Secure Data Aggregation Protocol Research Articles

Secure Data Aggregation Using Authentication and Authorization for Privacy Preservation in Wireless Sensor Networks.

Existing secure data aggregation protocols are weaker to eliminate data redundancy and protect wireless sensor networks (WSNs). Only some existing approaches have solved this singular issue when aggregating data. However, there is a need for a multi-featured protocol to handle the multiple problems of data aggregation, such as energy efficiency, authentication, authorization, and maintaining the security of the network. Looking at the significant demand for multi-featured data aggregation protocol, we propose secure data aggregation using authentication and authorization (SDAAA) protocol to detect malicious attacks, particularly cyberattacks such as sybil and sinkhole, to extend network performance. These attacks are more complex to address through existing cryptographic protocols. The proposed SDAAA protocol comprises a node authorization algorithm that permits legitimate nodes to communicate within the network. This SDAAA protocol's methods help improve the quality of service (QoS) parameters. Furthermore, we introduce a mathematical model to improve accuracy, energy efficiency, data freshness, authorization, and authentication. Finally, our protocol is tested in an intelligent healthcare WSN patient-monitoring application scenario and verified using an OMNET++ simulator. Based upon the results, we confirm that our proposed SDAAA protocol attains a throughput of 444 kbs, representing a 98% of data/network channel capacity rate; an energy consumption of 2.6 joules, representing 99% network energy efficiency; an effected network of 2.45, representing 99.5% achieved overall performance of the network; and time complexity of 0.08 s, representing 98.5% efficiency of the proposed SDAAA approach. By contrast, contending protocols such as SD, EEHA, HAS, IIF, and RHC have throughput ranges between 415-443, representing 85-90% of the data rate/channel capacity of the network; energy consumption in the range of 3.0-3.6 joules, representing 88-95% energy efficiency of the network; effected network range of 2.98, representing 72-89% improved overall performance of the network; and time complexity in the range of 0.20 s, representing 72-89% efficiency of the proposed SDAAA approach. Therefore, our proposed SDAAA protocol outperforms other known approaches, such as SD, EEHA, HAS, IIF, and RHC, designed for secure data aggregation in a similar environment.

PF-DA: Pairing Free and Secure Data Aggregation for Energy Internet-Based Smart Meter-to-Grid Communication

The amalgamation of energy, economics and information technology has evolved the paradigm of Energy Internet (EI). This evolution of EI has transformed houses or buildings into home networks (HN) to ease communication between consumer-to-grid. Smart meters deployed at various sites (of HNs) send load, consumption and related information to the control center of the distribution utility. However, data sharing using wireless channels creates associated privacy and security issues and challenges. For example, adversary can capture family life-style from consumption data and may try to commit crime. Besides, data received at control center from various sites must be processed in an efficient manner. Therefore, an efficient protocol for such sharing and processing of data is aggregation scheme. Even though there is a considerable number of data aggregation schemes relying on public-key cryptography have been proposed in the literature. However, most of them are based on the expensive pairing computation and hence are not efficient. To address this issue, in this article we present an efficient and new pairing free and highly secure data aggregation protocol in certificate-based infrastructure. Due to pairing free design, the method’s computational cost is adequately efficient for any resource-constrained devices such as smart appliances or smart meters. The security and performance analysis has been presented to support the deployability of the scheme.

Identity-based secure data aggregation in big data wireless sensor networks

Secure data aggregation (SDA) is an inherent paradigm in big data wireless sensor networks (WSNs) to reduce data transmissions, maximise the network lifetime and provide security. However, SDA protocols that use elliptic curve suffer from mapping and reverse mapping functions. Currently, there is no known mapping function which is both homomorphic and effective in reverse mapping. In addition, SDA protocols that use public key infrastructure incurs high computation and communication cost. To overcome these challenges, this paper proposes a novel identity-based secure data aggregation (ISDA) protocol for big data wireless sensor networks. This protocol is based on bilinear pairing and combines identity-based homomorphic encryption scheme with identity-based signature to achieve end-to-end security. In WSNs, this is the first SDA protocol that employs both identity-based encryption and identity-based signature scheme. ISDA shares the same public/private keys during encryption and signature generation, which significantly reduces the complexity of the protocol. Security analysis reveals that ISDA is secure against various internal and external attacks and proves the correctness of the proposed protocol. Performance evaluation shows that ISDA incurs less overhead than state-of-the-art bilinear pairing-based SDA schemes, thereby it minimises the energy consumption and increases the lifetime of wireless sensor networks.

A novel appliance-based secure data aggregation scheme for bill generation and demand management in smart grids

ABSTRACT Internet of Things (IoT) has been introduced into smart grids, which has achieved great improvement. The statistics of power consumption is one of the important functions but could lead to the leakage of user daily behaviour. Researchers have put efforts into secure data aggregation protocols to avoid such potential risk. However, only a few schemes have considered the dynamic unit price of electricity, and no schemes have been designed for calculating the power consumption of every appliance in a specific area. This paper proposes a novel appliance-based data aggregation scheme (ABDAS) for bill generation and demand management in smart grids. In the proposed scheme, chameleon hash function (CHF) is utilised to facilitate the extraction of aggregated data due to the characteristic of collision controllability. Furthermore, indistinguishability obfuscation (IO) is utilised to keep the chameleon hash value secret and decrease the overhead of the trusted third party. The fog nodes (FNs) in our scheme are responsible for the calculation of aggregation with its powerful computing and storage capabilities. The security analysis shows that our scheme satisfies IND-CPA and multiple security goals. Additionally, the performance evaluation indicates that the computational overhead of our scheme is lower than that of existing schemes.

A Comparative Analysis of Data Aggregation Based Routing Protocols Hierarchies and Comparing Secure Data Aggregation Protocols in Wireless Sensor Networks

Sensor nodes deployed in Wireless Sensor Networks (WSNs) are battery powered. It operates at low voltage. The main challenge in WSNs is to reduce energy consumption so that it increases the lifetime of the sensor nodes. The goal is achieved by using data aggregation technique and also by selecting the appropriate routing strategy. Sensor nodes are commonly arranged in unmanned location; the security of data plays another important role. In order to provide reliable data to the destination, there are various approaches designed for security. In this paper, we analyzed the various existing approaches for data routing, data aggregation and data security.

DAML

Data aggregation based on machine learning (ML), in mobile edge computing, allows participants to send ephemeral parameter updates of local ML on their private data instead of the exact data to the untrusted aggregator. However, it still enables the untrusted aggregator to reconstruct participants’ private data, although parameter updates contain significantly less information than the private data. Existing work either incurs extremely high overhead or ignores malicious participants dropping out. The latest research deals with the dropouts with desirable cost, but it is vulnerable to malformed message attacks. To this end, we focus on the data aggregation based on ML in a practical setting where malicious participants may send malformed parameter updates to perturb the total parameter updates learned by the aggregator. Moreover, malicious participants may drop out and collude with other participants or the untrusted aggregator. In such a scenario, we propose a scheme named DAML , which to the best of our knowledge is the first attempt toward verifying participants’ submissions in data aggregation based on ML. The main idea is to validate participants’ submissions via SSVP, a novel secret-shared verification protocol, and then aggregate participants’ parameter updates using SDA, a secure data aggregation protocol. Simulation results demonstrate that DAML can protect participants’ data privacy with preferable overhead.

Malicious Node Detection in Wireless Sensor Networks Using an Efficient Secure Data Aggregation Protocol

Wireless sensor networks are randomly deployed and responsible for monitoring geographical area wide. In WSN, the aggregation of data is very complex because of its limited power and computing capabilities. Issue in data aggregation is that the data may be passed on malicious node. All the existing data aggregation techniques undergo security issues because of the transfer of large amount of data. In this paper we propose a protocol named Secure Data Aggregation Protocol (SDAP) which identifies the malicious node by providing a logical group in the form of tree topology. In the tree topology the aggregation is formed by aggregating the nodes, which are non-leaf node and high level of trust is required to provide a better approximation and accuracy against the security threats. Thus the data is securely aggregated and the efficiency is achieved in data aggregation.

Fog computing‐based privacy preserving data aggregation protocols

AbstractAs the number of active Internet of Things (IoT) devices increases, managing and securing the enormous amount of data generated by these devices become harder. With their always‐connected smart meters and internet‐enabled electrical appliances, smart grids (SGs) are major data generation sources in IoT. Traditional SGs store and process their collected data in centralized cloud servers. Secure data aggregation (SDA) protocols play an essential role in efficient and private data collection and storage in cloud‐based SGs. Due to a high number of connected devices, centralized cloud‐based SGs may become inadequate to satisfy the processing and storage needs of the collected data. This article introduces two efficient and lightweight SDA protocols for fog computing‐based SGs (FCSG), namely, FCSG‐DF and FCSG‐P, as a complementary solution for processing and storage needs of cloud‐based SGs. By leveraging the distributed nature and other extended capabilities of fog computing, the proposed SDA protocols have a better response time with less computational overhead. Moreover, the privacy of fine‐grained energy consumption data is preserved with the help of the privacy‐preserving data aggregation processes in the hierarchical fog computing structure of FCSG. Extensive performance evaluation results demonstrate that the proposed protocols have superiority in terms of data transmission and storage efficiency compared to cloud‐assisted schemes without data aggregation. Both protocols are analyzed by comparing their success in transmission and storage efficiencies. Moreover, privacy analysis verifies that both protocols effectively ensure the privacy of the data in each layer.

Data Aggregation in Wireless Sensor Networks: From the Perspective of Security

Nodes in wireless sensor networks (WSNs) are usually deployed in an unattended even hostile environment. What is worse, these nodes are equipped with limited battery, storage, computation, and communication resources. Therefore, it is challenging to ensure the security of a WSN without decreasing its network performance. Data aggregation (DA) combined with a security mechanism can provide a good scheme for solving the aforementioned problems. This article presents a comprehensive review of secure DA (SDA) in WSNs, including its security goals together with the existing problems. The traditional network topologies as well as new emerging ones are discussed and compared in order to indicate the application scenes and security levels of different topologies. Meanwhile, the contrastive analyses of security strategies are presented which divides SDA protocols into five categories according to different security mechanisms, security goals, and network topologies. Besides, the discussion points out some open issues which may be the valuable topics of SDA in the future.

Secure Data Aggregation Protocol with Efficient Energy in Sensor Networks

In the current secure data aggregation strategies, decrease within the energy utilization isn't greatly talked about and consolidated answer for both trustworthiness and confirmation isn't tended to. In this paper, we propose to structure an Energy Efficient Secure Data Aggregation Protocol for wireless sensor networks. In this protocol, we fuse the confirmation as well as protection to keep up the productivity of the data aggregation. Initially the network been partitioned into bunches, every group is going through an aggregator also the aggregators are associated with sink each straightforwardly otherwise by different aggregators. The aggregator has been chosen dependent taking place the closest separation toward a lot of sensor hubs as well as its energy level. Detached inputs has been circulated toward the two points i.e., sensor hub to the aggregator as well as aggregator to the sink. At whatever point a sensor hub needs to mail information toward an additional hub; former the sensor hub scrambles the information utilizing a input also mails it toward the aggregator. For honesty of the information parcel, a MAC support confirmation policy is utilized. Reenactment outcome confirm so as to our planned protocol have decreased energy utilization though achieving great bundle conveyance proportion.

Maximizing Network Lifetime using Fuzzy Based Secure Data Aggregation Protocol (FSDAP) in a Wireless Sensor Networks

Abstract: Secure Data Aggregation in Wireless Senor Networks (WSNs) is a challenging issue. The various protocols has been suggested in the recent past such as EDIT[13], ADA[8], TSDA[9], SEDAN[10]. These protocols effectively meet the constraints of WSNs. In this paper, we have proposed a Fuzzy Based Secure Data Aggregation protocol (FSDAP) which is an efficient localized protocol. The FSDAP protocol is designed with three phases. The first phase selects Aggregator Node using ANS algorithm. An ANS algorithm involves two steps to elect an Aggregator Node in the clustered network. In first step, the cluster head is selected based on the Euclidean distance and in second step, the cluster head is selected based on the fuzzy product and fuzzy value (α). Then, in second phase, a selected AN eliminates data redundancy sensed by all sensor nodes within the cluster. Finally, in third phase, the FSDAP protocol effectively detects malicious node and provides secure data transmission path. Thus, the proposed protocol, FSDAP utilizes the node’s resource parameter uniformly, which in turn improves Network Lifetime, maximizes Throughput Rate, maximizes Packet Delivery Ratio and minimizes End-to-End Delay. The FSDAP is simulated using the NS2 simulator and compared with centroid algorithms Fuzzy C-Means and K-Means algorithm and a secure aggregation protocol implemented using SAR (Secure Aware Ad hoc Routing). The time complexity of FSDAP protocol is O(m2n).

A secure and energy-efficient platform for the integration of Wireless Sensor Networks and Mobile Cloud Computing

Wireless Sensor Networks suffer from power and energy consumption issues because the batteries used are small and power-limited. Mobile Cloud Computing suffers from several security threats such as integrity and privacy issues. The integration of both areas results in better energy conservation and a more secure environment. Thus, this research introduces a secure energy-efficient platform that reduces the energy consumption and maintains privacy. The security approach of the platform utilizes a modified version of the Sharing-based Scheme and a Precision-enhanced and Encryption-mixed Privacy-preserving Data Aggregation scheme. The first supports both authentication and encryption using XOR gates, while the second is a slicing, secure data aggregation protocol that enhances both security and energy. For energy consumption reduction, asynchronous scheduling duty cycling based on Location, Priority and Pre-Configuration is introduced. The results show that the platform depends on the rate of sensing, frequency of sending data, data size, location and number of sleeping sensors, and smartphone battery capacity. In the case of less frequent rates and lower data sizes, the operational energy consumption is 1% of the mobile's entire battery capacity. In the case of sensors sleeping next to the sink, the cost is reduced by over 70% with an additional cost of 20% over the un-secured network. The simulations show that the encryption cost decreases as the number of sensors increases. Furthermore, when the number of sensors increase, the distance between the node decreases and therefore more sensors are tending to sleep, which leads to less energy consumption. As a result, the platform introduced in this work outperforms existing schemes for large numbers of sensors (greater than 300 sensors) with an additional average security cost of 2.96%.

Research and Improvement of Wireless Sensor Network Secure Data Aggregation Protocol Based on SMART

The privacy-preserving of information is one of the most important problems to be solved in wireless sensor network (WSN). Privacy-preserving data aggregation is an effective way to protect security of data in WSNs. In order to deal with the problem of energy consumption of the SMART algorithm, we present a new dynamic slicing D-SMART algorithm which based on the importance degree of data. The proposed algorithm can decrease the communication overhead and energy consumption effectively while provide good performance in preserving privacy by the reasonable slicing based on the importance degree of the collected raw data. Simulation results show that the proposed D-SMART algorithm improve the aggregation accuracy, enhance the privacy-preserving, reduce the communication overhead to some extent, decrease the energy consumption of sensor node and prolong the network lifetime indirectly.

Unfailing secure data aggregation protocol in wireless sensor networks

Unfailing secure data aggregation protocol in wireless sensor networks

Secure data aggregation using access control and authentication for wireless sensor networks

The existing secure data aggregation approaches for wireless sensor networks were not designed for authorization, energy efficiency and proper security, leaving them prone to attacks. In this paper, we introduce the secure data aggregation using the access control and authentication (SDAACA) protocol. Using this protocol, we aim to detect sinkhole and Sybil attacks that are difficult to detect by existing cryptographic approaches. The proposed SDAACA protocol consists of two novel algorithms: the secure data fragmentation (SDF) and the node joining authorization (NJA). The SDF algorithm hides the data from the adversary by fragmenting it into small pieces. In the NJA algorithm, an authorization process is initiated before allowing any new node to join the network. Both algorithms help improve the Quality of Service (QoS) parameters. Moreover, we propose an access control scheme that supports accuracy, energy efficiency, freshness and authentication by reducing the communication overhead and guaranteeing the communication authenticity process. Furthermore, the proposed protocol is mapped on the oil-refinery plant to prevent and detect both sinkhole and Sybil attacks in the presence of static and mobile sensor nodes. Finally, we show the effectiveness of our proposed protocol through extensive simulations and a comparative study of other known secure data aggregation protocols.

Detecting Wormhole Attack on Data Aggregation in Hierarchical WSN

Wireless networks are used by everyone for their convenience for transferring packets from one node to another without having a static infrastructure. In WSN, there are some nodes which are light weight, small in size, having low computation overhead, and low cost known as sensor nodes. In literature, there exists many secure data aggregation protocols available but they are not sufficient to detect the malicious node. The authors require a better security mechanism or a technique to secure the network. Data aggregation is an essential paradigm in WSN. The idea is to combine data coming from different source nodes in order to achieve energy efficiency. In this paper, the authors proposed a protocol for worm hole attack detection during data aggregation in WSN. Main focus is on wormhole attack detection and its countermeasures.

Novel dynamic data aggregation scheme for WSN based intelligent vehicle systems

The data aggregation with multi-resources traffic information is a very important issue for intelligent vehicle systems (IVS). It can not only collect the most critical data from the traffic environment, but also prevent sensor network congestion. Unfortunately, we so far have no suitable solutions for WSN based IVSs. This paper presents an efficient approach for traffic data aggregation, applied in IVSs. At first, our approach adopts a hybrid network structure which is the combination of the chain structure and the unequal clusters structure. In this structure, all sensor nodes from the same cluster use parameters such as leading code and geographical position etc. to guarantee secure data aggregation. Furthermore, a method is introduced depending on creditability evaluation and reliability allocation so that the application layer can calculate aggregation results accurately, and then makes the decisions. Finally, the performance of the proposed scheme has been verified using simulation, showing that it is superior to similar protocol VLEACH (an improvement on LEACH) and ESDA (Efficient and Secure Data Aggregation protocol) such as the sensor nodes energy consumption and aggregation precision. The analysis result indicates that our scheme is effective and feasible in the next generation of sensor technologies of ITSs.

Secure End to End Data Aggregation using Public Key Encryption in Wireless Sensor Network

Wireless Sensor Networks is made of a large number of lowcost and low power sensor nodes that contains strictly limited sensing, computation, as well as communication abilities. Because of resource restricted sensor nodes, it is very important to reduce the amount of data transmission so the average sensor lifespan and also the total bandwidth utilization are generally increased. Data aggregation is the process of summarizing and merging sensor data to be able to minimize the number of data transmission in the network. Cluster based Data Aggregation approach, the data sensed by the sensor nodes are transferred to the cluster head and in the cluster head performs data aggregation and forwards results to the sink. Data aggregation could conserve energy (power) as well as bandwidth of the networks. As wireless sensor networks are generally used in remote and hostile environments in order to transfer very sensitive information, sensor nodes are susceptible to node compromise attacks and security problems such as data confidentiality and integrity are extremely crucial. Therefore, Secure Data aggregation protocol, must be designed with security in mind and investigates the relationship between security and data aggregation process within wireless sensor networks. In this paper, the secure data aggregation schemes are categorized into hop by hop aggregation and end to end aggregation. Here we explore a Homomorphic aggregation system based on a public key encryption (PKE) scheme to protect sensor data secure is proposed. Security analysis shows that our proposed protocol can guarantee end-to-end confidentiality and privacy. General Terms Secure Data Aggregation, WSN, Privacy Homomorphism(PH).

A Secure Routing Protocol for Wireless Sensor Networks Considering Secure Data Aggregation.

The commonly unattended and hostile deployments of WSNs and their resource-constrained sensor devices have led to an increasing demand for secure energy-efficient protocols. Routing and data aggregation receive the most attention since they are among the daily network routines. With the awareness of such demand, we found that so far there has been no work that lays out a secure routing protocol as the foundation for a secure data aggregation protocol. We argue that the secure routing role would be rendered useless if the data aggregation scheme built on it is not secure. Conversely, the secure data aggregation protocol needs a secure underlying routing protocol as its foundation in order to be effectively optimal. As an attempt for the solution, we devise an energy-aware protocol based on LEACH and ESPDA that combines secure routing protocol and secure data aggregation protocol. We then evaluate its security effectiveness and its energy-efficiency aspects, knowing that there are always trade-off between both.

A novel secure aggregation scheme for wireless sensor networks using stateful public key cryptography

Wireless sensor networks (WSNs) are nowadays considered as an important part of the Internet of Things (IoT). In these networks, data aggregation plays an essential role in energy preservation. However, WSNs are usually deployed in hostile and unattended environments (e.g. military applications) in which the confidentiality and integrity security services are widely desired. Recently, homomorphic encryptions have been applied to conceal sensitive information during aggregation such that algebraic operations are done directly on ciphertexts without decryption. The main benefit is that they offer the end-to-end data confidentiality and they do not require expensive computation at aggregator nodes since no encryption and decryption are performed. However, existing solutions either incur a considerable overhead or have limited applicability to certain types of aggregate queries. This paper presents a novel secure data aggregation protocol for WSNs. The scheme employs Stateful Public Key Encryption (StPKE) and some previous techniques in order to provide an efficient end-to-end security. Moreover, our solution does not impose any bound on the aggregation function’s nature (Maximum, Minimum, Average, etc.). We present and implement our scheme on TelosB as well as MicaZ sensor network platforms and measure the execution time of our various cryptographic functions. Simulations are also conducted to show how our scheme can achieve a high security level (by providing the above security services) with a low overhead (in terms of computation and communication) in large-scale scenario.