Privacy Of Nodes Research Articles

The risk of node re-identification in labeled social graphs

Real network datasets provide significant benefits for understanding phenomena such as information diffusion or network evolution. Yet the privacy risks raised from sharing real graph datasets, even when stripped of user identity information, are significant. When nodes have associated attributes, the privacy risks increase. In this paper we quantitatively study the impact of binary node attributes on node privacy by employing machine-learning-based re-identification attacks and exploring the interplay between graph topology and attribute placement. We also analyze the risk of anonymity over epidemic networks subject to different node re-identification attacks. Our experiments show that the population’s diversity on the binary attribute consistently degrades anonymity. More interestingly, we show that similar diverse populations in the SI epidemic model maintain different levels of anonymity with different infection rates.

The evaluation and application of node influence in dynamic networks based on evolving communities

AbstractThe network connectivity in dynamic networks depends on a small number of highly mobile nodes. Identifying the influential nodes is one of the most engaging challenges for mobile applications, such as data offloading or worm propagation control. Reachability is an important metric to uncover node influence. Both TRGs (temporal reachability graphs) and CJEGs (critical journey evolving graphs) provide approaches to calculate reachability. Nevertheless, these approaches are only for epidemic scenarios. In practice, due to node privacy or limited battery life, message transmission is, to a certain extent, a probabilistic dissemination. Accordingly, reachability is difficult to exactly determine. As a structure of tight‐knit nodes, a community is born of a coarse‐grained estimation of reachability under a probabilistic propagation scenario. Based on an existing overlapping community detection framework, ie, AFOCS (an unsupervised machine learning algorithm), we propose an evolving overlapping community detection algorithm, ie, EFOCS, and further developed a metric, ie, OR_CEN, to estimate the reachability under the probabilistic propagation scenario. A content delivery experiment showed that OR_CEN accurately reveals the influence of nodes in dynamic networks. Based on OR_CEN, we also propose several target set selection algorithms and discuss their application in mobile data offloading. Analysis and simulation experiments indicated that CBS_OR, the target set selection algorithm based on OR_CEN centrality, has more advantages in scalability and distributed computing than CBS_AFOCS (an algorithm based on an aggregated AFOCS community), TRG_GREEDY (a greedy algorithm based on TRGs) and RANDOM (an algorithm based on a random selection strategy). Moreover, CBS_OR exhibited a significant better offloading effect than the algorithms mentioned earlier.

Differentially Private Location Privacy Preservation in Wireless Sensor Networks

In wireless sensor networks, the privacy of an event is critical to its safety. The location privacy of the sensor node that reports the event is imperative to the privacy of the event. Thus, privacy protection of both the event and the node that observes and reports the event is critical. In this work, we present a differentially private framework for ensuring the location privacy of a node and through it the event. The framework is based on the premise that an event occurrence is observed by multiple nodes. The transmissions triggered by an event reported by multiple nodes have low sensitivity to transmission by a single source node. If an event is reported by small number of nodes, additional dummy traffic needs to be generated for privacy of the event. Moreover, fake events are required to evade sustained observation. The privacy of an event also requires that an adversary must not be able to distinguish between real and dummy traffic. Reduced sensitivity to a single node transmission is achieved by cumulative, real and dummy traffic reporting the same event and by rendering real and fake events indistinguishable. Results indicate that dummy traffic for real and fake event ensure the differential privacy of the location of the occurrence of a node and the related event can be achieved.

Efficient Secure Aggregation in VANETs Using Fully Homomorphic Encryption (FHE)

The data aggregation is used generally in VANETs to preserve the user information and reduces the traffic due to packets of high frequency data. The data aggregation schemes performing multiple operations, usually undergoes problem related to message complexity, which leads to increased communication and storage overhead. This case is true in case of message transmitted frequently from a vehicle to provide communication in vehicular adhoc networks. Fully homomorphic encryption (FHE) lacks efficiency due to severe communicationoverhead problem. Hence, this paper improves the privacy of nodes in vehicular networks with reduced communication overhead. To achieve such concerns in VANETs, homomorphic encryption with pseudonym is utilized to carry the messages that tends to change with a desired frequency. The pseudonym changes often with vehicle mobility and the physical and logical address tends to vary over time. Here, the information of the vehicle relating its physical location and speed is made known globally in network, however, the information specific to vehicle and message transmitted is not known to the network. The message is encrypted with proposed Full homomorphic encryption (FHE) scheme to improve the security and reduce the overhead. Also, measures are taken such that the one pseudonym does not matches with the other pseudonym and makes the attacker ineffective for vehicle information tracking. The performance of the proposed FHE is compared with Paillier cryptosystem. It is found that the proposed method provides less communication overhead to transmit the message with improved security than with Paillier cryptosystem.

Privacy enabled disjoint and dynamic address auto-configuration protocol for 6Lowpan

In unsecured 6LoWPANs, the nodes can be easily identified by their IPv6 as well as MAC addresses. An adversary can snoop (and later, spoof) these addresses, thereby posing a major threat against the node’s identity and communication integrity. Such threats necessitate enabling privacy by obscuring the node’s addresses. This study proposes a protocol for dynamic, auto-configuring and conflict-free IPv6 addressing scheme that attempts to ensure privacy of nodes. In the proposed protocol, each node obtains a three-level hierarchical IPv6 address space which is dynamically generated on basis of congruence classes. Use of congruence classes, along with hierarchical addressing, facilitates generation of inter-leaved (and hence, disjoint) and non-fragmented address space for each node, resulting in conflict free address auto-generation. Nodes auto-configure their address sets independently with congruence seeds shared by routers, potentially reducing router complexity. To ensure the MAC address privacy, MAC address also changes when IPv6 address changes and it is derived from the interface identification (IID) part of the IPv6 address. The proposed protocol runs on Contiki operating system, simulated in Cooja. Simulated results highlight lower latency and optimal communication costs when compared with existing protocols.

On practical privacy-preserving fault-tolerant data aggregation

In this paper, we propose a fault-tolerant privacy-preserving data aggregation protocol which utilizes limited local communication between nodes. As a starting point, we analyze the Binary Protocol presented by Chan et al. Comparing to previous work, their scheme guaranteed provable privacy of individuals and could work even if some number of users refused to participate. In our paper we demonstrate that despite its merits, their method provides unacceptably low accuracy of aggregated data for a wide range of assumed parameters and cannot be used in majority of real-life systems. To show this we use both analytic and experimental methods. On the positive side, we present a precise data aggregation protocol that provides provable level of privacy even when facing massive failures of nodes. Moreover, our protocol requires significantly less computation (limited exploiting of heavy cryptography) than most of currently known fault-tolerant aggregation protocols and offers better security guarantees that make it suitable for systems of limited resources (including sensor networks). Most importantly, our protocol significantly decreases the error (compared to Binary Protocol). However, to obtain our result we relax the model and allow some limited communication between the nodes. Our approach is a general way to enhance privacy of nodes in networks that allow such limited communication, i.e., social networks, VANETs or other IoT appliances. Additionally, we conduct experiments on real data (Facebook social network) to compare our protocol with protocol presented by Chan et al.

Staircase based differential privacy with branching mechanism for location privacy preservation in wireless sensor networks

The privacy of an event is a critical aspect of safety in wireless sensor networks. Specially, the location privacy of the reporting sensor nodes is essential to preserving the privacy of the event. Protection the privacy of both the event and the node that observes and reports the corresponding event is critical. In this work, we present a differentially private branching framework for guaranteeing the location privacy of a node and subsequently the event. The proposed framework is based on the premise that an event is normally observed by multiple nodes. This leads to a low sensitivity to transmission by a single source node for the transmissions triggered by an event. If an event is reported by small number of nodes, additional fake traffic is required to be generated. Additionally, dummy sources are required to prevent backtracking. The privacy of an event also imposes the constraint that an adversary must not be able to distinguish between real and fake traffic. Results show that the mechanism initially adds small number of dummy sources which increases the number of source nodes. Later the branching mechanism adds large number of virtual nodes in branches emanating from the routing paths rooted in dummy sources. This increases the number of apparent source nodes substantially thereby ensuring location privacy of the source node.

Sink-Location Privacy Protection Based on Differential Privacy in WSNs

The location privacy of sink nodes is of vital importance for WSN security. Many location privacy protocols need the location of the sink node when routing, while most of them can’t resist an active attack. Hence, this paper proposed a new sink-location privacy protection protocol based on differential privacy (DPSL). The protocol uses anonymity and differential privacy to disturb the real position of the sink node and balances the privacy protection level and network performance by adjusting parameters. Analyzing the security, performance and power consumption of the protocol in Figure 4 to Figure 7, results showed that the protocol can protect location privacy with a little influence to power consumption of the network.

VANET Routing Protocols and Architectures: An Overview

VAVETs have become an interesting area of research since vehicles can be equipped with sensors, processing and communication devices. As a result, various life changing application emerged in different areas such as safety and public services. VANETs are considered as a subclass of Ad hoc networks. However, they have special characteristics that differentiates them such as QoS requirements, privacy, safety and high mobility of nodes. This paper discusses VANET’s special characteristics and explain why VANETs are considered a subcategory of ad hoc networks. Also, a categorization of VANETs architectures is presented in this study. Additionally, the importance and needs of VANETs along with their applications are presented in this study. Furthermore various routing protocols proposed for VANETs are studied and a categorization for these protocols is proposed in this study.

An anonymous access authentication scheme for vehicular ad hoc networks under edge computing

With the rapid booming of intelligent traffic system, vehicular ad hoc networks have attracted wide attention from both academic and industry. However, security is the main obstacle for the wide deployment of vehicular ad hoc networks. Vehicular ad hoc networks security has two critical issues: access authentication and privacy preservation. How to ensure privacy preservation and improve the efficiency of authentication has become the urgent needs. However, the existing access authentication schemes for vehicular ad hoc networks with different flaws cannot maintain the balance between security and efficiency. Thus, an anonymous access authentication scheme for vehicular ad hoc networks under edge computing based on ID-based short group signature mechanism is proposed in this article to improve the efficiency and anonymity of access authentication. Multiple pseudonyms are presented to preserve the privacy of vehicle node. Besides, a new method is designed to identify and revoke malicious vehicles in the evaluation manner. The core protocols of the proposed scheme are proved to be secure by SVO logic. According to the computation cost and transmission overhead analysis, we indicate that our scheme owns better performance. Moreover, in this article, we combine vehicular ad hoc networks with edge computing together to provide a new clue for the development of mobile edge computing.

Leveraging Mobile Nodes for Preserving Node Privacy in Mobile Crowd Sensing

Mobile crowd sensing has been a very important paradigm for collecting sensing data from a large number of mobile nodes dispersed over a wide area. Although it provides a powerful means for sensing data collection, mobile nodes are subject to privacy leakage risks since the sensing data from a mobile node may contain sensitive information about the sensor node such as physical locations. Therefore, it is essential for mobile crowd sensing to have a privacy preserving scheme to protect the privacy of mobile nodes. A number of approaches have been proposed for preserving node privacy in mobile crowd sensing. Many of the existing approaches manipulate the sensing data so that attackers could not obtain the privacy‐sensitive data. The main drawback of these approaches is that the manipulated data have a lower utility in real‐world applications. In this paper, we propose an approach called P3 to preserve the privacy of the mobile nodes in a mobile crowd sensing system, leveraging node mobility. In essence, a mobile node determines a routing path that consists of a sequence of intermediate mobile nodes and then forwards the sensing data along the routing path. By using asymmetric encryptions, it is ensured that a malicious node is not able to determine the source nodes by tracing back along the path. With our approach, upper‐layer applications are able to access the original sensing data from mobile nodes, while the privacy of the mobile node is not compromised. Our theoretical analysis shows that the proposed approach achieves a high level of privacy preserving capability. The simulation results also show that the proposed approach incurs only modest overhead.

Cloud-based security and privacy-aware information dissemination over ubiquitous VANETs

The rapid advancement of automobile industry enables the production of the high-tech vehicles equipped with more computing and communication power. This phenomenon explodes the development of rich vehicular applications for intelligent and safe transportation systems. However, security and privacy are one of the major concerns in cloud-based Vehicular ad hoc networks (VANETs). In this paper, we propose a cloud-based security and privacy-aware information dissemination environment between vehicular nodes and cloud infrastructure. Information Vectors (IVs) enable the sharing of fine-grained information among vehicular nodes and the cloud system. In this scheme, we couple the identity-based signature (IBS) with a pseudonym to not only provide authentication for IVs but also ensure the privacy of vehicular nodes. Moreover, we take on ciphertext policy attribute-based encryption (CP-ABE) to implement the access control systems and effective access policies for both cloud and VANETs. The experimental results demonstrate the efficiency of the proposed scheme in terms of computational overhead, space overhead and IVs authentication.

A remote attestation mechanism for the sensing layer nodes of the Internet of Things

Trusted transmission of data in sensing layer is the basis of security of Internet of Things so in data transmission process the trust of sensing node needs real-time confirmation and the track of the node is also needed. But the most current remote attestation mechanisms cannot achieve real-time trust attestation of sensing nodes and cannot track the node, if the node is an untrusted one, and these mechanisms also have poor environmental adaptability, so the current remote attestation mechanisms are not suitable for the sensing layer nodes in the Internet of Things. To solve the above problems, a remote attestation mechanism for the sensing layer nodes in the Internet of Things is presented in this paper. Firstly, the formal description of the sensor nodes is given; secondly, based on the formal description, a real-time trust measurement for the sensing nodes is proposed and the real-time trust measurement for the sensing nodes is realized; thirdly by encapsulating the properties and trust value of sensing node, the real-time tracing of the trust of nodes are realized in data transmission process. The security of this mechanism is proved in the standard model, meanwhile, this mechanism will not expose the privacy of nodes in the process of attestation, and it can trace the untrusted nodes. The simulation experiment shows that this mechanism can resist the attacks to the sensing nodes and can effectively improve the trust rate of data transmission, and this mechanism has good dynamic adaptability to network environment. This mechanism is simple and efficient, meanwhile the mechanism is flexible and easy to implement.

FaceChange: Attaining Neighbor Node Anonymity in Mobile Opportunistic Social Networks With Fine-Grained Control

In mobile opportunistic social networks (MOSNs), mobile devices carried by people communicate with each other directly when they meet for proximity-based MOSN services (e.g., file sharing) without the support of infrastructures. In current methods, when nodes meet, they simply communicate with their real IDs, which leads to privacy and security concerns. Anonymizing real IDs among neighbor nodes solves such concerns. However, this prevents nodes from collecting real ID-based encountering information, which is needed to support MOSN services. Therefore, in this paper, we propose FaceChange that can support both anonymizing real IDs among neighbor nodes and collecting real ID-based encountering information. For node anonymity, two encountering nodes communicate anonymously. Only when the two nodes disconnect with each other, each node forwards an encrypted encountering evidence to the encountered node to enable encountering information collection. A set of novel schemes are designed to ensure the confidentiality and uniqueness of encountering evidences. FaceChange also supports fine-grained control over what information is shared with the encountered node based on attribute similarity (i.e., trust), which is calculated without disclosing attributes. Advanced extensions for sharing real IDs between mutually trusted nodes and more efficient encountering evidence collection are also proposed. Extensive analysis and experiments show the effectiveness of FaceChange on protecting node privacy and meanwhile supporting the encountering information collection in MOSNs. Implementation on smartphones also demonstrates its energy efficiency.

Access Control Protocol With Node Privacy in Wireless Sensor Networks

For preventing malicious nodes joining wireless sensor networks (WSNs), an access control mechanism is necessary for the trustworthy cooperation between the nodes. In addition to access control, recently, privacy has been an important topic regarding how to achieve privacy without disclosing the real identity of communicating entities in the WSNs. Based on elliptic curve cryptography, in this paper, we present an access control protocol with node privacy (called ACP) for the WSN. The proposed scheme not only accomplishes the node authentication but also provides the identity privacy (i.e., source to destination and vice-versa) for the communicating entities. Compared with the current state of the art, the proposed solution can defend actively against attacks. The efficacy and the efficiency of the proposed ACP are confirmed through the test bed analysis and performance evaluations.

Preserving source- and sink-location privacy in sensor networks

Protecting the location privacy of source and sink nodes in a sensor network is an important problem. Source-location privacy is to prevent event source tracking by adversaries and sink-location privacy is to protect sink nodes from adversaries who try to disrupt the sensor network. In this paper, we propose a constant-rate broadcast scheme for ensuring their location privacy. This scheme (1) equalizes traffic patterns of the sensor network to deal with eavesdropping and (2) minimizes the routing information of each sensor node to deal with node compromising. We further reduce the overhead of the proposed scheme by proposing a forwarder-driven broadcast (FdB) scheme that allows efficient multiple broadcasts with smaller buffer usage. Analysis and evaluation results show that FdB can support multiple broadcasts with small message delivery time and buffer usage.

Security and privacy in localization for underwater sensor networks

Underwater sensor networks are envisioned to enable a wide range of underwater applications such as pollution monitoring, offshore exploration, and oil/gas spill monitoring. Such applications require precise location information as otherwise the sensed data might be meaningless. On the other hand, security and privacy are critical issues as underwater sensor networks are typically deployed in harsh environments. Nevertheless, most underwater localization schemes are vulnerable to many attacks and suffer from potential privacy violations as they are designed for benign environments. However, a localization scheme that does not consider security and privacy could lead to serious consequences, especially in critical applications such as military monitoring. In this article, we discuss the security and privacy issues in underwater localization, and investigate the techniques that can provide security and preserve node privacy in underwater sensor networks.

무선 센서 네트워크에서의 통신 경로 은닉

무선 센서 네트워크에 대한 전역 도청에 대응하여 통신 경로 상의 노드들을 은닉하기 위해서는 네트워크 전반에 걸쳐 수많은 속임수용 더미 패킷들이 발행되어야한다. 이 논문에서는 모바일 싱크(기지국)와 근원지들을 포함하는 일정 크기의 원 형태 내에 존재하는 노드들로 국한되는 플러딩 기반의 데이터 전송 프로토콜을 제안하여 노드들의 위치 기밀을 유지하고 생성되는 더미 패킷들의 수를 감축하고자 한다. 플러딩 크기는 보안 수준과 통신 비용을 고려하여 결정할 수 있다. 제안 프로토콜을 설계하고 주요 특성을 검증한다. Tremendous amount of dummy packets are generally generated for faking over a wireless sensor network so as to keep the location privacy of nodes on the communication paths against the global eavesdropping. In this paper, a scoped-flooding protocol is designed for transferring data between each source and mobile sink(aka, basestation) where, the only nodes within the scope are allowed to issue dummy packets at every idle time so that the location privacy of the nodes on the paths is kept and the amount of dummy packets is reduced to the extend of the flooding scope. The size of the flooding diameter can be taken into consideration of the privacy level and the communication cost. We design a detailed specification of the protocol and verify several properties.

Privacy-preserving data aggregation in two-tiered wireless sensor networks with mobile nodes.

Privacy-preserving data aggregation in wireless sensor networks (WSNs) with mobile nodes is a challenging problem, as an accurate aggregation result should be derived in a privacy-preserving manner, under the condition that nodes are mobile and have no pre-specified keys for cryptographic operations. In this paper, we focus on the SUM aggregation function and propose two privacy-preserving data aggregation protocols for two-tiered sensor networks with mobile nodes: Privacy-preserving Data Aggregation against non-colluded Aggregator and Sink (PDAAS) and Privacy-preserving Data Aggregation against Colluded Aggregator and Sink (PDACAS). Both protocols guarantee that the sink can derive the SUM of all raw sensor data but each sensor's raw data is kept confidential. In PDAAS, two keyed values are used, one shared with the sink and the other shared with the aggregator. PDAAS can protect the privacy of sensed data against external eavesdroppers, compromised sensor nodes, the aggregator or the sink, but fails if the aggregator and the sink collude. In PDACAS, multiple keyed values are used in data perturbation, which are not shared with the aggregator or the sink. PDACAS can protect the privacy of sensor nodes even the aggregator and the sink collude, at the cost of a little more overhead than PDAAS. Thorough analysis and experiments are conducted, which confirm the efficacy and efficiency of both schemes.

ReDD: recommendation‐based data dissemination in privacy‐preserving mobile social networks

AbstractMobile social network (MSN), which is built upon popular smart phone devices and enables mobile users with similar interests to connect with one another, has received considerable attention in recent years. A common phenomenon that makes the MSN vivid today is mobile users often like to share attractive things to their friends in MSN. In this paper, based on this common phenomenon, we propose an efficient recommendation‐based data dissemination (ReDD) protocol for MSN, which can efficiently disseminate high‐quality messages in a privacy‐preserving way. Specifically, in the proposed ReDD protocol, each mobile user, based on both his or her own view and his or her friends' recommendations, will form his or her personal estimation on the quality of a message. Only if the estimation of quality reaches a threshold, the message will be disseminated. In this way, high‐quality messages can be widely spread in the network and occupy more network resources than low‐quality ones. In order to check the validity of friends' recommendations, ReDD also employs an efficient anonymous authentication technique, which ensures that only the friends of a user can verify recommendations made by the user. Detailed security analysis demonstrates that ReDD can effectively resist various attacks launched by attackers and ensure identity privacy of nodes, confidentiality of shared keys and integrity of data packets. In addition, extensive simulations are also conducted to evaluate the performance of ReDD in terms of the number of active nodes and the average active time, and the simulation results show that high‐quality messages can be disseminated widely and efficiently, while low‐quality ones will be eliminated shortly to avoid occupying network resources. Copyright © 2014 John Wiley & Sons, Ltd.