On the public citation graph

Anomaly Detection in IaaS Clouds

https://doi.org/10.1109/cloudcom.2013.57

0 signed · 43 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-10665-1_56openalex-snapshot

Cloud Infrastructure & Applications – CloudIA

inferredcites →https://doi.org/10.1016/0893-6080(95)90002-0openalex-snapshot

Neural networks for pattern recognition

inferredcites →https://doi.org/10.1109/glocom.2011.6134532openalex-snapshot

Performance Metric Selection for Autonomic Anomaly Detection on Cloud Computing Systems

inferredcites →https://doi.org/10.1109/isise.2012.13openalex-snapshot

Design of the Network Traffic Anomaly Detection System in Cloud Computing Environment

inferredcites →https://doi.org/10.1109/noms.2010.5488443openalex-snapshot

Online detection of utility cloud anomalies using metric distributions

inferredcites →https://doi.org/10.1109/services.2012.12openalex-snapshot

Validating Cloud Infrastructure Changes by Cloud Audits

inferredcites →https://doi.org/10.1109/srds.2012.3openalex-snapshot

AAD: Adaptive Anomaly Detection System for Cloud Computing Infrastructures

inferredcites →https://doi.org/10.1145/2245276.2232005openalex-snapshot

A security analysis of amazon's elastic compute cloud service

inferredcites →https://doi.org/10.1145/2398776.2398778openalex-snapshot

Analysis of a "/0" stealth scan from a botnet

inferredcites →https://doi.org/10.1186/2192-113x-1-9openalex-snapshot

An agent based business aware incident detection system for cloud environments

inferredcites →https://doi.org/10.5860/choice.31-5500openalex-snapshot

Neural networks for pattern recognition

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/cpe.4169openalex-snapshot

On the effectiveness of isolation‐based anomaly detection in cloud data centers

inferred← citeshttps://doi.org/10.1002/cpe.6646openalex-snapshot

Intrusion detection systems in the cloud computing: A comprehensive and deep literature review

inferred← citeshttps://doi.org/10.1007/978-3-031-23690-7_10openalex-snapshot

Detecting Cloud Originated DDoS Attacks at the Source Using Out-Cloud Attack Detection (OCAD)

inferred← citeshttps://doi.org/10.1007/978-3-319-29814-6_27openalex-snapshot

Leveraging Static Probe Instrumentation for VM-based Anomaly Detection System

inferred← citeshttps://doi.org/10.1007/978-3-319-62594-2_7openalex-snapshot

Detecting Anomaly in Cloud Platforms Using a Wavelet-Based Framework

inferred← citeshttps://doi.org/10.1007/978-981-99-3250-4_42openalex-snapshot

Anomaly Detection Using Machine Learning Techniques: A Systematic Review

inferred← citeshttps://doi.org/10.1016/j.future.2018.05.014openalex-snapshot

Detecting performance anomalies in scientific workflows using hierarchical temporal memory

inferred← citeshttps://doi.org/10.1109/access.2020.2980522openalex-snapshot

Meet the Sherlock Holmes’ of Side Channel Leakage: A Survey of Cache SCA Detection Techniques

inferred← citeshttps://doi.org/10.1109/access.2021.3083060openalex-snapshot

Machine Learning for Anomaly Detection: A Systematic Review

inferred← citeshttps://doi.org/10.1109/ares.2015.72openalex-snapshot

Towards Abuse Detection and Prevention in IaaS Cloud Computing

inferred← citeshttps://doi.org/10.1109/bigdata47090.2019.9005653openalex-snapshot

RAMP: Real-Time Anomaly Detection in Scientific Workflows

inferred← citeshttps://doi.org/10.1109/cloudcom.2014.165openalex-snapshot

Reflecting on Whether Checklists Can Tick the Box for Cloud Security

inferred← citeshttps://doi.org/10.1109/cloudcom.2014.93openalex-snapshot

On Analyzing Elasticity Relationships of Cloud Services

inferred← citeshttps://doi.org/10.1109/cloudnet51028.2020.9335812openalex-snapshot

Quantifying Cloud Misbehavior

inferred← citeshttps://doi.org/10.1109/cloudtech.2016.7847681openalex-snapshot

SOMBA - automated anomaly detection for Cloud quality of service

inferred← citeshttps://doi.org/10.1109/cscloud.2016.51openalex-snapshot

Sequence-Based Analysis of Static Probe Instrumentation Data for a VMM-Based Anomaly Detection System

inferred← citeshttps://doi.org/10.1109/icdmw60847.2023.00157openalex-snapshot

Exploring Large Language Models for Low-Resource IT Information Extraction

inferred← citeshttps://doi.org/10.1109/icengtechnol.2017.8308189openalex-snapshot

Enterprise security and privacy: Why adding IoT and big data makes it so much more difficult

inferred← citeshttps://doi.org/10.1109/iconstem.2019.8918909openalex-snapshot

To Detect Malware attacks for an Autonomic Self-Heal Approach of Virtual Machines in Cloud Computing

inferred← citeshttps://doi.org/10.1109/mascots.2016.14openalex-snapshot

A Platform for Run-Time Health Verification of Elastic Cyber-Physical Systems

inferred← citeshttps://doi.org/10.1109/ucc.2014.48openalex-snapshot

AMAD: Resource Consumption Profile-Aware Attack Detection in IaaS Cloud

inferred← citeshttps://doi.org/10.1145/3442536.3442550openalex-snapshot

A Systematic Review on Anomaly Detection for Cloud Computing Environments

inferred← citeshttps://doi.org/10.1155/2022/4255220openalex-snapshot

Implementation of Block‐Level Double Encryption Based on Machine Learning Techniques for Attack Detection and Prevention

inferred← citeshttps://doi.org/10.11648/j.net.20180601.11openalex-snapshot

Identifying the Top Threats in Cloud Computing and Its Suggested Solutions: A Survey

inferred← citeshttps://doi.org/10.1186/s12984-024-01322-zopenalex-snapshot

Intelligent systems for sitting posture monitoring and anomaly detection: an overview

inferred← citeshttps://doi.org/10.14257/ijgdc.2015.8.6.27openalex-snapshot

A Data Transmission Model based on Adaptive Periodic Push Strategy for IaaS Cloud Computing Platforms

inferred← citeshttps://doi.org/10.4018/978-1-4666-8225-2.ch003openalex-snapshot

Anomaly Detection in Cloud Environments

inferred← citeshttps://doi.org/10.4018/978-1-5225-8176-5.ch006openalex-snapshot

Anomaly Detection in Cloud Environments

inferred← citeshttps://doi.org/10.48550/arxiv.2101.06054openalex-snapshot

Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper

inferred← citeshttps://doi.org/10.5220/0005913701060117openalex-snapshot

A Wavelet-inspired Anomaly Detection Framework for Cloud Platforms

inferred← citeshttps://doi.org/10.5220/0006305500001535openalex-snapshot

Anomaly Detection for Soft Security in Cloud based Auditing of Accounting Systems

inferred← citeshttps://doi.org/10.70675/f4d33b0azf0daz4285z83b6z83477b3610aaopenalex-snapshot

Software-based Detection and Mitigation of Microarchitectural Attacks on Intel’s x86 Architecture

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.