Suat Ozdemir

Energy-efficient secure pattern based data aggregation for wireless sensor networks

Data aggregation in wireless sensor networks eliminates redundancy to improve bandwidth utilization and energy-efficiency of sensor nodes. This paper presents a secure energy-efficient data aggregation protocol called ESPDA (Energy-Efficient Secure Pattern based Data Aggregation). Unlike conventional data aggregation techniques, ESPDA prevents the redundant data transmission from sensor nodes to cluster-heads. If sensor nodes sense the same data, ESPDA first puts all but one of them into sleep mode and generate pattern codes to represent the characteristics of data sensed by sensor nodes. Cluster-heads implement data aggregation based on pattern codes and only distinct data in encrypted form is transmitted from sensor nodes to the base station via cluster-heads. Due to the use of pattern codes, cluster-heads do not need to know the sensor data to perform data aggregation, which allows sensor nodes to establish secure end-to-end communication links with base station. Therefore, there is no need for encryption/decryption key distribution between the cluster-heads and sensor nodes. Moreover, the use of NOVSF Block-Hopping technique improves the security by randomly changing the mapping of data blocks to NOVSF time slots. Performance evaluation shows that ESPDA outperforms conventional data aggregation methods up to 50% in bandwidth efficiency.

ESPDA: Energy-efficient and Secure Pattern-based Data Aggregation for wireless sensor networks

Secure data transmission and data aggregation are critical in designing cluster-based sensor networks. This paper presents an Energy-efficient and Secure Pattern-based Data Aggregation protocol (ESPDA) for wireless sensor networks. ESPDA is energy and bandwidth efficient because cluster-heads prevent the transmission of redundant data from sensor nodes. ESPDA is also secure because it does not require the encrypted data to be decrypted by cluster-heads to perform data aggregation. In ESPDA, cluster-head first requests sensor nodes to send the corresponding pattern code for the sensed data. If multiple sensor nodes send the same pattern code to the cluster-head, then only one of them is permitted to send the data to the cluster-head. Hence, ESPDA has advantages over the conventional data aggregation techniques with respect to energy, bandwidth efficiency and security. Simulations results show that as data redundancy increases, the amount of data transmitted from sensor nodes to cluster-head decreases up to 45% when compared to conventional algorithms.

SRDA: secure reference-based data aggregation protocol for wireless sensor networks

Data aggregation in wireless sensor networks eliminates data redundancy, thereby improving bandwidth usage and energy utilization. The paper presents a secure data aggregation protocol, called SRDA (secure reference-based data aggregation), for wireless sensor networks. In order to reduce the number of bits transmitted, sensor nodes compare their raw sensed data value with their reference data value and then transfer only the difference data. In addition to reducing the number of transmitted bits, SRDA also establishes secure connectivity among sensor nodes without any online key distribution. The security level of the communication links is gradually increased as packets are transmitted at higher level cluster-heads, since intercepting a packet at higher levels of the clustering hierarchy provides a summary of a large number of transmissions at lower levels. Simulation results show that the proposed protocol yields significant savings in energy consumption while preserving data security.

Functional reputation based reliable data aggregation and transmission for wireless sensor networks

0140-3664/

Integration of false data detection with data aggregation and confidential transmission in wireless sensor networks

see front matter 2008 Elsevier B.V. A doi:10.1016/j.comcom.2008.07.017 * Tel.: +90 312 231 7400x2123; fax: +90 312 230 8 E-mail addresses: suatozdemir@gazi.edu.tr, suatoz In wireless sensor networks, compromised sensor nodes aim to distort the integrity of data by sending false data reports, injecting false data during data aggregation, and disrupting transmission of aggregated data. Previously known trust systems rely on general reputation concept to prevent these attacks. However, this paper presents a novel reliable data aggregation and transmission protocol, called RDAT, which is based on the concept of functional reputation. Protocol RDAT improves the reliability of data aggregation and transmission by evaluating each type of sensor node action using a respective functional reputation. In addition, protocol RDAT employs a fault tolerant Reed–Solomon coding scheme based multi path data transmission algorithm to ensure the reliable data transmission to the base station. The simulation results show that protocol RDAT significantly improves the reliability of the data aggregation and transmission in the presence of compromised nodes. 2008 Elsevier B.V. All rights reserved.

Integrity protecting hierarchical concealed data aggregation for wireless sensor networks

In wireless sensor networks, compromised sensor nodes can inject false data during both data aggregation and data forwarding. The existing false data detection techniques consider false data injections during data forwarding only and do not allow any change on the data by data aggregation. However, this paper presents a data aggregation and authentication protocol, called DAA, to integrate false data detection with data aggregation and confidentiality. To support data aggregation along with false data detection, the monitoring nodes of every data aggregator also conduct data aggregation and compute the corresponding small-size message authentication codes for data verification at their pairmates. To support confidential data transmission, the sensor nodes between two consecutive data aggregators verify the data integrity on the encrypted data rather than the plain data. Performance analysis shows that DAA detects any false data injected by up to T compromised nodes, and that the detected false data are not forwarded beyond the next data aggregator on the path. Despite that false data detection and data confidentiality increase the communication overhead, simulation results show that DAA can still reduce the amount of transmitted data by up to 60% with the help of data aggregation and early detection of false data.

Energy efficient security protocol for wireless sensor networks

In wireless sensor networks, performing data aggregation while preserving data confidentiality and integrity is challenging. Recently, privacy homomorphism-based secure data aggregation schemes have been proposed to seamlessly integrate confidentiality and data aggregation. However, these schemes do not provide data integrity or allow hierarchical data aggregation if more than one encryption key is used in the network. This paper presents a novel integrity protecting hierarchical concealed data aggregation protocol that allows the aggregation of data packets that are encrypted with different encryption keys. In addition, during the decryption of aggregated data, the base station is able to classify the encrypted and aggregated data based on the encryption keys. The proposed data aggregation scheme employs an elliptic curve cryptography-based homomorphic encryption algorithm to offer data integrity and confidentiality along with hierarchical data aggregation.

A Survey of Wormhole-based Attacks and their Countermeasures in Wireless Sensor Networks

Wireless sensor networks consist of many inexpensive wireless nodes, each having sensing capability with some computational and communication power. Asymmetric cryptographic algorithms are not suitable for providing security on wireless sensor networks due to limited computation, power, and storage resources available on sensor nodes. Therefore, the energy-efficient security protocol proposed in this paper uses symmetric cryptographic algorithms to support security. To mitigate the drawbacks of symmetric cryptographic algorithms, the session key is changed dynamically, in addition to employing code-hopping technique in non-blocking OVSF codes.

Concealed Data Aggregation in Heterogeneous Sensor Networks using Privacy Homomorphism

Abstract In wormhole attacks, attackers create a low-latency link between two points in the network. This can be achieved by either compromising two or more sensor nodes of the network or adding a new set of mali-cious nodes to the network. Once the link is established, the attacker collects data packets on one end of the link, sends the data packets using the low-latency link and replays them at the other end. Wormhole attacks result in alterations in network data flow thereby deceiving the base station. Although implementing a wormhole attack is relatively simple, detecting it is not a trivial task as the replayed information is usually valid. This paper focuses on wormhole attacks and presents the state-of-the-art in wormhole attack detection in wireless sensor networks. The existing wormhole detection protocols are presented in detail and, based on the existing research, the open research areas and future research directions in wormhole attack detection are provided.

Secure and reliable data aggregation for wireless sensor networks

Data aggregation is implemented in wireless sensor networks to reduce data redundancy and to summarize relevant and necessary information without requiring all pieces of the data. The benefit of data aggregation can be maximized by implementing it at every data aggregator on the path to the base station. However, data confidentiality requires sensor nodes to encrypt their data prior to transmission. Moreover, once data is encrypted by a sensor node, it should be decrypted at the base station to maintain end-to-end security. This makes the implementation of data aggregation very difficult because data aggregation algorithms require encrypted data to be decrypted. Consequently, data aggregation and secure communication have conflicts in their implementation. To achieve data aggregation and secure communication together, this paper employs privacy homomorphism which offers end-to-end concealment of data and ability to operate on ciphertexts. In the proposed protocol, the computational overhead imposed by the privacy homomorphic encryption functions is tolerated by employing a set of powerful nodes, called AGGNODEs.