A survey of timing channels and countermeasures

A timing channel is a communication channel that can transfer information to a receiver/decoder by modulating the timing behavior of an entity. Examples of this entity include the interpacket delays of a packet stream, the reordering packets in a packet stream, or the resource access time of a cryptographic module. Advances in the information and coding theory and the availability of high-performance computing systems interconnected by high-speed networks have spurred interest in and development of various types of timing channels. With the emergence of complex timing channels, novel detection and prevention techniques are also being developed to counter them. In this article, we provide a detailed survey of timing channels broadly categorized into network timing channel, in which communicating entities are connected by a network, and in-system timing channel, in which the communicating entities are within a computing system. This survey builds on the last comprehensive survey by Zander et al. [2007] and considers all three canonical applications of timing channels, namely, covert communication, timing side channel, and network flow watermarking. We survey the theoretical foundations, the implementation, and the various detection and prevention techniques that have been reported in literature. Based on the analysis of the current literature, we discuss potential future research directions both in the design and application of timing channels and their detection and prevention techniques

Efficient Aggregation of Multiple Classes of Information in Wireless Sensor Networks

Congestion in a Wireless Sensor Network (WSN) can lead to buffer overflow, resource waste and delay or loss of critical information from the sensors. In this paper, we propose the Priority-based Coverage-aware Congestion Control (PCC) algorithm which is distributed, priority-distinct, and fair. PCC provides higher priority to packets with event information in which the sink is more interested. PCC employs a queue scheduler that can selectively drop any packet in the queue. PCC gives fair chance to all sensors to send packets to the sink, irrespective of their specific locations, and therefore enhances the coverage fidelity of the WSN. Based on a detailed simulation analysis, we show that PCC can efficiently relieve congestion and significantly improve the system performance based on multiple metrics such as event throughput and coverage fidelity. We generalize PCC to address data collection in a WSN in which the sensor nodes have multiple sensing devices and can generate multiple types of information. We propose a Pricing System that can under congestion effectively collect different types of data generated by the sensor nodes according to values that are placed on different information by the sink. Simulation analysis show that our Pricing System can achieve higher event throughput for packets with higher priority and achieve fairness among different categories. Moreover, given a fixed system capacity, our proposed Pricing System can collect more information of the type valued by the sink

A Stochastic Analysis of the Performance of Distributed Databases With Site and Link Failures

A stochastic model for analyzing the performance of a distributed database is proposed. The database is prone to site and link failures, possible leading to a partition of the underlying communication network. The system model is parametrized to support very general assumptions about data replication, transaction access patterns and network connectivity. For concreteness of analysis, a concurrency control protocol based on Thomas' Majority Consensus protocol and the Two-Phase Commit Protocol is used. A new performance measure called expected system degradation is proposed; this measure is a combination of availability of data and the transaction response time; this is the first step towards the ultimate goal of defining the notion of availability for real-time transaction systems. The model allows a database designer to analyse the expected system performance and choose the right input parameters that emphasize the relative importance of availability and response times