Client Virtual Machine Research Articles

Study of Immune-Based Intrusion Detection Technology in Virtual Machines for Cloud Computing Environment

Cloud computing platforms are usually based on virtual machines as the underlying architecture; the security of virtual machine systems is the core of cloud computing security. This paper presents an immune-based intrusion detection model in virtual machines of cloud computing environment, denoted as IB-IDS, to ensure the safety of user-level applications in client virtual machines. In the model, system call sequences and their parameters of processes are used, and environment information in the client virtual machines is extracted. Then the model simulates immune responses to ensure the state of user-level programs, which can detect attacks on the dynamic runtime of applications and has high real-time performance. There are five modules in the model: antigen presenting module, signal acquisition module, immune response module, signal measurement module, and information monitoring module, which are distributed into different levels of virtual machine environment. Performance analysis and experimental results show that the model brings a small performance overhead for the virtual machine system and has a good detection performance. It is applicable to judge the state of user-level application in guest virtual machine, and it is feasible to use it to increase the user-level security in software services of cloud computing platform.

Exploring infrastructure support for app-based services on cloud platforms

Major infrastructure-as-a-cloud (IaaS) providers have recently been building marketplaces of “cloud apps,” which are VMs pre-installed with a variety of software stacks. Clients of cloud computing leverage such markets by downloading and instantiating the apps that best suit their computing needs, thereby saving the effort needed to configure and build VMs from scratch.We posit that the notion of cloud apps as defined by these marketplaces is nascent and does not allow apps to leverage the benefits of virtual machine (VM) introspection technology developed over the past decade. We envision a marketplace of apps that can interact with client VMs in a rich set of ways to provide a number of services that are currently supported only by cloud providers. This allows clients to deploy services such as VM introspection-based security tools and network middleboxes on their work VMs without requiring the cloud provider to deploy these services on their behalf.This paper presents models to support such a marketplace of expressive cloud apps. We present a study of the design space of these models to understand their performance and deployment tradeoffs. We also consider the design of a permissions-based framework to contain untrusted third-party cloud apps. Finally, we demonstrate the utility of our models by building and evaluating a number of security tools built as cloud apps.

System cum Program-Wide Lightweight Malicious Program Execution Detection Scheme for Cloud

ABSTRACTCloud is prone to a set of well-known network and host-based attacks from cloud insiders, cloud users, and outside attackers. This paper concretely focuses over the detection of malware and program modification-based attacks through identification of malicious program executions and malware at the client virtual machines and hosts in a cloud environment. The paper also focuses on the related techniques for malware detection using system call sequence measures. An immediate system call structure-based program cum system-wide technique is proposed for the detection of anomalous program executions and malwares in the cloud. The algorithm is validated over University of New Mexico sendmail data set. Effective deployment architecture for such an implementation is also presented as a distributed cum centralized intrusion prevention system (IPS). The proposed IPS also solves the problem of individual IPS getting malformed at client virtual machine with the use of both process and system level based detection strategies. The paper provides detailed results and experimentations of the proposed intrusion detection technique on a private cloud with open nebula and virtual box.

Design on Framework for Dynamic Monitoring of Virtual Machines

In order to ensure that the cloud platform client runtime kernel virtual machine security, this paper proposes a new framework for dynamic monitoring of virtual machines, it is for the kernel rootkit attacks, study the cloud client virtual machine operating system kernel safety, presented Hyperchk virtual machine dynamic monitoring framework. This framework mainly for kernel rootkit attacks, ensure that customers running virtual machine kernel security.

Cloud security auditing based on behavioural modelling

Multi-tenancy is one of the most attractive features of cloud computing, which provides significant benefits to both clients and service providers by supporting elastic, efficient and on-demand resource provisioning and allocation. Multi-tenancy also introduces additional security auditing opportunities. Security auditing can be consolidated and offloaded onto a dedicated and well-protected service. The timely prevention of intrusive behaviour and malicious processes using signature-based intrusion detection technologies or system call level anomaly analysis is a very challenging task due to a high rate of false alarms. In this work, a behavioural modelling scheme is proposed to audit the behaviours of client virtual machine and detect suspicious processes on the level of functionality. The proposed scheme can be used as a community security auditing service. The scheme can also be used by cloud providers to offer automatic identification and auditing of the tenant’s services. Our preliminary results have...

Data Firewall: A TPM-based Security Framework for Protecting Data in Thick Client Mobile Environment

Recently, Virtual Desktop Infrastructure (VDI) has been widely adopted to ensure secure protection of enterprise data and provide users with a centrally managed execution environment. However, user experiences may be restricted due to the limited functionalities of thin clients in VDI. If thick client devices like laptops are used, then data leakage may be possible due to malicious software installed in thick client mobile devices. In this paper, we present Data Firewall, a security framework to manage and protect securitysensitive data in thick client mobile devices. Data Firewall consists of three components: Virtual Machine (VM) image management, client VM integrity attestation, and key management for Protected Storage. There are two types of execution VMs managed by Data Firewall: Normal VM and Secure VM. In Normal VM, a user can execute any applications installed in the laptop in the same manner as before. A user can access security-sensitive data only in the Secure VM, for which the integrity should be checked prior to access being granted. All the security-sensitive data are stored in the space called Protected Storage for which the access keys are managed by Data Firewall. Key management and exchange between client and server are handled via Trusted Platform Module (TPM) in the framework. We have analyzed the security characteristics and built a prototype to show the performance overhead of the proposed framework.

Transparent VPN failure recovery with virtualization

Cloud computing is widely used to provide today’s Internet services. Since its service scope is being extended to a wide range of business applications, the security of network communications between clients and clouds are becoming important. Several cloud vendors support virtual private networks (VPNs) for connecting their clouds. Unfortunately, cloud services become unavailable when a VPN failure occurred in a VPN gateway or networks. We propose a transparent VPN failure recovery scheme that can hide VPN failures from users and operating systems (OSs). This scheme transparently recovers from VPN failures by establishing VPN connections in a virtualization layer. When a VPN failure occurs, a client virtual machine monitor (VMM) automatically reconnects to an available VPN gateway which is geographically distributed and connected via leased lines in clouds. IP address changes are hidden from client OSs and servers via a packet relay system implemented by a relay client in the client VMM and a relay server. We implemented a prototype system based on BitVisor, a small client VMM supporting IPsec VPN, and evaluated the prototype system in a wide-area distributed Internet environment in Japan. Experimental results show that our scheme can maintain TCP connections on VPN failures, and performance overhead with the virtualization layer is around 0.6 ms to latency and 8%–30% to throughput.