Alessandro Daidone

Hidden Markov Models as a Support for Diagnosis: Formalization of the Problem and Synthesis of the Solution

In modern information infrastructures, diagnosis must be able to assess the status or the extent of the damage of individual components. Traditional one-shot diagnosis is not adequate, but streams of data on component behavior need to be collected and filtered over time as done by some existing heuristics. This paper proposes instead a general framework and a formalism to model such over-time diagnosis scenarios, and to find appropriate solutions. As such, it is very beneficial to system designers to support design choices. Taking advantage of the characteristics of the hidden Markov models formalism, widely used in pattern recognition, the paper proposes a formalization of the diagnosis process, addressing the complete chain constituted by monitored component, deviation detection and state diagnosis. Hidden Markov models are well suited to represent problems where the internal state of a certain entity is not known and can only be inferred from external observations of what this entity emits. Such over-time diagnosis is a first class representative of this category of problems. The accuracy of diagnosis carried out through the proposed formalization is then discussed, as well as how to concretely use it to perform state diagnosis and allow direct comparison of alternative solutions

The CRUTIAL Architecture for Critical Information Infrastructures

This invention provides a novel bracket for shock mounting a bulb within a housing for a lamp that is particularly intended for use with motorized vehicles, such as over-the-road trucks and the like. Basically, the novel bracket of the present invention comprises: a serpentine strip having polygonal apertures provided at its opposite ends and a bulb-receiving socket generally centrally located therein, the radial center of which socket is offset from the long central axis that extends between the apertures in the strip. Preferably, the strip is connected to the lamp housing by fastener means, portions of which are respectively passed through the polygonal apertures in the strip and prohibit pivotal movement of the apertures thereabout. It is also desirable that the fastener means portions comprise a pair of studs projecting from the lamp housing and being complementary in size and shape to the polygonal apertures in the strip through which they are respectively passed. And, those apertures are preferably square in shape. It is further desirable that the strip be constructed of glass fiber-reinforced nylon or some other similarly suitable material permitting deflection of the strip along, around and across the long central axis thereof which extends between the polygonal apertures in the opposite ends thereof.

A hidden Markov model based intrusion detection system for wireless sensor networks

Wireless sensor network (WSN) technology is being increasingly used for data collection in critical infrastructures (CIs). This paper presents an intrusion detection system (IDS), which is able to protect a CI from attacks directed to its WSN-based parts. By providing accurate and timely detection of malicious activities, the proposed IDS solution ultimately results in a dramatic improvement in terms of protection, since opportunities are given for performing proper remediation/reconfiguration actions, which counter the attack and/or allow the system to tolerate it. The proposed solution has the important advantage of exploiting the high accuracy of hidden Markov models as an effective means of detecting malicious activities. We present the basic ideas, discuss the main implementation issues, and perform a preliminary experimental campaign, with respect to sinkhole attacks, one of the most serious attacks to WSNs.

FOREVER: Fault/intrusiOn REmoVal through Evolution & Recovery

The goal of the FOREVER project is to develop a service for Fault/intrusiOn REmoVal through Evolution & Recovery. In order to achieve this goal, our work addresses three main tasks: the definition of the FOREVER service architecture; the analysis of how diversity techniques can improve resilience; and the evaluation of the FOREVER service. The FOREVER service is an important contribution to intrustion-tolerant replication middleware and significantly enhances the resilience.

Optimal configuration of fault-tolerance parameters for distributed replicated server access

Server replication is a common fault-tolerance strategy to improve transaction dependability for services in communications networks. In distributed architectures, fault-diagnosis and recovery are implemented via the interaction of the server replicas with the clients and other entities such as enhanced name servers. Such architectures provide an increased number of redundancy configuration choices. The influence of a (wide area) network connection can be quite significant and induce trade-offs between dependability and user-perceived performance. This paper develops a quantitative stochastic model using stochastic activity networks (SAN) for the evaluation of performance and dependability metrics of a generic transaction-based service implemented on a distributed replication architecture. The composite SAN model can be easily adapted to a wide range of client-server applications deployed in replicated server architectures. In order to obtain insight into the system behaviour, a set of relevant environment parameters and controllable fault-tolerance parameters are chosen and the dependability/performance trade-off is evaluated.