Self-organizing Routing Algorithm fo Wireless Sensors Networks (WSN) using Ant Colony Optimization (ACO) with Tinyos.

This paper describes the basic tools to work with wireless sensors. TinyOShas a componentbased architecture which enables rapid innovation and implementation while minimizing code size as required by the severe memory constraints inherent in sensor networks. TinyOS's component library includes network protocols, distributed services, sensor drivers, and data acquisition tools ? all of which can be used asia or be further refined for a custom application. TinyOS was originally developed as a research project at the University of California Berkeley, but has since grown to have an international community of developers and users. Some algorithms concerning packet routing are shown. Incar entertainment systems can be based on wireless sensors in order to obtain information from Internet, but routing protocols must be implemented in order to avoid bottleneck problems. Ant Colony algorithms are really useful in such cases, therefore they can be embedded into the sensors to perform such routing task

Klever: Verification Framework for Critical Industrial C Programs

Automatic software verification tools help to find hard-to-detect faults in programs checked against specified requirements non-interactively. Besides, they can prove program correctness formally under certain assumptions. These capabilities are vital for verification of critical industrial programs like operating system kernels and embedded software. However, such programs can contain hundreds or thousands of KLOC that prevent obtaining valuable verification results in any reasonable time when checking non-trivial requirements. Also, existing tools do not provide widely adopted means for environment modeling, specification of requirements, verification of many versions and configurations of target programs, and expert assessment of verification results. In this paper, we present the Klever software verification framework, designed to reduce the effort of applying automatic software verification tools to large and critical industrial C programs.Comment: 53 page

Security techniques for sensor systems and the Internet of Things

Sensor systems are becoming pervasive in many domains, and are recently being generalized by the Internet of Things (IoT). This wide deployment, however, presents significant security issues. We develop security techniques for sensor systems and IoT, addressing all security management phases. Prior to deployment, the nodes need to be hardened. We develop nesCheck, a novel approach that combines static analysis and dynamic checking to efficiently enforce memory safety on TinyOS applications. As security guarantees come at a cost, determining which resources to protect becomes important. Our solution, OptAll, leverages game-theoretic techniques to determine the optimal allocation of security resources in IoT networks, taking into account fixed and variable costs, criticality of different portions of the network, and risk metrics related to a specified security goal. Monitoring IoT devices and sensors during operation is necessary to detect incidents. We design Kalis, a knowledge-driven intrusion detection technique for IoT that does not target a single protocol or application, and adapts the detection strategy to the network features. As the scale of IoT makes the devices good targets for botnets, we design Heimdall, a whitelist-based anomaly detection technique for detecting and protecting against IoT-based denial of service attacks. Once our monitoring tools detect an attack, determining its actual cause is crucial to an effective reaction. We design a fine-grained analysis tool for sensor networks that leverages resident packet parameters to determine whether a packet loss attack is node- or link-related and, in the second case, locate the attack source. Moreover, we design a statistical model for determining optimal system thresholds by exploiting packet parameters variances. With our techniques\u27 diagnosis information, we develop Kinesis, a security incident response system for sensor networks designed to recover from attacks without significant interruption, dynamically selecting response actions while being lightweight in communication and energy overhead

Systematic and automatic verification of sensor networks

Ph.DDOCTOR OF PHILOSOPH

Model Checking and Model-Based Testing : Improving Their Feasibility by Lazy Techniques, Parallelization, and Other Optimizations

This thesis focuses on the lightweight formal method of model-based testing for checking safety properties, and derives a new and more feasible approach. For liveness properties, dynamic testing is impossible, so feasibility is increased by specializing on an important class of properties, livelock freedom, and deriving a more feasible model checking algorithm for it. All mentioned improvements are substantiated by experiments

Software verification for TinyOS

Ensuring the reliability of the software deployed on networked wireless sensors is a difficult problem: unsafe, low-level, interrupt-driven code runs without memory protection in dynamic environments. To aid the matter, we describe a software analysis tool for the debugging and verification of TinyOS 2, MSP430 applications at compile-time. Whileexistingsolutionsactatruntime to log, report and reboot from software errors such as memory violations, our tool is the first to allow the programmer to verify a TinyOS application statically; given assumptions about the behaviour of the node’s environment and assertions upon the state of the node itself, the tool explores all possible program executions and returns to the programmer an error trace leading to the violation of an assertion, if any exists. Besides memoryrelated errors (out-of-bounds arrays, null-pointer dereferences), we also support application-specific assertions, including low-level assertions upon the state of the registers and peripherals