A systematic map** of performance in distributed stream processing systems
Several software systems are built upon stream processing architectures to process large
amounts of data in near real-time. Today's distributed stream processing systems (DSPSs) …
amounts of data in near real-time. Today's distributed stream processing systems (DSPSs) …
Real-time distributed-random-forest-based network intrusion detection system using Apache spark
H Zhang, S Dai, Y Li, W Zhang - 2018 IEEE 37th international …, 2018 - ieeexplore.ieee.org
With the rapid increase in Internet services, network traffic data has become very large and
complex, increasing the possibility of intrusions. The traditional intrusion detection system …
complex, increasing the possibility of intrusions. The traditional intrusion detection system …
SPBench: a framework for creating benchmarks of stream processing applications
In a fast-changing data-driven world, real-time data processing systems are becoming
ubiquitous in everyday applications. The increasing data we produce, such as audio, video …
ubiquitous in everyday applications. The increasing data we produce, such as audio, video …
Smartphone-based outlier detection: a complex event processing approach for driving behavior detection
The majority of fatal car crashes are caused by reckless driving. With the sophistication of
vehicle instrumentation, reckless maneuvers, such as abrupt turns, acceleration, and …
vehicle instrumentation, reckless maneuvers, such as abrupt turns, acceleration, and …
Toward stream-based IP flow analysis
Analyzing IP flows is an essential part of traffic measurement for cyber security. Based on
information from IP flows, it is possible to discover the majority of concurrent cyber threats in …
information from IP flows, it is possible to discover the majority of concurrent cyber threats in …
Data Pipeline System Designs for In-network Learning
This paper introduces the design of a data pipeline system (DPS) integrated with artificial
intelligence (AIF) functions to support continuous AI learning and operations for network …
intelligence (AIF) functions to support continuous AI learning and operations for network …
Namb: A quick and flexible stream processing application prototype generator
The importance of Big Data is nowadays established, both in industry and research fields,
especially stream processing for its capability to analyze continuous data streams and …
especially stream processing for its capability to analyze continuous data streams and …
An intelligent and time-efficient DDoS identification framework for real-time enterprise networks: SAD-F: Spark based anomaly detection framework
Enterprise networks face a large number of threats that are managed and mitigated with a
combination of proprietary and third-party security tools and services. However, the …
combination of proprietary and third-party security tools and services. However, the …
Blockchained adaptive federated auto metalearning BigData and DevOps CyberSecurity Architecture in Industry 4.0
Maximizing the production process in modern industry, as proposed by Industry 4.0, requires
extensive use of Cyber-Physical Systems (CbPS). Artificial intelligence technologies …
extensive use of Cyber-Physical Systems (CbPS). Artificial intelligence technologies …
Normalization of unstructured log data into streams of structured event objects
Monitoring plays a crucial role in the operation of any sizeable distributed IT infrastructure.
Whether it is a university network or cloud datacenter, monitoring information is continuously …
Whether it is a university network or cloud datacenter, monitoring information is continuously …