[Book Publication - Springer Nature, Switzerland]

  • BOOK Title: "Context-Aware Machine Learning and Mobile Data Analytics: Automated Rule-based Services with Intelligent Decision Making".
    Authors: Iqbal H. Sarker, A. Colman, J. Han, P. Watters
    Number of Chapters: 10
    Publication Details: Springer Nature, Switzerland.
    BOOK Access Link: (https://link.springer.com/book/10.1007/978-3-030-88530-4).

    [*** This book mainly covers data-driven and machine learning algorithm design with experimental analysis towards transparent and explainable user behavior modeling in the broad area of AI and data science. This includes time-series data clustering, tree-based modeling, knowledge and rule mining, data-driven decision-making, recency mining, etc. highlighting real-world applications and research issues ***]
  • BOOK Title: "AI-Driven Cybersecurity and Threat Intelligence: Cyber Automation, Intelligent Decision-Making and Explainability".
    Author: Iqbal H. Sarker
    Number of Chapters: 10
    Publication Details: Springer Nature, Switzerland.
    BOOK Access Link: (https://link.springer.com/book/10.1007/978-3-031-54497-2).

    [*** This book covers a comprehensive guideline and potentiality of AI/XAI based modeling for cybersecurity. This includes machine learning and deep learning modeling, data science modeling, knowledge mining, generative AI and language modeling, etc. highlighting real-world applications and research issues ***]

[Scientific Journals - Top Ranked/Indexing/Publishers]

  • Iqbal H. Sarker, Helge Janicke, Alsharif Abuadbba, Mohamed Amine Ferrag (2024). Multi-Aspect Rule-Based AI: Methods, Taxonomy, Challenges and Directions toward Automation, Intelligence and Transparent Cybersecurity Modeling for Critical Infrastructures. Journal: Internet of Things, Netherlands. Elsevier (WoS, Q1, IF=5.9, CiteScore =14.2)
  • Iqbal H. Sarker, Helge Janicke, Ahmad Mohsin , Asif Gill, Leandros Maglaras (2024). Explainable AI for cybersecurity automation, intelligence and trustworthiness in digital twin: Methods, taxonomy, challenges and prospects. Journal: ICT Express, South Korea. Elsevier (WoS, Q1, IF=5.4, CiteScore =10.4)
  • Iqbal H. Sarker et al. (2020). ABC-RuleMiner: User behavioral rule-based machine learning method for context-aware intelligent services, Journal of Network and Computer Applications, USA. Elsevier (Q1, WoS, CiteScore: 19, IF: 8.7)
  • Iqbal H. Sarker (2021). CyberLearning: Effectiveness analysis of machine learning security modeling to detect cyber-anomalies and multi-attacks. Journal: Internet of Things, Netherlands. Elsevier (WoS, Q1, IF=5.9, CiteScore =14.2)
  • Iqbal H. Sarker et al. (2020). Cybersecurity Data Science: An Overview from Machine Learning Perspective, Journal of Big Data, UK. Springer Nature (Q1, WoS, IF: 10.84)
  • Iqbal H. Sarker, Alan Colman and Jun Han (2019). RecencyMiner: Mining Recency-based Personalized Behavior from Contextual Smartphone Data, Journal of Big Data, UK. Springer Nature (Q1, WoS, IF: 10.84)
  • Iqbal H. Sarker et al. (2022). Smart City Data Science: Towards Data-Driven Smart Cities with Open Research Issues, Journal: Internet of Things, Netherlands. Elsevier (WoS, Q1, IF=5.9, CiteScore =14.2)
  • Iqbal H. Sarker et al. (2019) A Machine Learning based Robust Prediction Model for Real-Life Mobile Phone Data, Journal: Internet of Things, Netherlands. Elsevier (WoS, Q1, IF=5.9, CiteScore =14.2)
  • Iqbal H. Sarker, A. Kayes, P. Watters (2019). Effectiveness Analysis of Machine Learning Classification Models for Predicting Personalized Context-Aware Smartphone Usage, Journal of Big Data, UK. Springer Nature (Q1, WoS, IF: 10.84)
  • Iqbal H. Sarker , Alan Colman, MA Kabir and Jun Han (2017). Individualized Time-Series Segmentation for Mining Mobile Phone User Behavior. The Computer Journal, Section C: Computational Intelligence, Machine Learning and Data Analytics, Publisher: Oxford University Press, British Computer Society, UK (WoS, IF: 1.76) [A Pioneer Journal in Computer Science [1958 - now]]
  • Iqbal H. Sarker (2019). Context-Aware Rule Learning from Smartphone Data: Survey, Challenges and Future Directions, Journal of Big Data, UK. Springer Nature (Q1, WoS, IF: 10.84)
  • Iqbal H. Sarker et al. (2019). BehavDT: A Behavioral Decision Tree Learning to Build User-Centric Context-Aware Predictive Model, Journal: Mobile Networks and Applications, Netherlands. Springer Nature (Q1, WoS, IF:3.07)
  • Iqbal H. Sarker et al. (2022). Internet of Things (IoT) Security Intelligence: A Comprehensive Overview, Machine Learning Solutions and Research Directions, Journal: Mobile Networks and Applications, Netherlands. Springer Nature (Q1, WoS, IF:3.07)
  • Iqbal H. Sarker, Alan Colman, Jun Han, A. Kayes and P. Watters (2019). CalBehav: A Machine Learning based Personalized Calendar Behavioral Model using Time-Series Smartphone Data. The Computer Journal, Section C: Computational Intelligence, Machine Learning and Data Analytics, Publisher: Oxford University Press, British Computer Society, UK (WoS, IF:1.76) [A Pioneer Journal in Computer Science [1958 - now]]
  • Iqbal H. Sarker et al. (2020). Mobile Data Science and Intelligent Apps: Concepts, AI-based Modeling, and Research Directions. Journal: Mobile Networks and Applications, Netherlands. Springer Nature (WoS, IF:3.4)
  • Iqbal H. Sarker (2022). Machine Learning for Intelligent Data Analysis and Automation in Cybersecurity: Current and Future Prospects. Journal: Annals of Data Science, Springer Nature, Germany.
  • N. Islam, T. Tinan, Iqbal H. Sarker et al. (2021). A Systematic Review on the Use of AI and ML for Fighting the COVID-19 Pandemic, Journal: IEEE Transactions on Artificial Intelligence, IEEE Transactions
  • MR Hossain, MM Hoque, MAA Dewan, N Siddique, N Islam, Iqbal H. Sarker, (2021). Authorship Classification in a Resource Constraint Language using Convolutional Neural Networks. Journal: IEEE Access, IEEE, USA (WoS, Q1, IF:3.74)
  • BC Das, MM Anwar, MA Moni, Iqbal H. Sarker, (2021). Attribute Driven Temporal Active Online Community Search. Journal: IEEE Access, IEEE, USA (WoS, Q1, IF:3.74)
  • R. Ripan, Iqbal H. Sarker, (2022). Effectively predicting cyber-attacks through isolation forest learning-based outlier detection. Journal: Security and Privacy, Wiley.
  • S. Gupta, Iqbal H. Sarker, (2022). Modeling Hybrid Feature-Based Phishing Websites Detection using Machine Learning Techniques. Journal: Annals of Data Science, Springer Nature, Germany.
  • R Hossain, M Hoque, N Siddiki, Iqbal H. Sarker, (2021). Bengali Text Document Categorization based on Very Deep Convolution Neural Network. Journal - Expert Systems with Applications - Elsevier (WoS, Q1, IF:8.67, CiteScore = 12.7)
  • B. Hossain , S. Arefin, Iqbal H. Sarker, (2022). CARAN: A Context-Aware Recency Based Attention Network for Point-of-interest Recommendation. Journal: IEEE Access, IEEE, USA (WoS, Q1, IF:3.74)
  • S. Gomasta, M. Anwar, Iqbal H. Sarker et al. (2022). Query-oriented Topical Influential Users Detection for Top-k Trending Topics in Twitter. Journal: Applied Intelligence, Netherlands. Springer Nature (WoS, IF:5.08)
  • A. Khan, F. Alsolami, Y. Abushark, Iqbal H. Sarker et al. (2022). Novel energy management scheme in IoT enabled smart irrigation system using optimized intelligence methods. Journal: Engineering Applications of Artificial Intelligence, UK. Elsevier (WoS, Q1, IF:7.80)
  • GM Sakhawat Hossain, Kaushik Deb, Helge Janicke, Iqbal H. Sarker, (2024). PDF Malware Detection: Towards Machine Learning Modeling with Explainability Analysis. Journal: IEEE Access, IEEE, USA (WoS, Q1, IF:3.74)

[Top Ranked Conference Proceedings and Book Chapters]

  • Iqbal H. Sarker, Flora Salim (2018). Mining User Behavioral Rules from Smartphone Data through Association Analysis, PAKDD 2018, Melbourne, Australia. Book: Advances in Knowledge Discovery and Data Mining, Lecture Notes in Computer Science (LNCS), Springer (Scopus, DBLP, Core Rank: A)
  • Iqbal H. Sarker, MA Kabir, Alan Colman and Jun Han (2017). An Improved Naive Bayes Classifier-based Noise Detection Technique for Classifying User Phone Call Behavior, AusDM 2017, Melbourne, Australia. Book: Data Mining, Springer (Scopus, DBLP, Core Rank: Australasian)
  • Iqbal H. Sarker et al. (2018). BehavMiner: Mining User Behaviors from Mobile Phone Data for Personalized Services, Ph.D. Forum, 16th IEEE International Conference on Pervasive Computing and Communications (PerCom 2018), Athens, Greece. IEEE (Scopus, DBLP, Core Rank: A*)
  • Iqbal H. Sarker, MA Kabir, Alan Colman and Jun Han (2017). Identifying Recent Behavioral Data Length in Mobile Phone Log, 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous 2017), Melbourne, Australia. ACM (Scopus, DBLP, Core Rank: A)
  • Iqbal H. Sarker, MA Kabir, Alan Colman and Jun Han (2017). Designing Architecture of a Rule-based System for Managing Phone Call Interruptions, Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the (UbiComp 2017), HI, USA. ACM (Scopus, DBLP, Core Rank: A*)
  • Iqbal H. Sarker, MA Kabir, Alan Colman and Jun Han (2017). Understanding Recency-Based Behavior Model for Individual Mobile Phone Users, Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers (UbiComp 2017), HI, USA. ACM (Scopus, DBLP, Core Rank: A*)
  • Iqbal H. Sarker, MA Kabir, Alan Colman and Jun Han (2017). An Effective Call Prediction Model Based on Noisy Mobile Phone Data, ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2017), HI, USA. ACM (Scopus, DBLP, Core Rank: A*)
  • Iqbal H. Sarker, MA Kabir, Alan Colman and Jun Han (2017). An Approach to Modeling Call Response Behavior on Mobile Phones Based on Multi-dimensional Contexts, Proceedings: IEEE/ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft@ICSE 2017), Buenos Aires, Argentina. IEEE/ACM (Scopus, DBLP)
  • Iqbal H. Sarker, MA Kabir, Alan Colman and Jun Han (2016). Predicting how you respond to phone calls: Towards discovering temporal behavioral rules, ACM Australian Conference on Computer-Human Interaction (OzCHI 2016), Tasmania, Australia. ACM (Scopus, DBLP, Core Rank: Australasian)
  • Iqbal H. Sarker, Alan Colman, MA Kabir and Jun Han (2016). Behavior-oriented time segmentation for mining individualized rules of mobile phone users, IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA 2016), Montreal, Canada. IEEE (Scopus, DBLP, Core Rank: A)
  • Iqbal H. Sarker, MA Kabir, Alan Colman and Jun Han (2016). Evidence-based behavioral model for calendar schedules of individual mobile phone user, IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA 2016), Montreal, Canada. IEEE (Scopus, DBLP, Core Rank: A)
  • Iqbal H. Sarker, Alan Colman, MA Kabir and Jun Han (2016) Understanding individuals phone call behavior for calendar events, ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (UbiComp 2016), Heidelberg, Germany. ACM (Scopus, DBLP, Core Rank: A*)
  • Iqbal H. Sarker, Alan Colman, MA Kabir and Jun Han (2016). Phone call log as a context source to modeling individual user behavior, ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (UbiComp 2016), Heidelberg, Germany. ACM (Scopus, DBLP, Core Rank: A*)

[International Ph.D. Forum]

  • Iqbal H. Sarker et al. (2018). BehavMiner: Mining User Behaviors from Mobile Phone Data for Personalized Services, Ph.D. Forum, 16th IEEE International Conference on Pervasive Computing and Communications (PerCom 2018), Athens, Greece. IEEE (Scopus, DBLP, Core Rank: A*)

[Position Paper]

  • Iqbal H. Sarker, Janicke, H., Nazeeruddin, M., Watters, P., Nepal, S. (2023). AI Potentiality and Awareness: A Position Paper from the Perspective of Human-AI Teaming in Cybersecurity. Lecture Notes in Networks and Systems, Springer Nature, Switzerland.
  • Iqbal H. Sarker, Janicke, H., Maglaras, L., & Camtepe, S. (2023). Data-Driven Intelligence can Revolutionize Today's Cybersecurity World: A Position Paper. Communications in Computer and Information Science, Springer Nature, Switzerland.
  • Iqbal H. Sarker (2024). LLM Potentiality and Awareness: A Position Paper from the Perspective of Trustworthy and Responsible AI Modeling. Journal: Discover Artificial Intelligence, Springer Nature, Switzerland.

[Full publication list (100+) by Sarker et al. can be found/read through-]:

(IF/Ranking may vary year to year)
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