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ICITDA 2026: International Conference on Information Technology and Digital Applications

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Submission Date:
2026-08-15
Notification Date:
2026-09-15
Conference Date:
2026-11-09
Location:
Lombok, Indonesia
Years:
Viewed: 8458   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

50.2 / 100
Ranked #1,565 of 5,693 conferences · Top 28%
Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
67
Community attention (10%)
10
Public record completeness (15%)
55

Inputs used: Editions on record: 11 · Researchers who opened this page in the past 24 months: 3

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-10-04

Call For Papers

ICITDA 2026 (International Conference on Information Technology and Digital Applications) is an academic conference held in Lombok, Indonesia on 2026-11-09. The paper submission deadline is 2026-08-15. Acceptance notifications are sent on 2026-09-15.

Main Topic “From Data to Defense: Advancing Cybersecurity Through Intelligence and Automation” The rapid digital transformation across industries has led to an unprecedented growth in data generation, interconnected systems, and cloud-based infrastructures. While this evolution enhances operational efficiency and innovation, it simultaneously expands the attack surface for cyber threats. Organizations today face increasingly sophisticated adversaries who exploit vulnerabilities using automation, artificial intelligence, and coordinated attack strategies. Traditional rule-based and reactive cybersecurity approaches are no longer sufficient to cope with the scale, speed, and complexity of modern cyberattacks. One of the primary challenges in contemporary cybersecurity lies in managing and interpreting massive volumes of heterogeneous data generated by networks, endpoints, applications, and users. Security teams are often overwhelmed by alerts, resulting in delayed responses, alert fatigue, and missed critical incidents. Furthermore, advanced persistent threats (APTs), zero-day vulnerabilities, ransomware campaigns, and supply-chain attacks require adaptive and intelligence-driven defense mechanisms rather than static security controls. The central issue, therefore, is how to transform raw security data into actionable intelligence that supports proactive and automated defense strategies. This transformation requires the integration of data analytics, machine learning, threat intelligence platforms, and security orchestration tools. By leveraging intelligent systems, organizations can identify anomalies, predict potential attack vectors, prioritize risks, and automate incident response processes in real time. Several research directions emerge from this theme. First, the development of scalable data-driven threat detection models using artificial intelligence and deep learning remains a critical area of investigation. Research may focus on improving detection accuracy, reducing false positives, and enhancing model interpretability. Second, the design of automated security orchestration and response frameworks (SOAR) can significantly reduce response time and operational costs. Third, integrating cyber threat intelligence sharing mechanisms across organizations while preserving privacy and compliance presents both technical and regulatory challenges. Finally, adaptive defense architectures—such as zero trust models and autonomous security systems—offer promising avenues for building resilient cyber infrastructures. In conclusion, advancing cybersecurity through intelligence and automation is not merely a technological enhancement but a strategic necessity. By converting data into defensive capabilities, researchers and practitioners can move toward predictive, autonomous, and resilient security ecosystems capable of confronting the evolving cyber threat landscape. The theme emphasizes how data analytics, threat intelligence, artificial intelligence, and machine learning can be leveraged to detect, predict, and mitigate cyber threats in real time. It highlights the integration of security intelligence platforms, automated incident response, behavioral analytics, and adaptive defense architectures to strengthen resilience across networks, cloud systems, and critical infrastructures. About Conference Tracks and Topics Artificial Intelligence Big Data Causal Modeling Cloud Computing Computer Graphics and Multimedia Computer Networks Computer Vision Databases Data Science Deep Learning Digital Forensics and Security Educational Technology Human Computer Interaction Information Systems Information Theory Intelligent System Internet of Things (IoT) Machine Learning Medical Informatics Pattern Recognition Soft Computing Software Systems Text Analytics Wireless Communication
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