相关论文: Watchword-Oriented and Time-Stamped Algorithms for…
Low latency and high availability of an app or a web service are key, amongst other factors, to the overall user experience (which in turn directly impacts the bottomline). Exogenic and/or endogenic factors often give rise to breakouts in…
In this paper, we investigate how we can leverage Spark platform for efficiently processing provenance queries on large volumes of workflow provenance data. We focus on processing provenance queries at attribute-value level which is the…
Nowadays, the rapid increases of the scale and complexity of the controlled plants bring new challenges such as computing power and storage for conventional control systems. Cloud computing is concerned as a powerful solution to handle the…
Cloud services have become an essential infrastructure for enterprises and individuals. Access to these cloud services is typically governed by Identity and Access Management systems, where user authentication often relies on passwords.…
Effective provenance tracking enhances reproducibility, governance, and data quality in array workflows. However, significant challenges arise in capturing this provenance, including: (1) rapidly evolving APIs, (2) diverse operation types,…
The interconnection of resource-constrained and globally accessible things with untrusted and unreliable Internet make them vulnerable to attacks including data forging, false data injection, and packet drop that affects applications with…
Provenance management must be present to enhance the overall security and reliability of long-tail microscopy (LTM) data management systems. However, there are challenges in provenance for domains with LTM data. The provenance data need to…
Modern cyber attackers use advanced zero-day exploits, highly targeted spear phishing, and other social engineering techniques to gain access and also use evasion techniques to maintain a prolonged presence within the victim network while…
This paper presents the development and implementation of a cloud detection algorithm for Proba-V. Accurate and automatic detection of clouds in satellite scenes is a key issue for a wide range of remote sensing applications. With no…
In the face of large-scale automated social engineering attacks to large online services, fast detection and remediation of compromised accounts are crucial to limit the spread of new attacks and to mitigate the overall damage to users,…
Reliability is extremely important for large-scale cloud systems like Microsoft 365. Cloud failures such as disk failure, node failure, etc. threaten service reliability, resulting in online service interruptions and economic loss. Existing…
This paper presents various automatic detection methods to extract so called tortured phrases from scientific papers. These tortured phrases, e.g. flag to clamor instead of signal to noise, are the results of paraphrasing tools used to…
While Endpoint Detection and Response (EDR) are able to efficiently monitor threats by comparing static rules to the event stream, their inability to incorporate past system context leads to high rates of false alarms. Recent work has…
Software bugs in cloud management systems often cause erratic behavior, hindering detection, and recovery of failures. As a consequence, the failures are not timely detected and notified, and can silently propagate through the system. To…
The increasing deployment of deep neural networks (DNNs) in cyber-physical systems (CPS) enhances perception fidelity, but imposes substantial computational demands on execution platforms, posing challenges to real-time control deadlines.…
This paper addresses the challenges of complex dependencies and diverse anomaly patterns in cloud service environments by proposing a dependency modeling and anomaly detection method that integrates contrastive learning. The method…
Detecting encryption-driven cyber threats remains a large challenge due to the evolving techniques employed to evade traditional detection mechanisms. An entropy-based computational framework was introduced to analyze multi-domain system…
Multimodal large language models increasingly solve vision-centric tasks by calling external tools for visual inspection, OCR, retrieval, calculation, and multi-step reasoning. Current tool-using agents usually expose the executed tool…
Recently, point clouds have been widely used in computer vision, whereas their collection is time-consuming and expensive. As such, point cloud datasets are the valuable intellectual property of their owners and deserve protection. To…
Limitations of CAP theorem imply that if availability is desired in the presence of network partitions, one must sacrifice sequential consistency, a consistency model that is more natural for system design. We focus on the problem of what a…