云安全新挑战：CIDS——云端入侵检测系统的创新框架

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"基于云的入侵检测系统（CIDS）：应对云环境安全挑战的新框架" 随着云计算的普及，其便利性和成本效益吸引了大量企业和个人使用，但同时也带来了数据安全的顾虑。云计算环境中，由于其分布式和动态特性，攻击者可以通过伪装合法用户来滥用丰富的资源，这使得传统的入侵检测系统（IDS）在保护云环境中的数据安全方面存在局限性。CIDS（Cloud-based Intrusion Detection System）正是为了解决这些问题而提出的一种创新模型。 CIDS框架的核心目标是设计一个可扩展、弹性的系统，能够在没有中央协调者的环境下有效检测和应对各种入侵威胁。其架构设计的关键要素包括： 1. **组件划分**：CIDS由多个模块组成，如数据收集模块、分析模块、警报生成模块和管理员通知模块。这些模块协同工作，确保全面的安全监控。 2. **检测模型**：CIDS采用了先进的机器学习和行为分析技术，能够实时监控用户活动，识别异常模式，以区分正常操作和潜在攻击行为。它可能包括基于签名的检测方法（已知攻击模式），以及基于行为的检测（通过用户行为模式进行分析）。 3. **警报处理**：不同于传统IDS，CIDS还包含一个智能警报汇总和管理组件。它能自动分析大量的警报信息，将相似或无关紧要的警报合并，减少误报，并向云管理员提供关键的、经过筛选的警报，提高响应效率。 4. **可扩展性和弹性**：CIDS架构设计考虑到了云计算的动态特性，可以根据需求自动调整资源，适应不断变化的威胁环境。这使得系统在面对大规模用户和流量时仍能保持高效运作。 5. **安全性与隐私**：CIDS注重保护用户的隐私，采用加密技术和最小权限原则，确保即使在分布式环境中，敏感数据也得到充分保护。关键词：云计算、安全、入侵检测、伪装攻击、数据保护。总结来说，CIDS作为一种基于云的入侵检测解决方案，通过其独特的架构和智能警报管理，不仅弥补了现有IDS在云环境中的不足，而且提供了更高效、安全的数据保护措施。随着云计算的发展，CIDS有望成为未来保障云服务安全的重要工具。

CIDS: A framework for Intrusion Detection in Cloud Systems

Hisham A. Kholidy

Dipartimento di Informatica

Università di Pisa, Pisa, Italy

hkholidy@di.unipi.it, hisham_dev@yahoo.com

Fabrizio Baiardi

Dipartimento di Informatica

Università di Pisa, Pisa, Italy

baiardi@di.unipi.it

Abstract

By impersonating legitimate users, intruders can use the

abundant resources of cloud computing environments.

This paper develops a framework for "CIDS" a cloud

based intrusion detection system, to solve the deficiencies

of current IDSs. CIDS also provides a component to

summarize the alerts and inform the cloud administrator.

CIDS architecture is scalable and elastic with no central

coordinator. This paper describes the components,

architecture, detection models, and advantages of CIDS.

Key Words: cloud computing, security, intrusion

detection, attacks, masquerade.

1. Introduction

Cloud computing has a broad appeal because it

enables IT managers to provision services to users faster

and in a cost-effective way. However, it does raise some

concerns and chief among them is securing data in the

cloud because of their operational models, the enabling

technologies, and their distributed nature, clouds are easy

targets for intruders. While intrusions can be handled by

an Intrusion Detection System (IDS) [1], current IDSs

have many deficiencies which hinder their adoption in a

cloud environment. This paper describes CIDS, a

framework for a C

loud based Intrusion Detection System

to deal with attacks like: (1) Masquerade attacks: where

threats impersonate legitimate users, (2) Host-based

attacks: these can be a consequence of masquerade attacks

and generally result in an observable user behavior

anomaly and (3) Network-based attacks. CIDS

also

summarizes the intensive network based IDS alerts

according to the attack signature and target. Section 2

briefly introduces a cloud security and the seven known

top threats to cloud computing systems. Then, it classifies

vulnerabilities of the cloud computing paradigm. The next

section surveys the related works. Section 4 describes the

components, architecture, detection models, and

advantages of our CIDS framework. Section 5 outlines

future work.

2. Cloud computing security

Threats of cloud computing systems differ from those

of traditional IT solutions. CSA (Cloud Security

Alliance)[2] ranks seven threats that apply across cloud

computing SPI models [3]: (1) Abuse and nefarious use of

cloud computing, (2) Insecure interfaces and APIs, (3)

Malicious insiders, (4) Shared technology issues, (5) Data

loss or leakage, (6) Account or service hijacking, (7)

Unknown risk profile. [4] defines seven risks a user

should raise before committing: (1) Sensitive data should

be processed outside the enterprise only with the

assurance that they are only accessible and propagated to

privileged users, (2) One customer data should be fully

segregated from those of another customer, (3) A

customer needs to verify if the infrastructure complies

with some regulatory security requirements, (4) The cloud

provider should commit to store and process data in

specific jurisdictions and obey local privacy requirements

on behalf of the customer who do not know where data is

stored, (5) The cloud provider should offer replication and

disaster recovery mechanisms, (6) Investigative support

needs to be ensured, (7) Data should be accessible even

when the provider is acquired by another company or if

the user moves to another provider.

3. Related work

IDSs may be classified according to the source of data

into: (1) Host-based IDS (HIDS), where sensors that

detect an intrusion are focused on a single host. (2)

Network-based IDS (NIDS), where sensors are focused

on a network segment. (3) Distributed IDS (DIDS) which

integrates both types of sensors, DIDS can be categorized

as Mobile Agent IDS (MAIDS), Grid based IDS (GIDS),

and recently Cloud based

IDS. Traditional NIDS and

HIDS cannot identify suspicious activities in a cloud

environment. As an example, a NIDS can not detect an

attack anytime node communication is encrypted. Attacks

can also be invisible to HIDS, because they may not leave

traces in the node operating system where the IDS resides.

Since in clouds, distinct users share computing and

communication resources, attacks may be originated from

and be directed against several resources within the cloud

infrastructure. Hence, only a distributed strategy may be

appropriate. The adoption of DIDS solutions [5] is still

challenging in cloud computing because the complex

architecture of the infrastructure and the distinct kinds of

users lead to different requirements and possibilities for

being secured. Some of these IDSs are scalable but they

have the problem of single point of failure as most

2012 Ninth International Conference on Information Technology- New Generations

DOI 10.1109/ITNG.2012.94

379

2012 Ninth International Conference on Information Technology - New Generations

DOI 10.1109/ITNG.2012.94

379

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