People-centric urban sensing systems (PC-USSs) refer to using human-carried mobile devices such as smartphones and tablets for urban-scale distributed data collection, analysis, and sharing to facilitate interaction between humans and their surrounding environments. A main obstacle to the widespread deployment and adoption of PC-USSs are the privacy concerns of participating individuals as well as the concerns about data integrity. To tackle this open challenge, this paper presents the design and evaluation of VPA, a novel peer-to-peer based solution to verifiable privacy-preserving data aggregation in PC-USSs. VPA achieves strong user privacy by letting each user exchange random shares of its datum with other peers, while at the same time ensures data integrity through a combination of Trusted Platform Module and homomorphic message authentication code. VPA can support a wide range of statistical additive and non-additive aggregation functions such as Sum, Average, Variance, Count, Max/Min, Median, Histogram, and Percentile with accurate aggregation results. The efficacy and efficiency of VPA are confirmed by thorough analytical and simulation results.

We consider an unattended tiered sensor network (UTSN) consisting of resource-rich master nodes at the upper tier and resource-poor sensor nodes at the lower tier. Sensor nodes submit data to nearby master nodes which store the data and answer the queries from the network owner on behalf of sensor nodes. Such a cooperative data storage and query processing paradigm offers a number of advantages over traditional Homogeneous unattended sensor networks. Relying on master nodes for data storage and query processing, however, raises severe concerns about data confidentiality and query-result correctness when the sensor network is deployed in hostile environments. In particular, a compromised master node may leak hosted sensitive data to the adversary; it may also return juggled or incomplete query results to the network owner. In this paper, we take multidimensional range queries as an example to investigate secure cooperative data storage and query processing in UTSNs. We present a suite of novel schemes that can ensure data confidentiality against master nodes and also enable the network owner to verify with very high probability the authenticity and completeness of any query result by inspecting the spatial and temporal relationships among the returned data. Detailed performance evaluations confirm the high efficacy and efficiency of the proposed schemes.

We target a two-tier sensor network with resource-rich master nodes at the upper tier and resource-poor sensor nodes at the lower tier. Master nodes collect data from sensor nodes and answer the queries from the network owner. The reliance on master nodes for data storage and query processing raises serious concerns about both data confidentiality and query-result correctness in hostile environments. In particular, a compromised master node may leak hosted sensitive data to the adversary; it may also return juggled or incomplete data in response to a query. This paper presents a novel spatiotemporal approach to ensure secure range queries in event-driven two-tier sensor networks. It offers data confidentiality by preventing master nodes from reading hosted data and also enables efficient range-query processing. More importantly, it allows the network owner to verify with very high probability whether a query result is authentic and complete by examining the spatial and temporal relationships among the returned data. The high efficacy and efficiency of our approach are confirmed by detailed performance evaluations.

People-centric urban sensing is a new paradigm gaining popularity. A main obstacle to its widespread deployment and adoption are the privacy concerns of participating individuals. To tackle this open challenge, this paper presents the design and evaluation of PriSense, a novel solution to privacy-preserving data aggregation in people-centric urban sensing systems. PriSense is based on the concept of data slicing and mixing and can support a wide range of statistical additive and non-additive aggregation functions such as Sum, Average, Variance, Count, Max/Min, Median, Histogram, and Percentile with accurate aggregation results. PriSense can support strong user privacy against a tunable threshold number of colluding users and aggregation servers. The efficacy and efficiency of PriSense are confirmed by thorough analytical and simulation results.

Most large-scale sensor networks are expected to follow a two-tier architecture with resource-poor sensor nodes at the lower tier and resource-rich master nodes at the upper tier. Master nodes collect data from sensor nodes and then answer the queries from the network owner on their behalf. In hostile environments, master nodes may be compromised by the adversary and then instructed to return fake and/or incomplete data in response to data queries. Such application-level attacks are more harmful and difficult to detect than blind DoS attacks on network communications, especially when the query results are the basis for making critical decisions such as military actions. This paper presents three schemes whereby the network owner can verify the authenticity and completeness of fine-grained top-k query results in tired sensor networks, which is the first work of its kind. The proposed schemes are built upon symmetric cryptographic primitives and force compromised master nodes to return both authentic and complete top-k query results to avoid being caught. Detailed theoretical and quantitative results confirm the high efficacy and efficiency of the proposed schemes.

The open wireless medium in a mobile ad-hoc network (MANET) enables malicious traffic analysis to dynamically infer the network traffic pattern in hostile environments. The disclosure of the traffic pattern and its changes is often devastating in a mission-critical MANET. A number of anonymous routing protocols have been recently proposed as an effective countermeasure against traffic analysis in MANETs. In this paper, we propose a novel traffic inference algorithm, called TIA, which enables a passive global adversary to accurately infer the traffic pattern in an anonymous MANET without compromising any node. As the first work of its kind, TIA works on existing on-demand anonymous MANET routing protocols. Detailed simulations show that TIA can infer the traffic pattern with an accuracy as high as 95%. Our results in this paper highlight the necessity for cross-layer designs to defend a MANET against traffic analysis.

We envision a two-tier sensor network which consists of resource-rich master nodes at the upper tier and resource- poor sensor nodes at the lower tier. Master nodes collect data from sensor nodes and answer the queries from the network owner. The reliance on master nodes for data storage and query processing raises concerns about both data confidentiality and query-result correctness in hostile environments. In particular, a compromised master node may leak hosted sensitive data to the adversary; it may also return juggled or incomplete data in response to a query. This paper presents a novel spatiotemporal crosscheck approach to ensure secure range queries in event- driven two-tier sensor networks. It offers data confidentiality by preventing master nodes from reading hosted data and also enables efficient range-query processing. More importantly, it allows the network owner to verify with very high probability whether a query result is authentic and complete by examining the spatial and temporal relationships among the returned data. The high efficacy and efficiency of our approach are confirmed by detailed performance evaluations.

Most future large-scale sensor networks are expected to follow a two-tier architecture which consists of resource-rich master nodes at the upper tier and resource-poor sensor nodes at the lower tier. Sensor nodes submit data to nearby master nodes which then answer the queries from the network owner on behalf of sensor nodes. Relying on master nodes for data storage and query processing raises severe concerns about data confidentiality and query-result correctness when the sensor network is deployed in hostile environments. In particular, a compromised master node may leak hosted sensitive data to the adversary; it may also return juggled or incomplete query results to the network owner. This paper, for the first time in the literature, presents a suite of novel schemes to secure multidimensional range queries in tiered sensor networks. The proposed schemes can ensure data confidentiality against master nodes and also enable the network owner to verify with very high probability the authenticity and completeness of any query result by inspecting the spatial and temporal relationships among the returned data. Detailed performance evaluations confirm the high efficacy and efficiency of the proposed schemes.