6073620
LAD: localization anomaly detection for wireless sensor networks
In wireless sensor networks (WSNs), sensors' locations play a critical role in many applications. Having a GPS receiver on every sensor node is costly. In the past, a number of location discovery (localization) schemes have been proposed. Most of these schemes share a common feature: they use some special nodes, called beacon nodes, which are assumed to know their own locations (e.g., through GPS receivers or manual configuration). Other sensors discover their locations based on the reference information provided by these beacon nodes. Most of the beacon-based localization schemes assume a benign environment, where all beacon nodes are supposed to provide correct reference information. However, when the sensor networks are deployed in a hostile environment, where beacon nodes can be compromised, such an assumption does not hold anymore. In this paper, we propose a general scheme to detect localization anomalies that are caused by adversaries. Our scheme is independent from the localization schemes. We formulate the problem as an anomaly intrusion detection problem, and we propose a number of ways to detect localization anomalies. We have conducted simulations to evaluate the performance of our scheme, including the false positive rates, the detection rates, and the resilience to node compromises.
15609835
A beacon-less location discovery scheme for wireless sensor networks
In wireless sensor networks (WSNs), sensor location plays a critical role in many applications. Having a GPS receiver on every sensor node is costly. In the past, a number of location discovery schemes have been proposed. Most of these schemes share a common feature: they use some special nodes, called beacon nodes, which are assumed to know their own locations (e.g., through GPS receivers or manual configuration). Other sensors discover their locations based on the information provided by these beacon nodes. In this paper, we show that efficient location discovery can be achieved in sensor networks without using beacons. We propose a beacon-less location discovery scheme, based on the following observations: in practice, it is quite common that sensors are deployed in groups, i.e., sensors are put into n groups, and sensors in the same group are deployed together at the same deployment point (the deployment point is different from the sensors' final resident location). Sensors from the same group can land in different locations, and those locations usually follow a probability distribution that can be known a priori. With this prior deployment knowledge, we show that sensors can discover their locations by observing the group memberships of its neighbors. We model the location discovery problem as a statistical estimation problem, and we use the maximum likelihood estimation method to estimate the location. We have conducted experiments to evaluate our scheme.
1319991
Context-aware wireless sensor networks for assisted living and residential monitoring
Improving the quality of healthcare and the prospects of "aging in place" using wireless sensor technology requires solving difficult problems in scale, energy management, data access, security, and privacy. We present AlarmNet, a novel system for assisted living and residential monitoring that uses a two-way flow of data and analysis between the front- and back-ends to enable context-aware protocols that are tailored to residents' individual patterns of living. AlarmNet integrates environmental, physiological, and activity sensors in a scalable heterogeneous architecture. The SenQ query protocol provides real-time access to data and lightweight in-network processing. Circadian activity rhythm analysis learns resident activity patterns and feeds them back into the network to aid context-aware power management and dynamic privacy policies.
393655
A Novel Artificial Immune System for Multiobjective Optimization Problems
This study presents a novel weight-based multiobjective artificial immune system (WBMOAIS) based on opt-aiNET. The proposed algorithm follows the elementary structure of opt-aiNET, but has the following distinct characteristics: At first,a randomly weighted sum of multiple objectives is used as a fitness function; Secondly, the individuals of the population are chosen from the memory, which is a set of elite solutions. Lastly, in addition to the clonal suppression algorithm similar to that used in opt-aiNET, a new truncation algorithm with similar individuals (TASI) is presented in order to eliminate the similar individuals in memory and obtain a well-distributed spread of non-dominated solutions. Simulation results show WBMOAIS outperforms the vector immune algorithm (VIS) and the elitist non-dominated sorting genetic system (NSGA-II).
3191506
A Fast Approximation Algorithm for MIN-ONE SAT
In this paper, we propose a novel approximation algorithm (RelaxSAT) for MIN-ONE SAT. RelaxSAT generates a set of constraints from the objective function to guide the search. The constraints are gradually relaxed to eliminate the conflicts with the original Boolean SAT formula until a solution is found. The experiments demonstrate that RelaxSAT is able to handle very large instances which cannot be solved by existing MIN-ONE algorithms; furthermore, very tight bounds on the solution were obtained with one to two orders of magnitude speedup.
7962101
A New Hybrid Solution to Boost SAT Solver Performance
Due to the widespread demands for efficient SAT solvers in Electronic Design Automation applications, methods to boost the performance of the SAT solver are highly desired. We propose a Hybrid Solution to boost SAT solver performance in this paper, via an integration of local and DPLL-based search approaches. A local search is used to identify a subset of clauses to be passed to a DPLL SAT solver through an incremental interface. In addition, the solution obtained by the DPLL solver on the subset of clauses is fed back to the local search solver to jump over any locally optimal points. The proposed solution is highly portable to the existing SAT solvers. For satisfiable instances, up to an order of magnitude speedup can be obtained via the proposed hybrid solver.
152848
Guided test generation for isolation and detection of embedded trojans in ics
Testing the genuineness of a manufactured chip is an important step in an IC product life cycle. This becomes more prominent with the outsourcing of the manufacturing process, since the manufacturer may tamper the internal circuit behavior using Trojan circuits in the original design. Traditional testing methods cannot detect these stealthy Trojans because the triggering scenario, which activates it, is unknown. Recently, approaches based on side-channel analysis have shown promising results in detecting Trojans. In this paper, we propose a novel test generation technique that aims at magnifying the disparity between side-channel signal waveforms of tampered and genuine circuits to indicate the possibility of internal tampering. Experimental results indicate that our approach could magnify the likelihood of Trojans 4 to 20 times more than existing side-channel analysis based approaches.