Joel W. Branch

Intrusion detection: a bioinformatics approach

We address the problem of detecting masquerading, a security attack in which an intruder assumes the identity of a legitimate user. Many approaches based on hidden Markov models and various forms of finite state automata have been proposed to solve this problem. The novelty of our approach results from the application of techniques used in bioinformatics for a pair-wise sequence alignment to compare the monitored session with past user behavior. Our algorithm uses a semiglobal alignment and a unique scoring system to measure similarity between a sequence of commands produced by a potential intruder and the user signature, which is a sequence of commands collected from a legitimate user. We tested this algorithm on the standard intrusion data collection set. As discussed, the results of the test showed that the described algorithm yields a promising combination of intrusion detection rate and false positive rate, when compared to published intrusion detection algorithms.

In-network outlier detection in wireless sensor networks

To address the problem of unsupervised outlier detection in wireless sensor networks, we develop an approach that (1) is flexible with respect to the outlier definition, (2) computes the result in-network to reduce both bandwidth and energy consumption, (3) uses only single-hop communication, thus permitting very simple node failure detection and message reliability assurance mechanisms (e.g., carrier-sense), and (4) seamlessly accommodates dynamic updates to data. We examine performance by simulation, using real sensor data streams. Our results demonstrate that our approach is accurate and imposes reasonable communication and power consumption demands.

SENSE: A WIRELESS SENSOR NETWORK SIMULATOR

A new network simulator, called SENSE, has been developed for simulating wireless sensor networks. The primary design goal is to address such factors as extensibility, reusability, and scalability, and to take into account the needs of different users. The recent progresses in component-based simulation, namely the component-port model and the simulation component classification, provided a sound theoretical foundation for the simulator. Practical issues, such as efficient memory usage, sensor network specific models, were also considered. Consequently, SENSE becomes an ease-of-use and efficient simulator for sensor network research.

Efficient network management for context-aware participatory sensing

Participatory sensing is becoming more popular with the help of sensor-embedded smartphones to retrieve context-aware information for users. However, new challenges arise for the maintenance of the energy supply, the support of the quality-of-information (QoI) requirements, and the generation of maximum revenue for network operator, but with sparsely research exposure. This paper proposes a novel efficient network management framework to tackle the above challenges, where four key design elements are introduced. First is the QoI satisfaction index, where the QoI benefit the queries receive is quantified in relation to the level they require. Second is the credit satisfaction index, where the credits are used by the network operator to motivate the user participation, and this index is to quantify its degree of satisfaction. Third is the Gur Game-based distributed energy control, where the above two indexes are used as inputs to the mathematical framework of the Gur Game for distributed decision-making. Fourth is the dynamic pricing scheme, based on a constrained optimization problem to allocate credits to the participants while minimizing the necessary adaptation of the pricing scheme from the network operator. We finally evaluate the proposed scheme under an event occurrence detection scenario, where the proposed scheme successfully guarantees less than 7% detection outage, saves 80% of the energy reserve if compared with the lower bound solution, and achieves the suboptimum with only 4% gap if compared with optimal solution.

A letter soup for the quality of information in sensor networks

In this paper, an information grouping paradigm for QoI in sensor networks is introduced. First, a definition of QoI is presented by analyzing the ITUs definition of QoS. Then, the concept of operational context to facilitate the dynamic binding of sensor resources to applications is presented and the 5WH principle ({why, when, where, what, who, how{) for summarizing the information needs of an application and the capabilities of the sensing resources is introduced. Finally, a brief treatise on metrics composition for relevancy parameters is presented.

Sentire: a framework for building middleware for sensor and actuator networks

Sentire represents a framework for building extensible middleware for sensor and actuator networks (SANET). The fundamental principle behind Sentire is the partitioning of SANET middleware into logically related components in order to allow developers of different aspects of the middleware to share a common plug-in infrastructure where their developed artifacts can interact. In this paper, an extended introduction of Sentire is presented, followed by a practical illustration of how this framework can be used to build SANET middleware.

Toward QoI and Energy-Efficiency in Internet-of-Things Sensory Environments

Considering physical sensors with certain sensing capabilities in an Internet-of-Things (IoTs) sensory environment, in this paper, we propose an efficient energy management framework to control the duty cycles of these sensors under quality-of-information (QoI) expectations in a multitask-oriented environment. Contrary to past research efforts, our proposal is transparent and compatible both with the underlying low-layer protocols and diverse applications, and preserving energy-efficiency in the long run without sacrificing the QoI levels attained. In particular, we first introduce the novel concept of QoI-aware sensor-to-task relevancy to explicitly consider the sensing capabilities offered by a sensor to the IoT sensory environments, and QoI requirements required by a task. Second, we propose a novel concept of the critical covering set of any given task in selecting the sensors to service a task over time. Third, energy management decision is made dynamically at runtime, to reach the optimum for long-term application arrivals and departures under the constraint of their service delay. We show a case study to utilize sensors to perform environmental monitoring with a complete set of performance analysis. We further consider the signal propagation and processing latency into the proposal, and provide a thorough analysis on its impact on average measured delay probability.

Self-selecting reliable paths for wireless sensor network routing

Routing protocols for wireless sensor networks face two challenges. One is an efficient bandwidth usage which requires minimum delay between transfers of packets. Establishing permanent routes from the source to destination addresses this challenge since the received packet can be immediately transmitted to the next node. However, any disruption on the established path either causes packet loss, lowering the delivery rate, or invokes a costly process of creating an alternative path. The second challenge is the ability to tolerate permanent and transient failures of nodes and links, especially since such failures are frequent in sensor networks. Protocols that chose the forwarding node at each hop of a packet are resilient to such failures, but incur the delay caused by selection of the forwarding node at each hop of the multi-hop path. This paper presents a novel wireless sensor routing protocol, self-selecting reliable path routing (SRP) for wireless sensor network (WSN) routing, that addresses both challenges at once. This protocol evolved from the self-selecting routing (SSR) protocol which is essentially memory-less. In the first generation of SSR protocols each packet selects the forwarding node at each hop on its path from the source to destination. The protocol takes advantage of broadcast communication commonly used in WSNs as a communication primitive. It also uses a prioritized transmission back-off delay to uniquely identify the neighbor of the forwarder that will forward the packet. As a result, the protocol is resistant to node or link failures as long as an alternative path exists from the current forwarder to the destination. The second generation of SSR protocols, called self-healing routing (SHR) added the route repair procedure, invoked when no neighbor of the forwarder closer to the destination is alive. In a series of transmissions, a packet trapped at the current forwarder by failures of its neighbors is capable of backing-off towards the source to find an alternative route, if such exists, to the destination. The main contribution of this paper is the third generation of SSR protocols, termed self-selecting reliable path routing, SRP. It preserves SHRs dynamic path selection in face of failure. Yet it also enables packets to follow established paths without selection delay if failures do not occur. The important change in the protocol is to make it memorize the successfully traversed path and attempt to reuse it for subsequent packets flowing to the same destination. The interesting behavior of SRP arising from this property is that if a path from the source to destination exists on which no transient failures occur, SRP would converge its routing to such a reliable path. In the paper, we describe novel elements of the SRP protocol that resulted in the desired properties. Using simulation, we compare SRP protocol with the representatives of the two other approaches: AODV as the route-based protocol, and GRAB and SHR as the hop-selection protocols.

Local leader election, signal strength aware flooding, and routeless routing

We have identified a fundamental operator in wireless networks that we named the local leader election in which the goal is to select a node in a spatially close neighborhood. We present a simple and efficient solution to the local leader election problem by making use of both: (i) implicit synchronization points, commonly observable by all nodes in the same neighborhood, and (ii) the prioritized backoff delay, dependent on the desired probability of each node becoming a leader. We then show that both flooding and routing are instances of the local leader election problem, so our general solution naturally applies. By relating the backoff delay to the signal strength of the received packet, we have designed a variant of flooding named signal strength aware flooding (SSAF) that can improve its efficiency. By using a different metric to derive the backoff delay, we have designed a new generation wireless routing protocol, that we named the routeless routing protocol that possesses several interesting properties.

QoI-Aware Wireless Sensor Network Management for Dynamic Multi-Task Operations

This paper considers the novel area of quality-of-information (QoI)-aware network management of multitasking wireless sensor networks (WSNs). Specifically, it provides an investigation of new task admission and resource utilization mechanisms for controlling the individual QoI provided to new and existing tasks using real-time feedback-based monitoring mechanisms. The paper describes three key design elements in support of the above: (a) the QoI satisfaction index of a task, which quantifies the degree to which the required QoI is satisfied by the WSN; (b) the QoI network capacity, which expresses the ability of the WSN to host a new task with specific QoI requirements without sacrificing the attained QoI levels of other existing tasks, and (c) an adaptive, negotiation-based admission control mechanism that reconfigures and optimizes the usage of network resources in order to optimally accommodate the QoI requirements of all tasks. Finally, extensive results are presented for assessing the performance of the proposed solution for the case of an intruder detection application scenario.