83 research outputs found

    Storytelling Security: User-Intention Based Traffic Sanitization

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    Malicious software (malware) with decentralized communication infrastructure, such as peer-to-peer botnets, is difficult to detect. In this paper, we describe a traffic-sanitization method for identifying malware-triggered outbound connections from a personal computer. Our solution correlates user activities with the content of outbound traffic. Our key observation is that user-initiated outbound traffic typically has corresponding human inputs, i.e., keystroke or mouse clicks. Our analysis on the causal relations between user inputs and packet payload enables the efficient enforcement of the inter-packet dependency at the application level. We formalize our approach within the framework of protocol-state machine. We define new application-level traffic-sanitization policies that enforce the inter-packet dependencies. The dependency is derived from the transitions among protocol states that involve both user actions and network events. We refer to our methodology as storytelling security. We demonstrate a concrete realization of our methodology in the context of peer-to-peer file-sharing application, describe its use in blocking traffic of P2P bots on a host. We implement and evaluate our prototype in Windows operating system in both online and offline deployment settings. Our experimental evaluation along with case studies of real-world P2P applications demonstrates the feasibility of verifying the inter-packet dependencies. Our deep packet inspection incurs overhead on the outbound network flow. Our solution can also be used as an offline collect-and-analyze tool

    Identifying Native Applications with High Assurance

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    The work described in this paper investigates the problem of identifying and deterring stealthy malicious processes on a host. We point out the lack of strong application iden- tication in main stream operating systems. We solve the application identication problem by proposing a novel iden- tication model in which user-level applications are required to present identication proofs at run time to be authenti- cated by the kernel using an embedded secret key. The se- cret key of an application is registered with a trusted kernel using a key registrar and is used to uniquely authenticate and authorize the application. We present a protocol for secure authentication of applications. Additionally, we de- velop a system call monitoring architecture that uses our model to verify the identity of applications when making critical system calls. Our system call monitoring can be integrated with existing policy specication frameworks to enforce application-level access rights. We implement and evaluate a prototype of our monitoring architecture in Linux as device drivers with nearly no modication of the ker- nel. The results from our extensive performance evaluation shows that our prototype incurs low overhead, indicating the feasibility of our model

    Studying a Virtual Testbed for Unverified Data

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    It is difficult to fully know the effects a piece of software will have on your computer, particularly when the software is distributed by an unknown source. The research in this paper focuses on malware detection, virtualization, and sandbox/honeypot techniques with the goal of improving the security of installing useful, but unverifiable, software. With a combination of these techniques, it should be possible to install software in an environment where it cannot harm a machine, but can be tested to determine its safety. Testing for malware, performance, network connectivity, memory usage, and interoperability can be accomplished without allowing the program to access the base operating system of a machine. After the full effects of the software are understood and it is determined to be safe, it could then be run from, and given access to, the base operating system. This thesis investigates the feasibility of creating a system to verify the security of unknown software while ensuring it will have no negative impact on the host machine

    Memory Access Monitoring and Disguising of Process Information to Avoid Attacks to Essential Services

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    To prevent attacks on essential software and to mitigate damage, an attack avoiding method that complicates process identification from attackers is proposed. This method complicates the identification of essential services by replacing process information with dummy information. However, this method allows attackers to identify essential processes by detecting changes in process information. To address this problems and provide more complexity to process identification, this paper proposes a memory access monitoring by using a virtual machine monitor. By manipulating the page access permission, a virtual machine monitor detects page access, which includes process information, and replaces it with dummy information. This paper presents the design, implementation, and evaluation of the proposed method

    Intrusion Detection Systems in Cloud Computing: A Contemporary Review of Techniques and Solutions

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    Rapid growth of resources and escalating cost of infrastructure is leading organizations to adopt cloud computing. Cloud computing provides high performance, efficient utilization, and on-demand availability of resources. However, the cloud environment is vulnerable to different kinds of intrusion attacks which involve installing malicious software and creating backdoors. In a cloud environment, where businesses have hosted important and critical data, the security of underlying technologies becomes crucial. To mitigate the threat to cloud environments, Intrusion Detection Systems (IDS) are a layer of defense. The aim of this survey paper is to review IDS techniques proposed for the cloud. To achieve this objective, the first step is defining the limitations and unique characteristics of each technique. The second step is establishing the criteria to evaluate IDS architectures. In this paper, the criteria used is derived from basic characteristics of cloud. Next step is a comparative analysis of various existing intrusion detection techniques against the criteria. The last step is on the discussion of drawbacks and open issues, comprehended from the evaluation, due to which implementation of IDS in cloud environment face hurdles
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