol Young], Kang, S.J.[Soon Ju],
Proximity-Based Asynchronous Messaging Platform for Location-Based Internet of Things Service,
IJGI(5), No. 7, 2016, pp. 116.
DOI Link 1608
BibRef

Utkovski, Z., Simeone, O., Dimitrova, T., Popovski, P.,
Random Access in C-RAN for User Activity Detection With Limited-Capacity Fronthaul,
SPLetters(24), No. 1, January 2017, pp. 17-21.
IEEE DOI 1702
cloud computing BibRef

Yu, N.Y.,
Indistinguishability of Compressed Encryption With Circulant Matrices for Wireless Security,
SPLetters(24), No. 2, February 2017, pp. 181-185.
IEEE DOI 1702
compressed sensing BibRef

Chen, Q., Kang, D., He, Y., Chang, T.H., Liu, Y.F.,
Joint Power and Admission Control Based on Channel Distribution Information: A Novel Two-Timescale Approach,
SPLetters(24), No. 2, February 2017, pp. 196-200.
IEEE DOI 1702
approximation theory BibRef

Li, W., Wang, X., Moran, B.,
Wireless Signal Travel Distance Estimation Using Non-Coprime Wavelengths,
SPLetters(24), No. 1, January 2017, pp. 27-31.
IEEE DOI 1702
signal processing BibRef

Kwon, M., Park, H.,
Distributed Network Formation Strategy for Network Coding Based Wireless Networks,
SPLetters(24), No. 4, April 2017, pp. 432-436.
IEEE DOI 1704
decision making BibRef

Sedjelmaci, H., Senouci, S.M., Ansari, N.,
Intrusion Detection and Ejection Framework Against Lethal Attacks in UAV-Aided Networks: A Bayesian Game-Theoretic Methodology,
ITS(18), No. 5, May 2017, pp. 1143-1153.
IEEE DOI 1705
Bayes methods, Games, Intrusion detection, Monitoring, Unmanned aerial vehicles, Bayesian game, intrusion detection system (IDS), intrusion ejection system (IES), unmanned aerial vehicles (UAVs), vehicular, networks BibRef

Larhlimi, A., Mestari, M., El Khaili, M.,
GPU parallel neural hierarchical multi objective solver for burst routing and wavelength assignment,
ISCV17(1-6)
IEEE DOI 1710
Burst Routing and Wavelength Assignment, Compute Unified Device Architecture, Graphics Processing Unit, BibRef

Yin, H., Zhang, X., Zhao, S., Luo, Y., Tian, C., Sekar, V.,
Tradeoffs Between Cost and Performance for CDN Provisioning Based on Coordinate Transformation,
MultMed(19), No. 11, November 2017, pp. 2583-2596.
IEEE DOI 1710
Decision support systems, Clustering, server provisioning, transform BibRef

Guerreiro, P., Xavier, J.,
Distributed Learning With Time Correlated Information,
SPLetters(24), No. 11, November 2017, pp. 1636-1640.
IEEE DOI 1710
Communication networks, Correlation, Diseases, Indexes, Markov processes, Time measurement, Distributed learning, Markov chains, Perron-Frobenius theorem, multiple hypotheses testing, networks BibRef

Hu, D., Zhang, Q., Yang, P., Qin, J.,
Proactive Monitoring via Jamming in Amplify-and-Forward Relay Networks,
SPLetters(24), No. 11, November 2017, pp. 1714-1718.
IEEE DOI 1710
Jamming, Monitoring, Relay networks (telecommunications), Search methods, Wireless communication, Amplify-and-forward (AF), BibRef

AlEroud, A.F., Karabatis, G.,
Queryable Semantics to Detect Cyber-Attacks: A Flow-Based Detection Approach,
SMCS(48), No. 2, February 2018, pp. 207-223.
IEEE DOI 1801
Context, Data mining, Feature extraction, Force, Intrusion detection, Semantics, Context, information security, intrusion detection, semantic link network (SLN) BibRef

Kozik, R.[Rafal],
Distributing extreme learning machines with Apache Spark for NetFlow-based malware activity detection,
PRL(101), No. 1, 2018, pp. 14-20.
Elsevier DOI 1801
Netflow BibRef

Ghofrani, F.[Fatemeh], Keshavarz-Haddad, A.[Alireza], Jamshidi, A.[Ali],
A new probabilistic classifier based on decomposable models with application to internet traffic,
PR(77), 2018, pp. 1-11.
Elsevier DOI 1802
Decomposable models, Over-fitting, TAN based on Chow-Liu algorithm, Averaged TAN, Internet traffic classification BibRef

Japkowicz, N., Elovici, Y.,
Introduction to the Special Issue on Data Mining for Cybersecurity,
IEEE_Int_Sys(33), No. 2, March 2018, pp. 3-4.
IEEE DOI 1806
Anomaly detection, Authentication, Biometrics (access control), Computer security, Data mining, Intrusion detection, SCADA systems, vulnerability assessment BibRef

Noble, J., Adams, N.,
Real-Time Dynamic Network Anomaly Detection,
IEEE_Int_Sys(33), No. 2, March 2018, pp. 5-18.
IEEE DOI 1806
Adaptation models, Adaptive estimation, Anomaly detection, Computer security, Image edge detection, ReTiNA, streaming data BibRef

Grolman, E.[Edita], Finkelshtein, A.[Andrey], Puzis, R.[Rami], Shabtai, A.[Asaf], Celniker, G.[Gershon], Katzir, Z.[Ziv], Rosenfeld, L.[Liron],
Transfer Learning for User Action Identication in Mobile Apps via Encrypted Traffic Analysis,
IEEE_Int_Sys(33), No. 2, March 2018, pp. 40-53.
IEEE DOI 1806
What action in mobile app from network traffic. Cryptography, Feature extraction, Intelligent systems, Mobile communication, Object recognition, transfer learning BibRef

Li, B., Yao, Y., Chen, H., Li, Y., Huang, S.,
Wireless Information Surveillance and Intervention Over Multiple Suspicious Links,
SPLetters(25), No. 8, August 2018, pp. 1131-1135.
IEEE DOI 1808
computational complexity, concave programming, integer programming, jamming, nonlinear programming, proactive intervening BibRef

Meng, W.,
Intrusion Detection in the Era of IoT: Building Trust via Traffic Filtering and Sampling,
Computer(51), No. 7, July 2018, pp. 36-43.
IEEE DOI 1808
Intrusion detection, Computer security, Internet of Things, Trust management, Privacy, Bayes methods, Internet of Things, IoT, Cybertrust in the IoT Age BibRef

Jiménez Tejero, C.E., Sallares, V., Ranero, C.R.,
Appraisal of Instantaneous Phase-Based Functions in Adjoint Waveform Inversion,
GeoRS(56), No. 9, September 2018, pp. 5185-5197.
IEEE DOI 1809
IP networks, Robustness, Receivers, Signal analysis, Acoustics, Tools, Computational modeling, Acoustic propagation, phase estimation BibRef

Chen, C.H.[Chi-Hua], Lo, K.R.[Kuen-Rong],
Applications of Internet of Things,
IJGI(7), No. 9, 2018, pp. xx-yy.
DOI Link 1810
BibRef

Mousavinejad, E., Yang, F., Han, Q., Vlacic, L.,
A Novel Cyber Attack Detection Method in Networked Control Systems,
Cyber(48), No. 11, November 2018, pp. 3254-3264.
IEEE DOI 1810
Cyberattack, Ellipsoids, Estimation, Actuators, Detectors, Kalman filters, Current measurement, Bias injection attacks, set-membership filtering BibRef

Garg, S., Kaur, K., Kumar, N., Rodrigues, J.J.P.C.[J. J. P. C.],
Hybrid Deep-Learning-Based Anomaly Detection Scheme for Suspicious Flow Detection in SDN: A Social Multimedia Perspective,
MultMed(21), No. 3, March 2019, pp. 566-578.
IEEE DOI 1903
Boltzmann machines, computer network security, gradient methods, learning (artificial intelligence), multimedia computing, social multimedia BibRef

Shang, Y.,
Subgraph Robustness of Complex Networks Under Attacks,
SMCS(49), No. 4, April 2019, pp. 821-832.
IEEE DOI 1903
Robustness, Complex networks, Social network services, Complex systems, Sampling methods, Attack robustness, sampling BibRef

Phetlasy, S.[Sornxayya], Ohzahata, S.[Satoshi], Wu, C.[Celimuge], Kato, T.[Toshihito],
A Sequential Classifiers Combination Method to Reduce False Negative for Intrusion Detection System,
IEICE(E102-D), No. 5, May 2019, pp. 888-897.
WWW Link. 1906
BibRef

Gao, N., Qin, Z., Jing, X.,
Pilot Contamination Attack Detection and Defense Strategy in Wireless Communications,
SPLetters(26), No. 6, June 2019, pp. 938-942.
IEEE DOI 1906
Contamination, Training, Covariance matrices, Receivers, Eigenvalues and eigenfunctions, Wireless communication, wireless communications BibRef

Cho, K., Lee, S., Khisti, A.,
Effect of User Cooperation on Smart Meter Privacy With Rechargeable Batteries,
SPLetters(26), No. 7, July 2019, pp. 971-975.
IEEE DOI 1906
data privacy, power engineering computing, secondary cells, smart meters, smart power grids, user cooperation, user privacy, information leakage BibRef

Antal, M.[Margit], Egyed-Zsigmond, E.[Elöd],
Intrusion detection using mouse dynamics,
IET-Bio(8), No. 5, September 2019, pp. 285-294.
DOI Link 1908
BibRef

Castaño, F.[Fernando], Strzelczak, S.[Stanislaw], Villalonga, A.[Alberto], Haber, R.E.[Rodolfo E.], Kossakowska, J.[Joanna],
Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Ma, W.[Wen], Zhang, X.Y.[Xin-Yang], Xin, Y.[Yong], Li, S.Z.[Shen-Zhang],
Study on short-term network forecasting based on SVM-MFA algorithm,
JVCIR(65), 2019, pp. 102646.
Elsevier DOI 1912
Support vector machine, Improved firefly algorithm, Load forecasting, Nonlinear regression, Evaluation criteria BibRef

Meng, Y.[Yuan], Tu, S.S.[Shan-Shan], Yu, J.L.[Jin-Liang], Huang, F.M.[Feng-Ming],
Intelligent attack defense scheme based on DQL algorithm in mobile fog computing,
JVCIR(65), 2019, pp. 102656.
Elsevier DOI 1912
Computing on the network edge plus cloud. Moving fog computing, Intelligent attack, Physical layer security, Prospect theory, Reinforcement learning BibRef

Hwang, K.,
Blocking of operation of unauthorised software using MQTT,
IJCVR(9), No. 6, 2019, pp. 609-620.
DOI Link 1912
BibRef

Chen, X.F.[Xiao-Fan], Yu, S.Z.[Shun-Zheng],
A Collaborative Intrusion Detection System against DDoS for SDN,
IEICE(E99-D), No. 9, September 2016, pp. 2395-2399.
WWW Link. 1609
BibRef

Wu, W., Li, R., Xie, G., An, J., Bai, Y., Zhou, J., Li, K.,
A Survey of Intrusion Detection for In-Vehicle Networks,
ITS(21), No. 3, March 2020, pp. 919-933.
IEEE DOI 2003
Controller area network (CAN), cybersecurity, in-vehicle network (IVN), intrusion detection system (IDS), machine learning BibRef

Liu, C.B.[Chuan-Bin], Tian, Y.[Youliang], Xie, H.T.[Hong-Tao],
Law Is Order: Protecting Multimedia Network Transmission by Game Theory and Mechanism Design,
MMMod20(II:651-668).
Springer DOI 2003
BibRef

Sun, L., Wang, X., Yang, A., Huang, Z.,
Radio Frequency Fingerprint Extraction Based on Multi-Dimension Approximate Entropy,
SPLetters(27), 2020, pp. 471-475.
IEEE DOI 2004
Entropy, Feature extraction, Wireless networks, Security, Steady-state, Nonlinear dynamical systems, Silicon, wireless network security BibRef

Cho, M.K.[Min-Kyoung], Kim, J.S.[Jik-Soo], Shin, J.[Jongho], Shin, I.[Incheol],
Mal2d: 2d Based Deep Learning Model for Malware Detection Using Black and White Binary Image,
IEICE(E103-D), No. 4, April 2020, pp. 896-900.
WWW Link. 2004
BibRef

Ye, Z.[Zehua], Ni, H.J.[Hong-Jie], Xu, Z.H.[Zhen-Hua], Zhang, D.[Dan],
Sensor fault estimation of networked vehicle suspension system with deny-of-service attack,
IET-ITS(14), No. 5, May 2020, pp. 455-462.
DOI Link 2005
BibRef

Kim, K.[Kwangjo],
Intrusion Detection System Using Deep Learning and Its Application to Wi-Fi Network,
IEICE(E103-D), No. 7, July 2020, pp. 1433-1447.
WWW Link. 2007
BibRef

Liang, J., Lin, Q., Chen, J., Zhu, Y.,
A Filter Model Based on Hidden Generalized Mixture Transition Distribution Model for Intrusion Detection System in Vehicle Ad Hoc Networks,
ITS(21), No. 7, July 2020, pp. 2707-2722.
IEEE DOI 2007
Hidden Markov models, Vehicular ad hoc networks, Reliability, Intrusion detection, Safety, Computational modeling, filter model based on HgMTD model (FM-HgMTD) BibRef

Rahmani, F., Touhami, N.A., Taher, N., Kchairi, A.B.,
Reconfigurable Radiation Pattern Antenna with eight Switchable Beams in Azimuth Plane for WLAN Wireless System,
ISCV20(1-7)
IEEE DOI 2011
antenna feeds, antenna radiation patterns, coaxial cables, p-i-n diodes, wireless LAN, circular planar ground, star patch, radiation pattern. BibRef

Dommel, J.[Johannes], Utkovski, Z.[Zoran], Simeone, O.[Osvaldo], Stanczak, S.[Slawomir],
Joint Source-Channel Coding for Semantics-Aware Grant-Free Radio Access in IoT Fog Networks,
SPLetters(28), 2021, pp. 728-732.
IEEE DOI 2105
Encoding, Sensors, Message passing, Decoding, Wireless sensor networks, Wireless communication, Bayes methods, semantic communications BibRef

Park, S.H.[Seok-Hwan], Jin, X.[Xianglan],
Joint Secure Design of Downlink and D2D Cooperation Strategies for Multi-User Systems,
SPLetters(28), 2021, pp. 917-921.
IEEE DOI 2106
Device-to-device communication, Downlink, Precoding, Covariance matrices, Eavesdropping, Optimization, Additive noise, matrix fractional programming BibRef

Wang, Z.[Zisheng], Blum, R.S.[Rick S.],
Elimination of Undetectable Attacks on Natural Gas Networks,
SPLetters(28), 2021, pp. 1002-1005.
IEEE DOI 2106
Natural gas, Mathematical model, Pipelines, Analytical models, Topology, Noise measurement, SCADA systems, Cybersecurity, undetectable attacks BibRef

Riddle-Workman, E.[Elizabeth], Evangelou, M.[Marina], Adams, N.M.[Niall M.],
Multi-type relational clustering for enterprise cyber-security networks,
PRL(149), 2021, pp. 172-178.
Elsevier DOI 2108
Non-negative matrix factorization, Multi-type relational clustering, Cyber-security, Network clustering BibRef

Bhardwaj, J.[Jayati], Yadav, V.K.[Virendra Kumar], Trivedi, M.C.[Munesh Chandra], Sen, A.K.[Anurag Kumar],
ARP cache poisoning: detection, mitigation and prevention schemes,
IJCVR(11), No. 4, 2021, pp. 357-373.
DOI Link 2108
BibRef

Mejia-Cabrera, H.I.[Heber I.], Paico-Chileno, D.[Daniel], Valdera-Contreras, J.H.[Jhon H.], Tuesta-Monteza, V.A.[Victor A.], Forero, M.G.[Manuel G.],
Automatic Detection of Injection Attacks by Machine Learning in NoSQL Databases,
MCPR21(23-32).
Springer DOI 2108
BibRef

Amato, F.[Flora], Coppolino, L.[Luigi], Mercaldo, F.[Francesco], Moscato, F.[Francesco], Nardone, R.[Roberto], Santone, A.[Antonella],
CAN-Bus Attack Detection With Deep Learning,
ITS(22), No. 8, August 2021, pp. 5081-5090.
IEEE DOI 2108
Standards, Deep learning, Automobiles, Protocols, Biological neural networks, Wireless communication, Automotive, security BibRef

Cho, Y.B.[Young-Bok],
Malware classifier for dynamic deep learning algorithm,
IJCVR(11), No. 5, 2021, pp. 486-496.
DOI Link 2109
BibRef

Chou, D.[Dylan], Jiang, M.[Meng],
A Survey on Data-Driven Network Intrusion Detection,
Surveys(54), No. 9, October 2021, pp. xx-yy.
DOI Link 2112
data mining, machine learning, Network intrusion detection BibRef

Arulananth, T.S., Baskar, M., Anbarasu, V., Thiagarajan, R., Rajendran, T., Balaji, A.,
Multi party secure data access management in cloud using user centric block chain data encryption,
PRL(152), 2021, pp. 295-301.
Elsevier DOI 2112
Cloud, Data security, Data encryption, UCBE, MSDAM, Distancing scheme, QoS BibRef

Vijayakumar, M., Shiny Angel, T.S.,
Performing Attack Halting Process with Digital Pattern and Proactive Model Resolving the Security Issues in IoT Based Models,
PRL(152), 2021, pp. 428-435.
Elsevier DOI 2112
PDoS attack, RNN algorithm, IoT models, Cyber-attack BibRef

Mehraj, H.[Haider], Jayadevappa, D., Haleem, S.L.A.[Sulaima Lebbe Abdul], Parveen, R.[Rehana], Madduri, A.[Abhishek], Ayyagari, M.R.[Maruthi Rohit], Dhabliya, D.[Dharmesh],
Protection motivation theory using multi-factor authentication for providing security over social networking sites,
PRL(152), 2021, pp. 218-224.
Elsevier DOI 2112
Trusted authentication, Security vulnerabilities, Social media, Protective motivation theory, Multi-factor authentication, Prevention strategy BibRef

Wei, S.M.[Shi-Mei], Pan, J.H.[Jing-Hu],
Resilience of Urban Network Structure in China: The Perspective of Disruption,
IJGI(10), No. 12, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Saveetha, D., Maragatham, G.,
Design of Blockchain enabled intrusion detection model for detecting security attacks using deep learning,
PRL(153), 2022, pp. 24-28.
Elsevier DOI 2201
Attack, Blockchain, Deep learning, Intrusion detection, Machine learning BibRef

Zhang, F.[Fei], Zhen, P.N.[Pei-Ning], Jing, D.S.[Di-Shan], Tang, X.T.[Xiao-Tang], Chen, H.B.[Hai-Bao], Yan, J.[Jie],
SVM Based Intrusion Detection Method with Nonlinear Scaling and Feature Selection,
IEICE(E105-D), No. 5, May 2022, pp. 1024-1038.
WWW Link. 2205
BibRef

Aoudni, Y.[Yassine], Donald, C.[Cecil], Farouk, A.[Ahmed], Sahay, K.B.[Kishan Bhushan], Babu, D.V.[D. Vijendra], Tripathi, V.[Vikas], Dhabliya, D.[Dharmesh],
Cloud security based attack detection using transductive learning integrated with Hidden Markov Model,
PRL(157), 2022, pp. 16-26.
Elsevier DOI 2205
Zero-day attack security, Transductive deep learning, Hidden Markov Model (HMM), Soft labels, K-medoids clustering BibRef

Balamurugan, E., Mehbodniya, A.[Abolfazl], Kariri, E.[Elham], Yadav, K.[Kusum], Kumar, A.[Anil], Anul Haq, M.[Mohd],
Network optimization using defender system in cloud computing security based intrusion detection system withgame theory deep neural network (IDSGT-DNN),
PRL(156), 2022, pp. 142-151.
Elsevier DOI 2205
Cloud Computing, Game theory, Optimization, CICIDS - 2017 dataset, Deep Neural Network BibRef

Fei, Z.Y.[Zhong-Yang], Wang, X.D.[Xu-Dong], Wang, Z.H.[Zhen-Hua],
Event-Based Fault Detection for Unmanned Surface Vehicles Subject to Denial-of-Service Attacks,
SMCS(52), No. 5, May 2022, pp. 3326-3336.
IEEE DOI 2205
Fault detection, Jamming, Denial-of-service attack, Communication networks, Wireless communication, unmanned surface vehicles (USVs) BibRef

Zhao, Y.R.[Yu-Rui], Wang, X.[Xiang], Lin, Z.Y.[Zi-Yu], Huang, Z.T.[Zhi-Tao],
Multi-Classifier Fusion for Open-Set Specific Emitter Identification,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Huang, Y.[Yi], Li, Y.[Ying], Heyes, T.[Timothy], Jourjon, G.[Guillaume], Cheng, A.[Adriel], Seneviratne, S.[Suranga], Thilakarathna, K.[Kanchana], Webb, D.[Darren], Xu, R.Y.D.[Richard Yi Da],
Task adaptive siamese neural networks for open-set recognition of encrypted network traffic with bidirectional dropout,
PRL(159), 2022, pp. 132-139.
Elsevier DOI 2206
DPGMM, Bidirectional dropout, Siamese, Open-set recognition BibRef

Foss, K.[Kyle], Couckuyt, I.[Ivo], Baruta, A.[Adrian], Mossoux, C.[Corentin],
Automated Software Defect Detection and Identification in Vehicular Embedded Systems,
ITS(23), No. 7, July 2022, pp. 6963-6973.
IEEE DOI 2207
Testing, Software, Automotive engineering, Electronic countermeasures, Complexity theory, Europe, system verification BibRef

Gao, B.[Bing], Bu, B.[Bing], Zhang, W.[Wei], Li, X.[Xiang],
An Intrusion Detection Method Based on Machine Learning and State Observer for Train-Ground Communication Systems,
ITS(23), No. 7, July 2022, pp. 6608-6620.
IEEE DOI 2207
Intrusion detection, Protocols, Observers, Anomaly detection, Machine learning algorithms, Communication systems, denial of service BibRef

dos Santos-Roque, A.[Alexandre], Jazdi, N.[Nasser], de Freitas, E.P.[Edison Pignaton], Pereira, C.E.[Carlos Eduardo],
A Fault Modeling Based Runtime Diagnostic Mechanism for Vehicular Distributed Control Systems,
ITS(23), No. 7, July 2022, pp. 7220-7232.
IEEE DOI 2207
Protocols, Degradation, Runtime, Automotive engineering, Decentralized control, Data models, Task analysis, vehicular control systems BibRef

Taguchi, S.[Shun], Yoshimura, T.[Takayoshi],
Online Estimation and Prediction of Large-Scale Network Traffic From Sparse Probe Vehicle Data,
ITS(23), No. 7, July 2022, pp. 7233-7243.
IEEE DOI 2207
Roads, Probes, Data models, Data assimilation, Predictive models, Neural networks, Network topology, Data assimilation, traffic speed prediction BibRef

Cai, X.Q.[Xing-Qiang], Wu, C.[Cheng], Sheng, J.[Jie], Wang, Y.M.[Yi-Ming], Ai, B.[Bo],
Spectrum Situation Awareness Based on Time-Series Depth Networks for LTE-R Communication System,
ITS(23), No. 7, July 2022, pp. 8629-8640.
IEEE DOI 2207
Rail transportation, Hidden Markov models, Predictive models, Cognitive radio, Wireless sensor networks, Resource management, spectrum situation awareness BibRef

Kye, H.[Hyoseon], Kim, M.[Miru], Kwon, M.[Minhae],
Hierarchical Detection of Network Anomalies: A Self-Supervised Learning Approach,
SPLetters(29), 2022, pp. 1908-1912.
IEEE DOI 2209
Decoding, Training, Network intrusion detection, Simulation, Training data, Standards, Self-supervised learning, autoencoder BibRef

Al-Yaseen, W.L.[Wathiq Laftah], Idrees, A.K.[Ali Kadhum], Almasoudy, F.H.[Faezah Hamad],
Wrapper feature selection method based differential evolution and extreme learning machine for intrusion detection system,
PR(132), 2022, pp. 108912.
Elsevier DOI 2209
Intrusion detection system (IDS), Feature selection, Differential evolution (DE), Extreme learning machine (ELM), NSL-KDD BibRef

He, Y.C.[Yu-Chu], Jia, Z.J.[Zhi-Juan], Hu, M.S.[Ming-Sheng], Cui, C.[Chi], Cheng, Y.[Yage], Yang, Y.Y.[Yan-Yan],
The Hybrid Similar Neighborhood Robust Factorization Machine Model for Can Bus Intrusion Detection in the In-Vehicle Network,
ITS(23), No. 9, September 2022, pp. 16833-16841.
IEEE DOI 2209
Mathematical models, Data models, Intrusion detection, Predictive models, Robustness, Computational modeling, factorization machine BibRef

Jichici, C.[Camil], Groza, B.[Bogdan], Ragobete, R.[Radu], Murvay, P.S.[Pal-Stefan], Andreica, T.[Tudor],
Effective Intrusion Detection and Prevention for the Commercial Vehicle SAE J1939 CAN Bus,
ITS(23), No. 10, October 2022, pp. 17425-17439.
IEEE DOI 2210
Intrusion detection, Standards, Protocols, Real-time systems, Payloads, Logic gates, Bit rate, CAN bus, J1939 BibRef

Sathish, N., Valarmathi, N.,
Detection of Intrusion behavior in cloud applications using Pearson's chi-squared distribution and decision tree classifiers,
PRL(162), 2022, pp. 15-21.
Elsevier DOI 2210
Intrusion behavior, Machinelearning, Optimalfeatures, Decision tree, Security, Fog BibRef

Agrawal, K.[Kushagra], Alladi, T.[Tejasvi], Agrawal, A.[Ayush], Chamola, V.[Vinay], Benslimane, A.[Abderrahim],
NovelADS: A Novel Anomaly Detection System for Intra-Vehicular Networks,
ITS(23), No. 11, November 2022, pp. 22596-22606.
IEEE DOI 2212
Feature extraction, Protocols, Anomaly detection, Deep learning, Intrusion detection, Computational modeling, Convolution, network security BibRef

Shi, Z.X.[Zhi-Xin], Wang, X.Y.[Xiang-Yu], Liu, P.C.[Peng-Cheng],
NBP-MS: Malware Signature Generation Based on Network Behavior Profiling,
ICPR22(1865-1870)
IEEE DOI 2212
Telecommunication traffic, Malware, Behavioral sciences, Computer crime BibRef

Koroniotis, N.[Nickolaos], Moustafa, N.[Nour], Schiliro, F.[Francesco], Gauravaram, P.[Praveen], Janicke, H.[Helge],
The SAir-IIoT Cyber Testbed as a Service: A Novel Cybertwins Architecture in IIoT-Based Smart Airports,
ITS(24), No. 2, February 2023, pp. 2368-2381.
IEEE DOI 2302
Industrial Internet of Things, Airports, Computer crime, Security, Testing, Australia, Protocols, Smart airport, testbed, cybertwins, cyber defences BibRef

Wang, K.[Kai], Zhang, A.[Aiheng], Sun, H.R.[Hao-Ran], Wang, B.L.[Bai-Ling],
Analysis of Recent Deep-Learning-Based Intrusion Detection Methods for In-Vehicle Network,
ITS(24), No. 2, February 2023, pp. 1843-1854.
IEEE DOI 2302
Intrusion detection, Biological system modeling, Periodic structures, Deep learning, Adaptation models, Security, vehicular networks BibRef

Rajapaksha, S.[Sampath], Kalutarage, H.[Harsha], Al-Kadri, M.O.[M. Omar], Petrovski, A.[Andrei], Madzudzo, G.[Garikayi], Cheah, M.[Madeline],
AI-Based Intrusion Detection Systems for In-Vehicle Networks: A Survey,
Surveys(55), No. 11, February 2023, pp. xx-yy.
DOI Link 2303
machine learning, Controller Area Network (CAN), Intrusion Detection System (IDS), automotive cybersecurity, in-vehicle network BibRef

Li, S.D.[Shu-Dong], Li, Y.[Yuan], Wu, X.B.[Xiao-Bo], Otaibi, S.A.[Sattam Al], Tian, Z.H.[Zhi-Hong],
Imbalanced Malware Family Classification Using Multimodal Fusion and Weight Self-Learning,
ITS(24), No. 7, July 2023, pp. 7642-7652.
IEEE DOI 2307
Malware, Feature extraction, Histograms, Machine learning, Codes, Task analysis, Semantics, Malware family classification, imbalanced data BibRef

Zhang, C.H.[Chen-Hao], Yin, S.[Shuijun], Li, H.[Heng], Cai, M.H.[Ming-Hui], Yuan, W.[Wei],
Detecting Android Malware With Pre-Existing Image Classification Neural Networks,
SPLetters(30), 2023, pp. 858-862.
IEEE DOI 2307
Perturbation methods, Feature extraction, Malware, Operating systems, Neural networks, Task analysis, malware detection BibRef

Xue, S.S.[Shuang-Si], Li, H.[Huan], Cao, H.[Hui], Tan, J.K.[Jun-Kai],
Distributed edge-event-triggered consensus of multi-agent system under DoS attack,
PRL(174), 2023, pp. 118-123.
Elsevier DOI 2310
Multi-agent systems, Consensus control, Edge-event-triggered, DoS attacks BibRef

Ding, Z.X.[Zhao-Xu], Zhong, G.Q.[Guo-Qiang], Qin, X.P.[Xian-Ping], Li, Q.Y.[Qing-Yang], Fan, Z.[Zhenlin], Deng, Z.Y.[Zhao-Yang], Ling, X.[Xiao], Xiang, W.[Wei],
MF-Net: Multi-frequency intrusion detection network for Internet traffic data,
PR(146), 2024, pp. 109999.
Elsevier DOI 2311
Cyber security, Intrusion detection, Deep learning, Multi-frequency transformer, Multi-frequency LSTM BibRef

Lee, S.[Seyoung], Choi, W.[Wonsuk], Jo, H.J.[Hyo Jin], Lee, D.H.[Dong Hoon],
ErrIDS: An Enhanced Cumulative Timing Error-Based Automotive Intrusion Detection System,
ITS(24), No. 11, November 2023, pp. 12406-12421.
IEEE DOI 2311
BibRef

Zhou, J.[Jia], Xie, G.Q.[Guo-Qi], Zeng, H.B.[Hai-Bo], Zhang, W.Z.[Wei-Zhe], Yang, L.T.[Laurence T.], Alazab, M.[Mamoun], Li, R.[Renfa],
A Model-Based Method for Enabling Source Mapping and Intrusion Detection on Proprietary Can Bus,
ITS(24), No. 11, November 2023, pp. 12922-12932.
IEEE DOI 2311
BibRef

Chougule, A.[Amit], Kohli, V.[Varun], Chamola, V.[Vinay], Yu, F.R.[Fei Richard],
Multibranch Reconstruction Error (MbRE) Intrusion Detection Architecture for Intelligent Edge-Based Policing in Vehicular Ad-Hoc Networks,
ITS(24), No. 11, November 2023, pp. 13068-13077.
IEEE DOI 2311
BibRef

Almutlaq, S.[Samah], Derhab, A.[Abdelouahid], Hassan, M.M.[Mohammad Mehedi], Kaur, K.[Kuljeet],
Two-Stage Intrusion Detection System in Intelligent Transportation Systems Using Rule Extraction Methods From Deep Neural Networks,
ITS(24), No. 12, December 2023, pp. 15687-15701.
IEEE DOI 2312
BibRef

Zhang, J.[Jiangjiang], Gong, B.[Bei], Waqas, M.[Muhammad], Tu, S.S.[Shan-Shan], Chen, S.[Sheng],
Many-Objective Optimization Based Intrusion Detection for in-Vehicle Network Security,
ITS(24), No. 12, December 2023, pp. 15051-15065.
IEEE DOI 2312
BibRef

Anbalagan, S.[Sudha], Raja, G.[Gunasekaran], Gurumoorthy, S.[Sugeerthi], Suresh, R.D.[R. Deepak], Dev, K.[Kapal],
IIDS: Intelligent Intrusion Detection System for Sustainable Development in Autonomous Vehicles,
ITS(24), No. 12, December 2023, pp. 15866-15875.
IEEE DOI 2312
BibRef

Qian, Z.J.[Zhen-Jiang], Zhong, S.[Shan], Sun, G.F.[Gao-Fei], Xing, X.S.[Xiao-Shuang], Jin, Y.[Yong],
A Formal Approach to Design and Security Verification of Operating Systems for Intelligent Transportation Systems Based on Object Model,
ITS(24), No. 12, December 2023, pp. 15459-15467.
IEEE DOI 2312
BibRef

da Cruz, M.A.A.[Mauro A. A.], Abbade, L.R.[Lucas R.], Lorenz, P.[Pascal], Mafra, S.B.[Samuel B.], Rodrigues, J.J.P.C.[Joel J. P. C.],
Detecting Compromised IoT Devices Through XGBoost,
ITS(24), No. 12, December 2023, pp. 15392-15399.
IEEE DOI 2312
BibRef

Li, Y.[Yang], Zhu, L.[Li], Wang, H.W.[Hong-Wei], Yu, F.R.[F. Richard], Tang, T.[Tao], Zhang, D.J.[Da-Jun],
Joint Security and Resources Allocation Scheme Design in Edge Intelligence Enabled CBTCs: A Two-Level Game Theoretic Approach,
ITS(24), No. 12, December 2023, pp. 13948-13961.
IEEE DOI 2312
communication-based train control. Secruity for control systems. BibRef

Zahid, M.U.[Muhammad Usama], Nisar, M.D.[Muhammad Danish], Shah, M.H.[Maqsood Hussain], Hussain, S.A.[Syed Aamer],
Specific Emitter Identification Based on Multi-Scale Multi-Dimensional Approximate Entropy,
SPLetters(31), 2024, pp. 850-854.
IEEE DOI 2404
Entropy, Vectors, Feature extraction, Steady-state, Training, Signal to noise ratio, Signal processing algorithms, specific emitter identification BibRef

Cao, J.H.[Jin-Hui], Di, X.Q.[Xiao-Qiang], Liu, X.[Xu], Li, J.Q.[Jin-Qing], Li, Z.[Zhi], Zhao, L.[Liang], Hawbani, A.[Ammar], Guizani, M.[Mohsen],
Anomaly Detection for In-Vehicle Network Using Self-Supervised Learning With Vehicle-Cloud Collaboration Update,
ITS(25), No. 7, July 2024, pp. 7454-7466.
IEEE DOI 2407
Anomaly detection, Feature extraction, Predictive models, Data models, Transformers, Intrusion detection, vehicle-cloud collaboration BibRef

Prashanthi, M., Mohan, M.C.[M. Chandra],
Hybrid Optimization-Based Neural Network Classifier for Software Defect Prediction,
IJIG(24), No. 4, July 2024, pp. 2450045.
DOI Link 2408
BibRef

Shumovskaia, V.[Valentina], Kayaalp, M.[Mert], Sayed, A.H.[Ali H.],
Detection of Malicious Agents in Social Learning,
SPLetters(31), 2024, pp. 1745-1749.
IEEE DOI 2408
Signal processing algorithms, Bayes methods, Vectors, Topology, Convergence, Testing, Network topology, Social learning, malicious agent BibRef

Lavanya, V., Sekhar, P.C.[P. Chandra],
Efficient Cybersecurity Model Using Wavelet Deep CNN and Enhanced Rain Optimization Algorithm,
IJIG(24), No. 4, July 2024, pp. 2450048.
DOI Link 2408
BibRef

Kong, X.Y.[Xiang-Yu], Yang, G.H.[Guang-Hong],
Anti-Watermarking Stealthy Deception Attacks Against Networked Unmanned Surface Vehicles,
ITS(25), No. 9, September 2024, pp. 12835-12840.
IEEE DOI 2409
Watermarking, Detectors, Wireless networks, System performance, State estimation, Intelligent transportation systems, Uplink, auxiliary estimator BibRef

Darabi, B.[Boshra], Bag-Mohammadi, M.[Mozafar], Karami, M.[Mojtaba],
A micro Reinforcement Learning architecture for Intrusion Detection Systems,
PRL(185), 2024, pp. 81-86.
Elsevier DOI Code:
WWW Link. 2410
Intrusion detection, Reinforcement learning, Deep Q-network, NSL-KDD, CIC-IDS2018, UNSW-NB15 BibRef

Yan, P.[Pei], Tan, S.Q.[Shun-Quan], Wang, M.[Miaohui], Huang, J.W.[Ji-Wu],
Enhanced Dynamic Analysis for Malware Detection With Gradient Attack,
SPLetters(31), 2024, pp. 2825-2829.
IEEE DOI 2410
Malware, Training, Noise, Feature extraction, Application programming interfaces, Perturbation methods, network security BibRef

He, X.F.[Xiao-Fei], Li, L.X.[Li-Xiang], Peng, H.P.[Hai-Peng], Tong, F.H.[Feng-Hua],
An Efficient Image Privacy Preservation Scheme for Smart City Applications Using Compressive Sensing and Multi-Level Encryption,
ITS(25), No. 10, October 2024, pp. 14958-14972.
IEEE DOI 2410
Encryption, Security, Protection, Image reconstruction, Data privacy, Smart cities, Privacy, Compressive sensing, data hiding, image data processing BibRef

Prathibha, L., Fatima, K.[Kaleem],
A Novel High-Speed Data Encryption Scheme for Internet of Medical Things Using Modified Elliptic Curve Diffie-Hellman and Advance Encryption Standard,
IJIG(24), No. 5, September 2024, pp. 2340004.
DOI Link 2410
BibRef

Cai, X.[Xiao], Shi, K.[Kaibo], Sun, Y.[Yanbin], Cao, J.[Jinde], Kwon, O.M.[Oh-Min], Qiao, C.[Cheng], Tian, Z.H.[Zhi-Hong],
Design of Intelligent Control Under Machine Learning Supervision and Signal Compression Mechanism Design for NCSs Under DoS Attacks,
ITS(25), No. 10, October 2024, pp. 15116-15121.
IEEE DOI 2410
Stability criteria, Power system stability, Bandwidth, Sun, Quality of service, Protocols, machine learning BibRef

Qi, W.H.[Wen-Hai], Yin, H.[Huaichao], Park, J.H.[Ju H.], Wu, Z.G.[Zheng-Guang], Yan, H.C.[Huai-Cheng],
Intelligent Finite-Time Protocol-Based Stabilization for Networked UMV Systems With DoS Attacks,
ITS(25), No. 11, November 2024, pp. 16734-16744.
IEEE DOI 2411
Protocols, Jamming, Stability analysis, Marine vehicles, Control systems, Vectors, Transient analysis, finite-time boundedness BibRef

Gao, D.[Demin], Ou, L.Y.[Li-Yuan], Liu, Y.[Ye], Yang, Q.[Qing], Wang, H.G.[Hong-Gang],
DeepSpoof: Deep Reinforcement Learning-Based Spoofing Attack in Cross-Technology Multimedia Communication,
MultMed(26), 2024, pp. 10879-10891.
IEEE DOI 2411
Wireless fidelity, Zigbee, Wireless communication, Communication system security, Security, spoofing attack BibRef

Yu, W.[Wei], Huang, D.Q.[De-Qing], Wang, X.L.[Xiao-Lei], Xu, K.[Kai],
Recovery-Based Distributed Adaptive ILC With Fading Compensation for MHSTs Under DoS Attacks: A Model-Free Approach,
ITS(25), No. 12, December 2024, pp. 20535-20546.
IEEE DOI 2412
Fading channels, Resistance, Security, Asymptotic stability, Adaptation models, Topology, Resists, Event detection, Cyberattack, denial-of-service attacks BibRef

Rege, A., Obradovic, Z., Asadi, N., Parker, E., Pandit, R., Masceri, N., Singer, B.,
Predicting Adversarial Cyber-Intrusion Stages Using Autoregressive Neural Networks,
IEEE_Int_Sys(33), No. 2, March 2018, pp. 29-39.
IEEE DOI 1806
Biological neural networks, Computer crime, Mathematical model, Predictive models, Time series analysis, Training, ARIMA, NARX, time series analysis BibRef

Liu, G.[Guowei], Tian, E.[Engang], Zhao, X.[Xia], Chen, H.[Huwei],
Critical-Area-Based Stochastic DoS Attack Strategy Design Against Remote State Estimation in Multi-Area Power Systems,
SPLetters(32), 2025, pp. 291-295.
IEEE DOI 2501
Denial-of-service attack, Power systems, State estimation, Topology, Stochastic processes, Power system stability, Vectors, remote state estimation BibRef

Jin, Z.W.[Zeng-Wang], Ma, M.[Menglu], Wang, Z.[Zhen], Sun, C.Y.[Chang-Yin],
Optimal Transmission Schedule With Privacy Preservation for Cyber-Physical System Against Eavesdropping Attack,
SPLetters(32), 2025, pp. 436-440.
IEEE DOI 2501
Noise, State estimation, Optimal scheduling, Eavesdropping, Accuracy, Schedules, Estimation error, Steady-state, Job shop scheduling, state estimation BibRef

Pan, X.D.[Xu-Dong], Zhang, M.[Mi], Yan, Y.F.[Yi-Fan], Zhang, S.Y.[Sheng-Yao], Yang, M.[Min],
Matryoshka: Exploiting the Over-Parametrization of Deep Learning Models for Covert Data Transmission,
PAMI(47), No. 2, February 2025, pp. 663-678.
IEEE DOI 2501
Novel insider attack called Matryoshka to reveal the possibility of breaking the privacy of machine learning data. Data models, Training, Predictive models, Training data, Computational modeling, Task analysis, Data privacy, AI security BibRef

Huan, S.[Sha], Zhang, X.Y.[Xiao-Yi], Shang, W.L.[Wen-Li], Cao, H.T.[Hai-Tao], Li, H.[Heng], Yang, Y.[Yuanjia], Liu, W.[Wenbai],
T-Shaped CAN Feature Integration With Lightweight Deep Learning Model for In-Vehicle Network Intrusion Detection,
ITS(25), No. 12, December 2024, pp. 21183-21196.
IEEE DOI 2412
Intrusion detection, Deep learning, Feature extraction, Entropy, Security, Intelligent vehicles, Safety, Floods, deep learning (DL) BibRef

Zheng, G.[Guhan], Ni, Q.[Qiang], Lu, Y.[Yang],
Privacy-Aware Anomaly Detection and Notification Enhancement for VANET Based on Collaborative Intrusion Detection System,
ITS(25), No. 12, December 2024, pp. 21172-21182.
IEEE DOI 2412
Vehicular ad hoc networks, Intrusion detection, Privacy, Blockchains, Roads, Games, Trust management, Nash equilibrium, Nash equilibrium BibRef

Berqia, A.[Amine], Bouijij, H.[Habiba], Merimi, A.[Ahmed], Ouaggane, A.[Abdellah],
Detecting DDoS Attacks using Machine Learning in IoT Environment,
ISCV24(1-8)
IEEE DOI 2408
Logistic regression, Machine learning algorithms, Accuracy, Artificial neural networks, Nearest neighbor methods, DDoS Attacks BibRef

Hsu, T.C.[Tse-Chuan], Lu, H.S.[Han-Sheng],
Designing a Secure and Scalable Service Model Using Blockchain and MQTT for IoT Devices,
IoTDesign24(645-653)
IEEE DOI 2404
Performance evaluation, Protocols, Public key, Computer architecture, Broadcasting, Encryption BibRef

Kannan, B.B.[B. Bharathi], Sriramulu, S.[Srinivasan],
Hybrid Convolutional Neural Networks To Create An Attack Detection Framework For A Wireless Sensor Network Based Health Care Application,
ICCVMI23(1-5)
IEEE DOI 2403
Dimensionality reduction, Deep learning, Wireless sensor networks, Energy consumption, Telemedicine, Gray hole attack BibRef

Tang, F.[Fei], Yu, B.Y.[Bo-Yang], Zhao, S.X.[Shi-Xiang], Xu, M.[MeiMei],
Towards Fraudulent URL Classification with Large Language Model based on Deep Learning,
CVIDL23(503-507)
IEEE DOI 2403
Uniform resource locators, Deep learning, Adaptation models, Analytical models, Natural languages, Robustness, Fraud, Fraudulent URL Classification BibRef

Benchadi, D.Y.M.[Djafer Yahia Messaoud], Batalo, B.[Bojan], Fukui, K.[Kazuhiro],
Malware Detection Using Kernel Constrained Subspace Method,
MVA23(1-5)
DOI Link 2403
Visualization, Machine vision, Malware, Real-time systems, Computational efficiency, Kernel, Standards BibRef

Dong, Q.[Qian], Sun, T.T.[Ting-Ting], Li, T.W.[Ting-Wei], Lu, X.Q.[Xiao-Qian], Yan, K.[Kai],
Anomaly Intrusion Detection in Online Learning Space Based on XGBoost,
ICIVC22(968-973)
IEEE DOI 2301
Machine learning algorithms, Supervised learning, Neural networks, Intrusion detection, Telecommunication traffic, anomaly intrusion detection BibRef

Li, S.S.[Shan-Shan], Chen, D.[Deng], Zhang, J.[Jun], Wang, H.Y.[Hao-Yu], Li, L.[Lei], Qian, Y.Y.[Yu-Yang], Liu, H.[Hailun],
Software Vulnerability Detection Based on Anomaly-Attention,
ICRVC22(261-265)
IEEE DOI 2301
Source coding, Computational modeling, Transformers, Dynamic scheduling, Software, Data models, Timing, correlation differences BibRef

Wang, S.W.[Shu-Wei], Wang, Q.Y.[Qiu-Yun], Jiang, Z.W.[Zheng-Wei], Wang, X.[Xuren], Jing, R.Q.[Rong-Qi],
A Weak Coupling of Semi-Supervised Learning with Generative Adversarial Networks for Malware Classification,
ICPR21(3775-3782)
IEEE DOI 2105
Couplings, Technological innovation, Neural networks, Semisupervised learning, Generative adversarial networks, Classification BibRef

Qi, P.P.[Pan-Pan], Zhang, Z.Q.[Zhao-Qi], Wang, W.[Wei], Yao, C.[Chang],
Malware Detection by Exploiting Deep Learning over Binary Programs,
ICPR21(9068-9075)
IEEE DOI 2105
Deep learning, Analytical models, Computer hacking, Feature extraction, Malware, Data models BibRef

di Rocco, L.[Lorenzo], Petrillo, U.F.[Umberto Ferraro], Palini, F.[Francesco],
Large Scale Graph Based Network Forensics Analysis,
IWBDAF20(457-469).
Springer DOI 2103
BibRef

Scalas, M.[Michele], Rieck, K.[Konrad], Giacinto, G.[Giorgio],
Explanation-driven Characterization of Android Ransomware,
EDL-AI20(228-242).
Springer DOI 2103
BibRef

Chen, L.[Lin], Qiu, H.J.[Hui-Jun], Kuang, X.Y.[Xiao-Yun], Xu, A.D.[Ai-Dong], Yang, Y.W.[Yi-Wei],
Intelligent Data Security Threat Discovery Model Based on Grid Data,
ICIVC21(458-463)
IEEE DOI 2112
Training, Data analysis, Data security, Transfer learning, Process control, Reinforcement learning, Data models, smart grid BibRef

Ikrissi, G., Mazri, T.,
IoT-based Smart Environments: State of the Art, Security Threats and Solutions,
SmartCityApp21(279-286).
DOI Link 2201
BibRef

Niu, L., Song, Y., Chu, J., Li, S.,
Analysis of the Attacker and Defender GAN Models for the Indoor Navigation Network,
ISPRS21(B4-2021: 237-242).
DOI Link 2201
BibRef

Toka, K.O., Dikilitas, Y., Oktay, T., Sayar, A.,
Securing Iot With Blockchain,
SmartCityApp21(529-532).
DOI Link 2201
BibRef

Özarpa, C., Avci, I., Kinaci, B.F., Arapoglu, S., Kara, S.A.,
Cyber Attacks on Scada Based Traffic Light Control Systems in the Smart Cities,
SmartCityApp21(411-415).
DOI Link 2201
BibRef

Moulad, L., Chaabita, R., Balar, K.,
Wireless Sensor Network: Towards An Improvement of Security Policy,
SmartCityApp21(379-383).
DOI Link 2201
BibRef

Miryahyaie, S., Ebrahimpour-komleh, H., Nickfarjam, A.M.,
ACO-based Intrusion Detection Method in Computer Networks using Fuzzy Association Rules,
IPRIA21(1-5)
IEEE DOI 2201
Ant colony optimization, Image analysis, Urban areas, Intrusion detection, Computer networks, Computer Network BibRef

Mohseni, M.[Mahsa], Tanha, J.[Jafar],
A Density-based Undersampling Approach to Intrusion Detection,
IPRIA21(1-7)
IEEE DOI 2201
Radio frequency, Machine learning algorithms, Intrusion detection, Clustering algorithms, undersampling BibRef

Liu, Y.G.[Ying-Gang], Ning, Z.[Zhenhu], Zhang, J.J.[Jiang-Jiang], Wang, X.P.[Xiao-Ping],
Monitory Consensus Mechanism of Blockchain for Internet of Things,
ICIVC21(425-430)
IEEE DOI 2112
Fault tolerance, Scalability, Fault tolerant systems, Stability analysis, Computer crashes, Blockchains BibRef

Chen, L., Xian, M., Liu, J.,
Monitoring System of OpenStack Cloud Platform Based on Prometheus,
CVIDL20(206-209)
IEEE DOI 2102
cloud computing, public domain software, Prometheus, open source cloud platform, grafana BibRef

Prima, B., Bouhorma, M.,
Using Transfer Learning for Malware Classification,
SmartCityApp20(343-349).
DOI Link 2012
BibRef

El-Bakkouri, N., Mazri, T.,
Security Threats In Smart Healthcare,
SmartCityApp20(209-214).
DOI Link 2012
BibRef

Maryem, M., Abdelghani, E.O., Belkassem, T.,
Routing in Wireless Sensor Networks using Fuzzy Logic: A survey,
ISCV20(1-6)
IEEE DOI 2011
energy conservation, energy consumption, fuzzy logic, routing protocols, telecommunication power management, Fuzzy Logic BibRef

Mennour, H.[Hanene], Mostefai, S.[Sihem],
A hybrid Deep Learning Strategy for an Anomaly Based N-IDS,
ISCV20(1-6)
IEEE DOI 2011
Network traffic data. computer network security, feedforward neural nets, optimisation, pattern classification, supervised learning, Anomaly-based IDS BibRef

Sebbah, A., Kadri, B.,
A Privacy and Authentication Scheme for IoT Environments Using ECC and Fuzzy Extractor,
ISCV20(1-5)
IEEE DOI 2011
cryptography, data privacy, Internet of Things, message authentication, smart cards, smart card, Privacy. BibRef

Bouzoubaa, K., Taher, Y., Nsiri, B.,
DOS attack forecasting: A comparative study on wrapper feature selection,
ISCV20(1-7)
IEEE DOI 2011
computer network security, feature selection, genetic algorithms, Internet, learning (artificial intelligence), Feature Selection BibRef

Yang, Z.L.[Zhong-Liang], Hu, Y.T.[Yu-Ting], Huang, Y.F.[Yong-Feng], Zhang, Y.J.[Yu-Jin],
Behavioral Security in Covert Communication Systems,
IWDW19(377-392).
Springer DOI 2003
BibRef

Varenne, R.[Remi], Delorme, J.M.[Jean Michel], Plebani, E.[Emanuele], Pau, D.[Danilo], Tomaselli, V.[Valeria],
Intelligent Recognition of TCP Intrusions for Embedded Micro-controllers,
NTIAP19(361-373).
Springer DOI 1909
BibRef

Zhang, H., Wu, C.Q., Gao, S., Wang, Z., Xu, Y., Liu, Y.,
An Effective Deep Learning Based Scheme for Network Intrusion Detection,
ICPR18(682-687)
IEEE DOI 1812
Feature extraction, Intrusion detection, Engines, Training, Noise reduction, Hidden Markov models, deep learning BibRef

Lu, J., Lv, F., Liu, Q., Zhang, M., Zhang, X.,
Botnet Detection based on Fuzzy Association Rules,
ICPR18(578-584)
IEEE DOI 1812
Botnet, Feature extraction, Protocols, Servers, Security, Computers, Network security, botnet detection, fuzzy association BibRef

Lyons, J.B.[Joseph B.], Roebke, M.A.[Mark A.], Bobko, P.[Philip], Cox, C.A.[Craig A.],
Cyber Vulnerability: An Attentional Dilemma,
VAMR18(II: 331-340).
Springer DOI 1807
BibRef

Matthews, G.[Gerald], Panganiban, A.R.[April Rose], Bailey, R.[Rachel], Lin, J.C.[Jin-Chao],
Trust in Autonomous Systems for Threat Analysis: A Simulation Methodology,
VAMR18(II: 341-353).
Springer DOI 1807
BibRef

Samtani, S., Yu, S., Zhu, H., Patton, M., Matherly, J., Chen, H.,
Identifying SCADA Systems and Their Vulnerabilities on the Internet of Things: A Text-Mining Approach,
IEEE_Int_Sys(33), No. 2, March 2018, pp. 63-73.
IEEE DOI 1806
Anomaly detection, Automation, Computer security, Data mining, Object recognition, Ports (Computers), SCADA systems, vulnerability assessment BibRef

Menemencioglu, O., Orak, I.M.,
Geographical Assesment of Results From Preventing the Parameter Tampering in A Web Application,
GeoAdvances17(69-71).
DOI Link 1805
Malicious inputs to web resources. BibRef

Herrera-Semenets, V.[Vitali], Pérez-García, O.A.[Osvaldo Andrés], Gago-Alonso, A.[Andrés], Hernández-León, R.[Raudel],
A Novel Hybrid Data Reduction Strategy and Its Application to Intrusion Detection,
CIARP17(289-297).
Springer DOI 1802
BibRef

Mohan, R.[Ram], Chaudhury, S.[Santanu], Lall, B.[Brejesh],
Incremental Learning of Non-stationary Temporal Causal Networks for Telecommunication Domain,
PReMI17(501-508).
Springer DOI 1711
BibRef

Elejla, O.E.[Omar E.], Belaton, B.[Bahari], Anbar, M.[Mohammed], Alijla, B.O.[Basem O.],
IPv6 OS Fingerprinting Methods: Review,
IVIC17(661-668).
Springer DOI 1711
BibRef

Zabri, Z.[Zahidan], Nohuddin, P.N.E.[Puteri N. E.],
Analyzing and Detecting Network Intrusion Behavior Using Packet Capture,
IVIC17(750-761).
Springer DOI 1711
BibRef

Zyad, E., Khalid, C., Mohammed, B.,
Combination of R1-PCA and median LDA for anomaly network detection,
ISCV17(1-5)
IEEE DOI 1710
reduction dimension algorithms, zero day attacks, Anomaly detection, Computer crime, Intrusion detection, Principal component analysis, Robustness, Training, KDDcup99, LDA, BibRef