Udaya Kiran Tupakula

Security as a Service Model for Cloud Environment

Cloud computing is becoming increasingly important for provision of services and storage of data in the Internet. However there are several significant challenges in securing cloud infrastructures from different types of attacks. The focus of this paper is on the security services that a cloud provider can offer as part of its infrastructure to its customers (tenants) to counteract these attacks. Our main contribution is a security architecture that provides a flexible security as a service model that a cloud provider can offer to its tenants and customers of its tenants. Our security as a service model while offering a baseline security to the provider to protect its own cloud infrastructure also provides flexibility to tenants to have additional security functionalities that suit their security requirements. The paper describes the design of the security architecture and discusses how different types of attacks are counteracted by the proposed architecture. We have implemented the security architecture and the paper discusses analysis and performance evaluation results.

Trust and Recommendations in Mobile Ad hoc Networks

Recently several trust and reputation models have been proposed to enhance the security of mobile ad hoc networks. In these models, recommendations are circulated by forwarding explicit messages or introducing extra message headers. Apart from incurring additional overhead, the recommendations are prone to issues such as recommenders bias, honest-elicitation, and free-riding. In this paper, we propose a trust model to enhance the security of mobile ad hoc networks and to address the issues related to recommendations. The model uses only trusted routes for communication, and isolates malicious nodes depending on the evidence collected from direct interactions and recommendations. It deploys a novel approach for communicating recommendations such that they are free from recommenders bias, honest-elicitation, and free-riding. Simulation results confirm the effectiveness of our model.

Intrusion Detection Techniques for Infrastructure as a Service Cloud

Today, cloud computing is one of the increasingly popular technology where the customer can use the resources of the cloud services providers to perform their tasks and only pay for the resources they use. The customer virtual machines in the cloud are vulnerable to different types of attacks. In this paper we propose techniques for securing customer virtual machines from different types of attacks in the Infrastructure as a Service cloud and describe how this can be achieved in practice. Our model enables to differentiate attack traffic originating from each virtual machine even if multiple virtual machines on a VMM are sharing a single IP address.

Trust Enhanced Secure Mobile Ad-Hoc Network Routing

In recent years, several trust and reputation models have been proposed to enhance the security of mobile ad hoc networks. However, they either fail to capture evidence of trustworthiness within the limitations of the network, or introduce additional problems while capturing the evidence. In this paper, we propose a reputation-based trust model known as secure MANET routing with trust intrigue (SMRTI). In our model, the evidence of trustworthiness is captured in an efficient manner and from broader perspectives including direct interactions with neighbours, observing interactions of neighbours and through recommendations. SMRTI captures evidence from direct interactions with neighbours in order to identify their benign and malicious behaviours. It also captures evidence for misbehaviours by observing the interactions of neighbours. Lastly, the evidence captured from recommendations is used to summarize the benign behaviour of multi-hop nodes. Unlike other models, we adopt a novel approach to capture evidence from recommendations, which eliminates recommenders bias, free-riding, and honest- elicitation. SMRTI utilizes the captured evidence to predict whether a node is either benign or misbehaving. It then applies the prediction to enhance the security of communications depending on the decision policies, such as whether to send a packet to or forward a packet on behalf of other nodes. Finally, we demonstrate the performance of our model through simulation results.

Subjective logic based trust model for mobile ad hoc networks

In last five years, several trust models have been proposed to enhance the security of Mobile Ad hoc Networks (MANET). Nevertheless, these trust models fail to express the notion of ignorance during the establishment of trust relationships between mobile nodes. Furthermore, they lack a well-defined approach to defend against the issues resulting from recommendations. In this paper, we propose a novel subjective logic based trust model that enables mobile nodes to explicitly represent and manage ignorance as uncertainty during the establishment of trust relationships with other nodes. Our model defines additional operators to subjective logic in order to address the ignorance introduced between mobile nodes (which have already established trust relationships) as a result of mobility-induced separation. Second, we demonstrate on how mobile nodes formulate their opinions for other nodes based on the evidence collected from the benign and malicious behaviors of those nodes. We then describe on how mobile nodes establish trust relationships with other nodes using the opinions held for those nodes. Depending on the policies defined, these relationships are then used by our model to enhance the security of mobile communications. Third, we propose a novel approach to communicate recommendations by which no explicit packets or additional headers are disseminated as recommendations. This allows our model to defend against recommendation related issues such as free-riding, honest-elicitation, and recommenders bias. Finally, we demonstrate the performance of our model through NS2 simulations.

Fellowship: Defense against Flooding and Packet Drop Attacks in MANET

In this paper, we propose an obligation-based model called fellowship to mitigate the flooding and packet drop attacks. We also explain how the fellowship model identifies and penalizes both the malicious and selfish nodes respectively in mobile ad hoc networks (MANET). The main advantages of our model are: it unifies the framework to defend both flooding and packet drop attacks, it identifies and expels the malicious and selfish nodes that fail to contribute their resources, and rejoins the repenting malicious and selfish nodes into the network. In addition, our technique does not rely on any centralized authority or tamper-proof hardware

Intrusion detection techniques in cloud environment

Security is of paramount importance in this new era of on-demand Cloud Computing. Researchers have provided a survey on several intrusion detection techniques for detecting intrusions in the cloud computing environment. Most of them provide a discussion over traditional misuse and anomaly detection techniques. Virtual Machine Introspection (VMI) techniques are very helpful in detecting various stealth attacks targeting user-level and kernel-level processes running in virtual machines (VMs) by placing the analyzing component outside the VM generally at hypervisor. Hypervisor Introspection (HVI) techniques ensure the hypervisor security and prevent a compromised hypervisor to launch further attacks on VMs running over it. Introspection techniques introspect the hypervisor by using hardware-assisted virtualization-enabled technologies. The main focus of our paper is to provide an exhaustive literature survey of various Intrusion Detection techniques proposed for cloud environment with an analysis of their attack detection capability. We propose a threat model and attack taxonomy in cloud environment to elucidate the vulnerabilities in cloud. Our taxonomy of IDS techniques represent the state of the art classification and provides a detailed study of techniques with their distinctive features. We have provided a deep insight into Virtual Machine Introspection (VMI) and Hypervisor Introspection (HVI) based techniques in the survey. Specific research challenges are identified to give future direction to researchers. We hope that our work will enable researchers to launch and dive deep into intrusion detection approaches in a cloud environment.

Counteracting security attacks in virtual machines in the cloud using property based attestation

Cloud computing technologies are receiving a great deal of attention. Furthermore most of the hardware devices such as the PCs and mobile phones are increasingly having a trusted component called Trusted Platform Module embedded in them, which helps to measure the state of the platform and hence reason about its trust. Recently attestation techniques such as binary attestation and property based attestation techniques have been proposed based on the TPM. In this paper, we propose a novel trust enhanced security model for cloud services that helps to detect and prevent security attacks in cloud infrastructures using trusted attestation techniques. We consider a cloud architecture where different services are hosted on virtualized systems on the cloud by multiple cloud customers (multi-tenants). We consider attacker model and various attack scenarios for such hosted services in the cloud. Our trust enhanced security model enables the cloud service provider to certify certain security properties of the tenant virtual machines and services running on them. These properties are then used to detect and minimise attacks between the cloud tenants running virtual machines on the infrastructure and its customers as well as increase the assurance of the tenant virtual machine transactions. If there is a variation in the behaviour of the tenant virtual machine from the certified properties, the model allows us to dynamically isolate the tenant virtual machine or even terminate the malicious services on a fine granular basis. The paper describes the design and implementation of the proposed model and discusses how it deals with the different attack scenarios. We also show that our model is beneficial for the cloud service providers, cloud customers running tenant virtual machines as well as the customers using the services provided by these tenant virtual machines.

Tracing DDoS Floods: An Automated Approach

We propose a Controller-Agent model that would greatly minimize distributed denial-of-service (DDoS) attacks on the Internet. We introduce a new packet marking technique and agent design that enables us to identify the approximate source of attack (nearest router) with a single packet even in the case of attacks with spoofed source addresses. Our model is invoked only during attack times, and is able to process the victims traffic separately without disturbing other traffic, it is also able to establish different attack signatures for different attacking sources and can prevent the attack traffic at the nearest router to the attacking system. It is simple in its implementation, it has fast response for any changes in attack traffic pattern, and can be incrementally deployed. Hence we believe that the model proposed in this paper seems to be a promising approach to prevent distributed denial-of-service attacks.

TVDSEC: Trusted Virtual Domain Security

Virtualisation is one of the important technologies for the realisation of cloud computing. A Virtual Machine Monitor (VMM) is an additional software layer which has complete control on the physical resources and enables to run multiple operating systems on a scalable computer. Recently some of the techniques have been proposed to develop Trusted Virtual domains. A trusted virtual domain (TVD) enables grouping of related virtual machines running on separate physical machine into a single network domain with a unified security policy. In this paper we analyze the security issues related to TVD and propose security techniques to deal with the attacks in TVD.