Secure and highly-available aggregation queries in large-scale sensor networks via set sampling

Abstract

Wireless sensor networks are often queried for aggregates such as predicate count, sum, and average. In untrusted environments, sensors may potentially be compromised. Existing approaches for securely answering aggregation queries in untrusted sensor networks can detect whether the aggregation result is corrupted by an attacker. However, the attacker (controlling the compromised sensors) can keep corrupting the result, rendering the system unavailable.This paper aims to enable aggregation queries to tolerate instead of just detecting the adversary. To this end, we propose a novel tree sampling algorithm that directly uses sampling to answer aggregation queries. It leverages a novel set sampling technique to overcome a key and well-known obstacle in sampling -traditional sampling technique is only effective when the predicate count or sum is large. Set sampling can efficiently sample a set of sensors together, and determine whether any sensor in the set satisfies the predicate (but not how many). With set sampling as a building block, tree sampling can provably generate a correct answer despite adversarial interference, while without the drawbacks of traditional sampling techniques.

Secure distributed top-k aggregation

“…Extensive work has been carried out in the field of secure aggregation to assure the integrity of aggregates [15]- [20]. However, the work cited imposes severe restrictions on the aggregation system, such as assuming a limited set of aggregation functions, specific data types, a small number of possible adversaries, static networks and imposing expensive integrity assurance protocols that may undermine the scaling properties of distributed aggregation protocols.…”

“…Previous approaches to secure distributed aggregation generally use expensive security protocols or place severe restrictions on the types of networks and services they support [15]- [20]. By contrast, we propose a simple, modular and low-overhead technique, using established principles of trusted systems [21], [22] to perform distributed aggregation in a secure fashion while preserving the scalability properties of the underlying aggregation protocol.…”

Constrained Function-Based Message Authentication for Sensor Networks

“…The above equation can be rewritten as . Together with this equation, (16) can be represented as (17) It can be observed that reflection attack does not work in breaking with higher probability because there are still unknown variables in equations. Thus, unknown variables should be eliminated or correctly guessed.…”

“…From the estimation theory point of view, the sensor data cryptography in WSNs is investigated in [1]. The secure aggregation in WSNs is also studied in [8] and [17]. In this paper, we focus on the design of an en-route filtering scheme that can simultaneously defend against false data injection attack, PDoS attack, and false endorsement-based DoS (FEDoS) attack.…”

Secure Data Accumulation among Reliable Hops with Rest/Alert Scheduling in Wireless Sensor Networks

“…Haifeng Yu [13] has proposed a tree-testing method of calculation that specifically utilizes to answer the data collection inquiries and gives subjectively enhanced www.ijacsa.thesai.org usefulness in connection to the existing secure data collection techniques. The primary favorable position fathoms an important key test examining by reducing the direct problems into mathematical based problems that uses logarithms as the process models.…”