1CP_RT_J032 Intrusion Detection and Prevention in Web Servers

ABSTRACT:

Cloud security is one of most important issues that have attracted a lot of research and development effort in past few years. Particularly, attackers can explore vulnerabilities of a cloud system and compromise virtual machines to deploy further large-scale Distributed Denial-of-Service (DDoS). DDoS attacks usually involve early stage actions such as multi-step exploitation, low frequency vulnerability scanning, and compromising identified vulnerable virtual machines as zombies, and finally DDoS attacks through the compromised zombies. Within the cloud system, especially the Infrastructure-as-a-Service (IaaS) clouds, the detection of zombie exploration attacks is extremely difficult. This is because cloud users may install vulnerable applications on their virtual machines. To prevent vulnerable virtual machines from being compromised in the cloud, we propose a multi-phase distributed vulnerability detection, measurement, and countermeasure selection mechanism called NICE, which is built on attack graph based analytical models and reconfigurable virtual network-based countermeasures. The proposed framework leverages Open Flow network programming APIs to build a monitor and control plane over distributed programmable virtual switches in order to significantly improve attack detection and mitigate attack consequences. The system and security evaluations demonstrate the efficiency and effectiveness of the proposed solution.

AIM

            The main aim of this project is to prevent the vulnerable virtual machines from being compromised in the cloud server using multi-phase distributed vulnerability detection, measurement, and countermeasure selection mechanism called NICE.

SYNOPSIS

          In recent studies have shown that users migrating to the cloud consider security as the most important factor. A recent Cloud Security Alliance (CSA) survey shows that among all security issues, abuse and nefarious use of cloud computing is considered as the top security threat, in which attackers can exploit vulnerabilities in clouds and utilize cloud system resources to deploy attacks. In traditional data centers, where system administrators have full control over the host machines, vulnerabilities can be detected and patched by the system administrator in a centralized manner. However, patching known security holes in cloud data centers, where cloud users usually have the privilege to control software installed on their managed VMs, may not work effectively and can violate the Service Level Agreement (SLA). Furthermore, cloud users can install vulnerable software on their VMs, which essentially contributes to loopholes in cloud security. The challenge is to establish an effective vulnerability/attack detection and response system for accurately identifying attacks and minimizing the impact of security breach to cloud users.

 In a cloud system where the infra-structure is shared by potentially millions of users, abuse and nefarious use of the shared infrastructure benefits attackers to exploit vulnerabilities of the cloud and use its resource to deploy attacks in more efficient ways. Such attacks are more effective in the cloud environment since cloud users usually share computing resources, e.g., being connected through the same switch, sharing with the same data storage and file systems, even with potential attackers.

EXISTING SYSTEM:

Cloud users can install vulnerable software on their VMs, which essentially contributes to loopholes in cloud security. The challenge is to establish an effective vulnerability/attack detection and response system for accurately identifying attacks and minimizing the impact of security breach to cloud users. In a cloud system where the infrastructure is shared by potentially millions of users, abuse and nefarious use of the shared infrastructure benefits attackers to exploit vulnerabilities of the cloud and use its resource to deploy attacks in more efficient ways. Such attacks are more effective in the cloud environment since cloud users usually share computing resources, e.g., being connected through the same switch, sharing with the same data storage and file systems, even with potential attackers. The similar setup for VMs in the cloud, e.g., virtualization techniques, VM OS, installed vulnerable software, networking, etc., attracts attackers to compromise multiple VMs.

DISADVANTAGES OF EXISTING SYSTEM:

1.     No detection and prevention framework in a virtual networking environment.

2.     Not accuracy in the attack detection from attackers.

PROPOSED SYSTEM:

In this article, we propose NICE (Network Intrusion detection and Countermeasure selection in virtual network systems) to establish a defense-in-depth intrusion detection framework. For better attack detection, NICE incorporates attack graph analytical procedures into the intrusion detection processes. We must note that the design of NICE does not intend to improve any of the existing intrusion detection algorithms; indeed, NICE employs a reconfigurable virtual networking approach to detect and counter the attempts to compromise VMs, thus preventing zombie VMs.

ADVANTAGES OF PROPOSED SYSTEM:

The contributions of NICE are presented as follows:

Ø We devise NICE, a new multi-phase distributed network intrusion detection and prevention framework in a virtual networking environment that captures and inspects suspicious cloud traffic without interrupting users’ applications and cloud services.

Ø  NICE incorporates a software switching solution to quarantine and inspect suspicious VMs for further investigation and protection. Through programmable network approaches, NICE can improve the attack detection probability and improve the resiliency to VM exploitation attack without interrupting existing normal cloud services.

Ø  NICE employs a novel attack graph approach for attack detection and prevention by correlating attack behavior and also suggests effective countermeasures.

Ø NICE optimizes the implementation on cloud servers to minimize resource consumption. Our study shows that NICE consumes less computational overhead compared to proxy-based network intrusion detection solutions.

ALGORITHM USED:

Alert Correlation Algorithm

          Countermeasure Selection Algorithm

MODULES:

] Nice-A

] VM Profiling

] Attack Analyzer

] Network Controller

MODULES DESCRIPTION:

Nice-A

          The NICE-A is a Network-based Intrusion Detection System (NIDS) agent installed in each cloud server. It scans the traffic going through the bridges that control all the traffic among VMs and in/out from the physical cloud servers. It will sniff a mirroring port on each virtual bridge in the Open vSwitch. Each bridge forms an isolated subnet in the virtual network and connects to all related VMs. The traffic generated from the VMs on the mirrored software bridge will be mirrored to a specific port on a specific bridge using SPAN, RSPAN, or ERSPAN methods. It’s more efficient to scan the traffic in cloud server since all traffic in the cloud server needs go through it; however our design is independent to the installed VM. The false alarm rate could be reduced through our architecture design.

VM Profiling

          Virtual machines in the cloud can be profiled to get precise information about their state, services running, open ports, etc. One major factor that counts towards a VM profile is its connectivity with other VMs. Also required is the knowledge of services running on a VM so as to verify the authenticity of alerts pertaining to that VM. An attacker can use port scanning program to perform an intense examination of the network to look for open ports on any VM. So information about any open ports on a VM and the history of opened ports plays a significant role in determining how vulnerable the VM is. All these factors combined will form the VM profile. VM profiles are maintained in a database and contain comprehensive information about vulnerabilities, alert and traffic.

Attack Analyzer

          The major functions of NICE system are performed by attack analyzer, which includes procedures such as attack graph construction and update, alert correlation and countermeasure selection. The process of constructing and utilizing the Scenario Attack Graph (SAG) consists of three phases: information gathering, attack graph construction, and potential exploit path analysis. With this information, attack paths can be modeled using SAG. The Attack Analyzer also handles alert correlation and analysis operations. This component has two major functions: (1) constructs Alert Correlation Graph (ACG), (2) provides threat information and appropriate countermeasures to network controller for virtual network reconfiguration. NICE attack graph is constructed based on the following information: Cloud system information, Virtual network topology and configuration information, Vulnerability information

Network Controller

          The network controller is a key component to support the programmable networking capability to realize the virtual network reconfiguration. In NICE, we integrated the control functions for both OVS and OFS into the network controller that allows the cloud system to set security/filtering rules in an integrated and comprehensive manner. The network controller is responsible for collecting network information of current Open Flow network and provides input to the attack analyzer to construct attack graphs. In NICE, the network control also consults with the attack analyzer for the flow access control by setting up the filtering rules on the corresponding OVS and OFS. Network controller is also responsible for applying the countermeasure from attack analyzer. Based on VM Security Index and severity of an alert, countermeasures are selected by NICE and executed by the network controller.

SYSTEM CONFIGURATION:-

HARDWARE CONFIGURATION:-

ü Processor             -        Pentium –IV

ü Speed                   -        1.1 Ghz

ü RAM                    -        256 MB(min)

ü Hard Disk            -        20 GB

ü Key Board            -        Standard Windows Keyboard

ü Mouse                  -        Two or Three Button Mouse

ü Monitor                -        SVGA

SOFTWARE CONFIGURATION:-

Operating System                    : Windows XP

Programming Language           : JAVA/J2EE

 Java Version                           : JDK 1.6 & above.

CONTACT US

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