Security issues and challenges of big data analytics and visualization

Jayasingh, Bipin Bihari; Patra, Manas Ranjan; Mahesh, D Bhanu

doi:10.1109/ic3i.2016.7917961

Cited by 19 publications

(3 citation statements)

References 10 publications

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“…Privacy and security issues are equally important, especially in protecting sensitive customer data from breaches and unauthorised access. E-commerce companies must implement strong data governance practices, encryption, access control and data anonymisation to protect customer privacy and comply with data protection regulations [32], [33]. Addressing these challenges through advanced data management techniques and stringent security measures is critical to leveraging the full potential of big data analytics in demand prediction for ecommerce.…”

Section: Challenges and Opportunities In Big Data Analysis For Demand...mentioning

confidence: 99%

Big Data Analysis for Product Demand Prediction in Indonesian E-commerce

Akadji,

Dewantara

2024

WSIST

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The Indonesian e-commerce sector has witnessed exponential growth in recent years, necessitating effective strategies for predicting product demand to meet consumer expectations and stay competitive. Leveraging big data analytics offers a promising solution to this challenge, allowing businesses to harness vast volumes of data to forecast demand accurately. This research explores the utilization of big data analysis for product demand prediction in Indonesian e-commerce through a qualitative analysis approach. Interviews with e-commerce executives, data scientists, and industry experts revealed key themes, including data quality and integration, analytical techniques and tools, and organizational culture and capability. Results highlight the challenges, opportunities, and best practices associated with leveraging big data analytics for demand prediction in Indonesian e-commerce, providing valuable insights for businesses striving to optimize their predictive capabilities and enhance decision-making processes in this dynamic and rapidly evolving market.

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Section: Challenges and Opportunities In Big Data Analysis For Demand...mentioning

confidence: 99%

Big Data Analysis for Product Demand Prediction in Indonesian E-commerce

Akadji,

Dewantara

2024

WSIST

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“…Association technique is used in a recommender system, in monitoring logs and user profiling in an e-commerce environment. It is used in identifying the similarity between elements and variables of a large dataset [12]. Association rules are also used in retaining confidentiality, for eg.…”

Section: Summary Of Diverse Data Mining and Artificial Intelligence Techniques Used In Early Detection Of Threat Conditionmentioning

confidence: 99%

Cyber Security Threat Intelligence using Data Mining Techniques and Artificial Intelligence

Gupta*¹,

Sabitha²,

Punhani³

2019

IJRTE

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Threat intelligence is the procurement of evidence-based knowledge about current or potential threats. The interest of threat intelligence comprises of advancement in efficiency and boosting effectiveness in terms of analytical and prevention capabilities. Cybersecurity represents serious interest for numerous organizations because maximum of them are using Internet-connected data devices which are opening doors for cyber attackers. Outstanding threat intelligence within the cyber sphere requests for the knowledge base of threat information and a thoughtful way to represent this knowledge. This study proposes a clear rationale of significant artificial intelligence (AI) techniques used for recognizing a cyber-attack. Data analysis can be formulated to guide industries and Internet-connected systems such as smartphones or robotic factories on what to do in the appearance of an incident. AI techniques will analyze past incidents and summarize knowledge from experts and will continue to adapt or reform new branches as it reviews from the new incidents. In addition, various data mining approaches used in boosting threat truthfulness in cybersecurity data are also studied. To conclude, we discussed that; AI will robotize the collation of machine-readable external threats and will improve the efficiency and accuracy of the data for each smart organization’s specific framework.

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“…In terms of security issues, when dealing with integration of data from many sources, security mechanisms should be considered at various levels. It is a major requirement for data scientist to think or analyse on how a development of tools will co-operate with diverse data sets and their security demands [73]. Some of the traditional security mechanisms adopted when using relational database is access control which can be role based or credential based access control and this can feature in authentication, authorization and auditing [74] but these are not enough in the era of big data.…”

Section: Benefit Of This Frameworkmentioning

confidence: 99%

A Theoritical Exploration of Data Management and Integration in Organisation Sectors

Offia¹,

Crowe²

2019

IJDMS

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Big data development is a disturbing issue that will affect enterprise across various sectors. The increase of data volume, high speed of data generation and increasing rate of different data from heterogeneous sources have led to difficulties in data management. This paper first reviews different aspects of big data management, including data integration and traditional data warehouse, and their associated challenges. The problems include increase of redundant data, data accessibility, time consumption in data modelling and data movement from heterogeneous sources into a central database, especially in the big data environment. We then propose a logical data management approach using RESTview technology to integrate and analyse data, without fully adopting traditional ETL processes. Data that for governance, corporate, security or other restriction reasons cannot be copied or moved, can easily be accessed, integrated and analysed, without creating a central repository. Data can be kept in its original form and location, eliminating the movement of data, significantly speeding up the process and allowing for live data interrogation. It may not be the practical solution for every situation but, it is a feasible solution that is comparably cost effective.

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Security issues and challenges of big data analytics and visualization

Cited by 19 publications

References 10 publications

Big Data Analysis for Product Demand Prediction in Indonesian E-commerce

Big Data Analysis for Product Demand Prediction in Indonesian E-commerce

Cyber Security Threat Intelligence using Data Mining Techniques and Artificial Intelligence

A Theoritical Exploration of Data Management and Integration in Organisation Sectors

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