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Law enforcement agencies need the ability to conduct electronic surveillance to combat crime, terrorism, or other malicious activities exploiting the Internet. However, the proliferation of anonymous communication systems on the Internet has posed significant challenges to providing such traceback capability. In this paper, we develop a new class of flow marking technique for invisible traceback based on Direct Sequence Spread Spectrum (DSSS), utilizing a Pseudo-Noise (PN) code. By interfering with a sender's traffic and marginally varying its rate, an investigator can embed a secret spread spectrum signal into the sender's traffic. The embedded signal is carried along with the traffic from the sender to the receiver, so the investigator can recognize the corresponding communication relationship, tracing the messages despite the use of anonymous networks. The secret PN code makes it difficult for others to detect the presence of such embedded signals, so the traceback, while available to investigators is, effectively invisible. We demonstrate a practical flow marking system which requires no training, and can achieve both high detection and low false positive rates. Using a combination of analytical modeling, simulations, and experiments on Tor (a popular Internet anonymous communication system), we demonstrate the effectiveness of the DSSS-based flow mark- *

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Abstract. In this paper, we address issues related to flow correlation attacks and the corresponding countermeasures in mix networks. Mixes have been used in many anonymous communication systems and are supposed to provide countermeasures that can defeat various traffic analysis attacks. In this paper, we focus on a particular class of traffic analysis attack, flow correlation attacks, by which an adversary attempts to analyze the network traffic and correlate the traffic of a flow over an input link at a mix with that over an output link of the same mix. Two classes of correlation methods are considered, namely time-domain methods and frequency-domain methods. Based on our threat model and known strategies in existing mix networks, we perform extensive experiments to analyze the performance of mixes. We find that a mix with any known batching strategy may fail against flow correlation attacks in the sense that for a given flow over an input link, the adversary can correctly determine which output link is used by the same flow. We also investigated methods that can effectively counter the flow correlation attack and other timing attacks. The empirical results provided in this paper give an indication to designers of Mix networks about appropriate configurations and alternative mechanisms to be used to counter flow correlation attacks.

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Abstract-Location-based services (LBS) have become an immensely valuable source of real-time information and guidance. Nonetheless, the potential abuse of users' sensitive personal data by an LBS server is evolving into a serious concern. Privacy concerns in LBS exist on two fronts: location privacy and query privacy. In this paper we investigate issues related to query privacy. In particular, we aim to prevent the LBS server from correlating the service attribute, e.g., bar/tavern, in the query to the user's real-world identity. Location obfuscation using spatial generalization aided by anonymization of LBS queries is a conventional means to this end. However, effectiveness of this technique would abate in continuous LBS scenarios, i.e., where users are moving and recurrently requesting for LBS. In this paper, we present a novel query-perturbation-based scheme that protects query privacy in continuous LBS even when useridentities are revealed. Unlike most exiting works, our scheme does not require the presence of a trusted third party.

In the design of distributed computer systems, the scheduling problem is considered to be an important one and has been addressed by many researchers. However, most approaches have not dealt with tasks' timing and resource requirements. In this paper, we describe a set of heuristic algorithms to schedule tasks that have deadlines and resource requirements, in a distributed system. These algorithms are dynamic and function in a decentralized manner. When a task arrives at a node, the local scheduler at that node attempts to guarantee that the task will complete execution before its deadline, on that node. If the attempt fails, the scheduling components on individual nodes cooperate to determine which other node in the system has sufficient resource surplus to guarantee the task. In this paper, four algorithms for cooperation are evaluated. They differ in the way a node treats a task that cannot be guaranteed locally. The random scheduling algorithm: The task is sent to a randomly selected node. The focused addressing algorithm: The task is sent to a node that is estimated to have sufficient surplus to complete the task before its deadline. The bidding algorithm: The task is sent to a node based on the bids received for the task from nodes in the system. Theflexible algorithm: The task is sent to a node based on a technique that combines bidding and focused addressing. Simulation studies were performed to compare the performance of these algorithms relative to each other as well as with respect to two baselines. The first baseline is the noncooperative algorithm where a task that cannot be guaranteed locally is not sent to any other node. The second is an (ideal) algorithm that behaves exactly like the bidding algorithm but incurs no communication overheads. The simulation studies examine how communication delay, task laxity, load differences on the nodes, and task computation times affect the performance of the algorithms. The results show that distributed scheduling is effective even in a hard real-time environment and that the relative performance of these algorithms is a function of the system state.

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