Workload characterization: A survey revisited
Workload characterization is a well-established discipline that plays a key role in many
performance engineering studies. The large-scale social behavior inherent in the …
performance engineering studies. The large-scale social behavior inherent in the …
Detection of malicious social bots: A survey and a refined taxonomy
M Latah - Expert Systems with Applications, 2020 - Elsevier
Social bots represent a new generation of bots that make use of online social networks
(OSNs) as command and control (C&C) channels. Malicious social bots have been used as …
(OSNs) as command and control (C&C) channels. Malicious social bots have been used as …
Big data: A survey
In this paper, we review the background and state-of-the-art of big data. We first introduce
the general background of big data and review related technologies, such as could …
the general background of big data and review related technologies, such as could …
Toward scalable systems for big data analytics: A technology tutorial
Recent technological advancements have led to a deluge of data from distinctive domains
(eg, health care and scientific sensors, user-generated data, Internet and financial …
(eg, health care and scientific sensors, user-generated data, Internet and financial …
Generating synthetic decentralized social graphs with local differential privacy
A large amount of valuable information resides in decentralized social graphs, where no
entity has access to the complete graph structure. Instead, each user maintains locally a …
entity has access to the complete graph structure. Instead, each user maintains locally a …
{AttriGuard}: A practical defense against attribute inference attacks via adversarial machine learning
Users in various web and mobile applications are vulnerable to attribute inference attacks, in
which an attacker leverages a machine learning classifier to infer a target user's private …
which an attacker leverages a machine learning classifier to infer a target user's private …
[PDF][PDF] Dependence makes you vulnberable: Differential privacy under dependent tuples.
C Liu, S Chakraborty, P Mittal - NDSS, 2016 - princeton.edu
Differential privacy (DP) is a widely accepted mathematical framework for protecting data
privacy. Simply stated, it guarantees that the distribution of query results changes only …
privacy. Simply stated, it guarantees that the distribution of query results changes only …
Attacking graph-based classification via manipulating the graph structure
Graph-based classification methods are widely used for security analytics. Roughly
speaking, graph-based classification methods include collective classification and graph …
speaking, graph-based classification methods include collective classification and graph …
Speedup graph processing by graph ordering
The CPU cache performance is one of the key issues to efficiency in database systems. It is
reported that cache miss latency takes a half of the execution time in database systems. To …
reported that cache miss latency takes a half of the execution time in database systems. To …