Biblio

Collaborative filtering (CF) recommender system has been widely used for its well performing in personalized recommendation, but CF recommender system is vulnerable to shilling attacks in which shilling attack profiles are injected into the system by attackers to affect recommendations. Design robust recommender system and propose attack detection methods are the main research direction to handle shilling attacks, among which unsupervised PCA is particularly effective in experiment, but if we have no information about the number of shilling attack profiles, the unsupervised PCA will be suffered. In this paper, a new unsupervised detection method which combine PCA and data complexity has been proposed to detect shilling attacks. In the proposed method, PCA is used to select suspected attack profiles, and data complexity is used to pick out the authentic profiles from suspected attack profiles. Compared with the traditional PCA, the proposed method could perform well and there is no need to determine the number of shilling attack profiles in advance.

Feature extraction and feature selection are the first tasks in pre-processing of input logs in order to detect cybersecurity threats and attacks by utilizing data mining techniques in the field of Artificial Intelligence. When it comes to the analysis of heterogeneous data derived from different sources, these tasks are found to be time-consuming and difficult to be managed efficiently. In this paper, we present an approach for handling feature extraction and feature selection utilizing machine learning algorithms for security analytics of heterogeneous data derived from different network sensors. The approach is implemented in Apache Spark, using its python API, named pyspark.

Radio Frequency Identification (RFID) systems are widely used today because of their low price, usability and being wireless. As RFID systems use wireless communication, they may encounter challenging security problems. Several lightweight encryption algorithms have been proposed so far to solve these problems. The RBS block cipher is one of these algorithms. In designing RBS, conventional block cipher elements such as S-box and P-box are not used. RBS is based on inserting redundant bits between altered plaintext bits using an encryption key Kenc. In this paper, considering not having a proper diffusion as the main defect of RBS, we propose a chosen ciphertext attack against this algorithm. The data complexity of this attack equals to N pairs of text and its time complexity equals to N decryptions, where N is the size of the encryption key Kenc.