Towards an Enhancement of Organizational Information Security through Threat Factor Profiling (TFP) Model

Sidi, Fatimah; Daud, Maslina; Ahmad, Sabariah; Zainuddin, Naqliyah; Abdullah, Syafiqa Anneisa; Jabar, Marzanah A.; Affendey, Lilly Suriani; Ishak, Iskandar; Sharef, Nurfadhlina Mohd; Zolkepli, Maslina; Nordin, Fatin Nur Majdina; Sejani, Hashimah Amat; Hairani, Saiful Ramadzan

doi:10.1088/1742-6596/892/1/012011

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…The review methodology is consistent with the work conducted by [45]. Therefore, prior studies that showed systematic review or systematic mapping approaches are applied with minor differences [51][52][53][54][55][56][57]; however, there are overlapping phases or processes, such as the identification of studies, selection, quality assessment, data extraction, and data synthesis [51,52,[58][59][60][61][62][63][64]. For example, reference [54] splits the selection phase into the development of inclusion or exclusion criteria and selected studies for inclusion and exclusion criteria.…”

Section: Methodsmentioning

confidence: 99%

How Advanced Technological Approaches Are Reshaping Sustainable Social Media Crisis Management and Communication: A Systematic Review

et al. 2022

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The end goal of technological advancement used in crisis response and recovery is to prevent, reduce or mitigate the impact of a crisis, thereby enhancing sustainable recovery. Advanced technological approaches such as social media, machine learning (ML), social network analysis (SNA), and big data are vital to a sustainable crisis management decisions and communication. This study selects 28 articles via a systematic process that focuses on ML, SNA, and related technological tools to understand how these tools are shaping crisis management and decision making. The analysis shows the significance of these tools in advancing sustainable crisis management to support decision making, information management, communication, collaboration and cooperation, location-based services, community resilience, situational awareness, and social position. Moreover, the findings noted that managing diverse outreach information and communication is increasingly essential. In addition, the study indicates why big data and language, cross-platform support, and dataset lacking are emerging concerns for sustainable crisis management. Finally, the study contributes to how advanced technological solutions effectively affect crisis response, communication, decision making, and overall crisis management.

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Section: Methodsmentioning

confidence: 99%

How Advanced Technological Approaches Are Reshaping Sustainable Social Media Crisis Management and Communication: A Systematic Review

et al. 2022

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“…Our previous works on threat factor profiling [3], [4] has been focusing on the sources integration, fuzzifying the threat severity, computing asset (ATL) and organisational (OTL) based threat level and developing model to predict the ATL and OTL. Presentation and visualization of the results are in multiple granularities such as hourly, daily, weekly, and so on.…”

Section: Network Threats Severity Predictionmentioning

confidence: 99%

“…Our previous and similar efforts [3]- [7] were tested data within different time series from the ones highlighted in this work. This paper is also distinguished by addressing the temporal trend analysis pattern mining.…”

Section: Introductionmentioning

confidence: 99%

Temporal Trends Analysis for Dengue Outbreak and Network Threats Severity Prediction Accuracy Improvement

Sharef¹,

Husin²,

Kasmiran³

et al. 2019

Journal of Digital Information Management

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Time series analysis is one of the major techniques in capturing trends and pattern of the occurrence for future forecasting. Existing but scarce works have developed temporal-based techniques which target to either predict movement (increase or decrease) or quantify the possibility of the predicted event to happen. Many of these techniques focus on the values of the time series attribute but there is no available work on dengue or intrusion logs that focus on temporal trend analysis-based on temporal relations mining. In this work the proposed technique utilize the temporal trends analysis of the observational attributes towards the pattern of the target's attribute values. In this work, we propose a new temporal trends analysis approach that uses temporal relation mining in forecasting dengue outbreak and cyber intrusion.We leverage the temporal abstractions and temporal logic to define patterns with the goal to optimize prediction accuracy. From the experiment conducted, the results showed that the proposed approach has better prediction as compared to the baseline.

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“…[9], [10] Degree of RA is determined by probability and impact [11] and its status is separated into 5 degrees (higher, high, middle, low and lower). [12] There are several RA standards, that is ISO/IEC TR 13335:1998, AS/NZS 4360:2004, [13]BSI standard 100-3:2005, FAIR, ISACA, COBIT 5, ISF IRAM, ISO/IEC 3100:2009 and 27005:2011 [14], MAGERIT, NIST special publication 800-30, OCTAVE Allegro and risk safety, etc. and framework, the RA, is ISO 270002 standard, COBIT, NIST SP800-53, etc.…”

Section: Introductionmentioning

confidence: 99%

A Real-time Risk Assessment for Information System with CICIDS2017 Dataset Using Machine Learning

Pangsuban¹,

Nilsook²,

Wannapiroon³

2020

IJMLC

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The purpose of this research was to study the concept and architectural design for Risk Assessment (RA) for information system with the Canadian Institute for Cybersecurity Intrusion Detection Systems 2017 dataset (CICIDS2017 dataset) using Machine Learning (ML) to establish a model. It evaluated the risk on detected network data. The results indicated, the concept consisted of input such as CICIDS2017 dataset, ML, network data and risk matrix. Information system real time RA using CICIDS2017 dataset and ML were processes and the RA on the system were outcomes. In addition, the concept components were improved upon and comprised of four sections; 1) network data capture for network data collection, 2) CICIDS2017 that was intrusion dataset for establishment of a predictive model with ML algorithm, 3) classification predictive model, forecasted on intrusion from network data and 4) RA report, estimated risk of information in risk matrix format. Finally, architectural design, consists of three major parts which includes; network data capture, risk predictive analysis and RA report.

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Towards an Enhancement of Organizational Information Security through Threat Factor Profiling (TFP) Model

Cited by 4 publications

References 9 publications

How Advanced Technological Approaches Are Reshaping Sustainable Social Media Crisis Management and Communication: A Systematic Review

How Advanced Technological Approaches Are Reshaping Sustainable Social Media Crisis Management and Communication: A Systematic Review

Temporal Trends Analysis for Dengue Outbreak and Network Threats Severity Prediction Accuracy Improvement

A Real-time Risk Assessment for Information System with CICIDS2017 Dataset Using Machine Learning

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