Infrastructure-as-a-Service (IaaS) clouds can be viewed as distributed systems of cloud services that are entrusted to execute users' cloud commands to provision and manage clouds computing resources (e.g., VM). However, recent vulnerabilities found in cloud services show that this trust is often misplaced. By exploiting a vulnerability in a cloud service, an adversary can hijack or forge commands to modify user VMs, exfiltrate sensitive information, and even modify other service hosts. This paper introduces Cloud Armor, a system that detects and blocks the tampering of user commands without the need for modifications to cloud services. Our insight is that we can construct state machine models to limit the system call sequences executed by cloud services. By applying constraints over system call arguments, we can restrict the way user commands are executed, blocking unauthorized operations from compromised cloud services. We implemented a prototype Cloud Armor system for Open Stack, a widely adopted open source cloud platform. Results show that Cloud Armor can greatly limit attack options available for adversaries while imposing less than 1% overhead for user VMs. As a result, cloud users can leverage Cloud Armor to execute user commands safely even in presence of compromised cloud services.

Voice control is a popular way to operate mobile devices, enabling users to communicate requests to their devices. However, adversaries can leverage voice control to trick mobile devices into executing commands to leak secrets or to modify critical information. Contemporary mobile operating systems fail to prevent such attacks because they do not control access to the speaker at all and fail to control when untrusted apps may use the microphone, enabling authorized apps to create exploitable communication channels. In this paper, we propose a security mechanism that tracks the creation of audio communication channels explicitly and controls the information flows over these channels to prevent several types of attacks. We design and implement AuDroid, an extension to the SE Linux reference monitor integrated into the Android operating system for enforcing lattice security policies over the dynamically changing use of system audio resources. To enhance flexibility, when information flow errors are detected, the device owner, system apps and services are given the opportunity to resolve information flow errors using known methods, enabling AuDroid to run many configurations safely. We evaluate our approach on 17 widely-used apps that make extensive use of the microphone and speaker, finding that AuDroid prevents six types of attack scenarios on audio channels while permitting all 17 apps to run effectively. AuDroid shows that it is possible to prevent attacks using audio channels without compromising functionality or introducing significant performance overhead.

Microservice architecture allows different parts of an application to be developed, deployed and scaled independently, therefore becoming a trend for developing cloud applications. However, it comes with challenging security issues. First, the network complexity introduced by the large number of microservices greatly increases the difficulty in monitoring the security of the entire application. Second, microservices are often designed to completely trust each other, therefore compromise of a single microservice may bring down the entire application. The problems are only exacerbated by the cloud, since applications no longer have complete control over their networks. In this paper, we propose a design for security-as-a-service for microservices-based cloud applications. By adding a new API primitive FlowTap for the network hypervisor, we build a flexible monitoring and policy enforcement infrastructure for network traffic to secure cloud applications. We demonstrate the effectiveness of our solution by deploying the Bro network monitor using FlowTap. Results show that our solution is flexible enough to support various kinds of monitoring scenarios and policies and it incurs minimal overhead (~6%) for real world usage. As a result, cloud applications can leverage our solution to deploy network security monitors to flexibly detect and block threats both external and internal to their network.

Cloud computing has commoditized compute, storage, and networking resources creating an on-demand utility. Despite the attractiveness of this new paradigm, its adoption has been stymied by cloud platform's lack of transparency, which leaves customers unsure if their sensitive data and computation can be entrusted to the cloud. While techniques like encryption can protect customers' data at rest, clouds still lack mechanisms for customers to verify that their computations are being executed as expected, a guarantee one could obtain if they were running the computation in their own data center. In this paper, we present the cloud verifier (CV), a flexible framework that cloud vendors can configure to provide cloud monitoring services for customers to validate that their computations are configured and being run as expected in Infrastructure as a Service (IaaS) clouds. The CV builds a chain of trust from the customer to their hosted virtual machine (VM) instances through the cloud platform, enabling it to check customer-specified requirements against a comprehensive view of both the VM's load-time and run-time properties. In addition, the CV enables cloud vendors to provide more responsive remediation techniques than traditional attestation mechanisms. We built a proof of concept CV for the OpenStack cloud platform whose evaluation demonstrates that a single CV enables over 20,000 simultaneous customers to verify numerous properties with little impact on cloud application performance. As a result, the CV gives cloud customers a low-overhead method for assuring that their instances are running according to their requirements.