Improving the shilling attack detection in recommender systems using an SVM gaussian mixture model
JM Alostad - Journal of Information & Knowledge Management, 2019 - World Scientific
With recent advances in e-commerce platforms, the information overload has grown due to
increasing number of users, rapid generation of data and items in the recommender system …
increasing number of users, rapid generation of data and items in the recommender system …
Shilling attack detection—a new approach for a trustworthy recommender system
Recommender systems rely on the opinions of many users to predict the preferences of
potential customers. These systems have been broadly used to make quality …
potential customers. These systems have been broadly used to make quality …
A comparative study of shilling attack detectors for recommender systems
Uncovering shilling attackers hidden in recommender systems is very crucial to enhance the
robustness and trustworthiness of product recommendation. Many shilling attack detection …
robustness and trustworthiness of product recommendation. Many shilling attack detection …
An outlier degree shilling attack detection algorithm based on dynamic feature selection
G Cao, H Zhang, J Zheng, L Kuang… - International Journal of …, 2019 - World Scientific
Recommender system is widely used in various fields for dealing with information overload
effectively, and collaborative filtering plays a vital role in the system. However, recommender …
effectively, and collaborative filtering plays a vital role in the system. However, recommender …
An enhanced method for detecting attack in collaborative recommender system
In recent decades, the advent of digital information services by YouTube, Amazon, Netflix,
and many other web services of this kind have made recommendation systems more and …
and many other web services of this kind have made recommendation systems more and …
Shilling attacks detection in recommender systems based on target item analysis
Recommender systems are highly vulnerable to shilling attacks, both by individuals and
groups. Attackers who introduce biased ratings in order to affect recommendations, have …
groups. Attackers who introduce biased ratings in order to affect recommendations, have …
A novel classification‐based shilling attack detection approach for multi‐criteria recommender systems
Recommender systems are emerging techniques guiding individuals with provided referrals
by considering their past rating behaviors. By collecting multi‐criteria preferences …
by considering their past rating behaviors. By collecting multi‐criteria preferences …
A novel shilling attack detection method
Recommender systems provide an impressive way to overcome information overload
problem. However, they are vulnerable to profile injection or shilling attacks. Malicious users …
problem. However, they are vulnerable to profile injection or shilling attacks. Malicious users …
A comparative study on shilling detection methods for trustworthy recommendations
Uncovering shilling attackers hidden in recommender systems is very crucial to enhance the
robustness and trustworthiness of product recommendation. Many shilling attack detection …
robustness and trustworthiness of product recommendation. Many shilling attack detection …
Shilling attack detection in collaborative recommender systems using a meta learning strategy
W Bhebe, OP Kogeda - … on Emerging Trends in Networks and …, 2015 - ieeexplore.ieee.org
Collaborative Recommender Systems suggest items to a user based on other users past
behaviour (items they once bought, viewed or selected and/or ratings they gave to those …
behaviour (items they once bought, viewed or selected and/or ratings they gave to those …