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Part of: Synthesis digital library of engineering and computer science.

Includes bibliographical references (pages 113-124).

1. Introduction -- 1.1 Wireless sensing devices and wireless sensor networks -- 1.2 Sensor cloud -- 1.2.1 Sensor cloud layered architecture -- 1.2.2 Virtual sensors -- 1.2.3 Sensor cloud delivery models -- 1.3 Secure sensor cloud --

2. Preliminaries -- 2.1 Security risk assessment -- 2.1.1 Risk assessment methodologies -- 2.2 Cryptographic operations -- 2.2.1 Homomorphic encryption -- 2.2.2 Paillier encryption -- 2.2.3 Elliptic curve cryptography -- 2.2.4 Key policy attribute-based encryption -- 2.2.5 Proxy re-encryption -- 2.3 Other mathematical primitives -- 2.3.1 Bilinear maps -- 2.3.2 Shamir's secret sharing -- 2.3.3 Bloom filter --

3. Sensor cloud architecture and implementation -- 3.1 Virtual sensors -- 3.2 Sensor cloud architecture -- 3.2.1 Client-centric layer -- 3.2.2 Middleware layer -- 3.2.3 Sensor-centric layer -- 3.3 Software design -- 3.4 QoS in sensor cloud -- 3.5 Implementation -- 3.5.1 System setup -- 3.5.2 Middleware implementation details -- 3.5.3 Backend base station server implementation details -- 3.5.4 Data streaming for multi-user environment -- 3.5.5 Virtual sensor implementation -- 3.5.6 Time model for virtual sensors -- 3.6 Summary --

4. Risk assessment in a sensor cloud -- 4.1 Introduction -- 4.2 Risk assessment framework for WSN in a sensor cloud -- 4.2.1 Attack graphs for wireless sensor networks -- 4.2.2 Quantitative risk assessment by modeling attack graphs using Bayesian networks -- 4.2.3 Time frame estimations -- 4.3 Use case scenario depicting the risk assessment framework -- 4.3.1 Attack graph for confidentiality -- 4.3.2 Time frame estimations -- 4.4 Discussions -- 4.4.1 Complexity analysis and scalability -- 4.4.2 Risk assessment vs. intrusion detection systems -- 4.5 Summary --

5. Secure aggregation of data in a sensor cloud -- 5.1 Introduction -- 5.2 Related work -- 5.3 Secure hierarchical data aggregation algorithm -- 5.3.1 Modified ECDSA signature algorithm -- 5.3.2 EC Elgamal encryption -- 5.4 Privacy and integrity preserving data aggregation (PIP) -- 5.4.1 The PIP algorithm -- 5.4.2 Numerical example -- 5.5 Summary --

6. Access control of aggregated data in sensor clouds -- 6.1 Introduction -- 6.2 Related work -- 6.3 Models -- 6.3.1 System model -- 6.3.2 Adversary model -- 6.4 Access control policy -- 6.5 Overview of the scheme -- 6.6 Access control scheme -- 6.6.1 System setup -- 6.6.2 Access control secret key generation -- 6.6.3 Data aggregation key generation -- 6.6.4 Data aggregation key establishment -- 6.6.5 Data aggregation -- 6.7 Discussion -- 6.8 Revocation of users -- 6.9 Modifying access at runtime -- 6.9.1 Encryption scheme for modifying access at runtime -- 6.9.2 Protocol for modifying access at runtime -- 6.10 Security analysis -- 6.11 Summary --

7. Efficient and secure code dissemination in sensor clouds -- 7.1 Introduction -- 7.2 Related work -- 7.3 System model and assumptions -- 7.4 Proposed approach -- 7.5 The EC-BBS proxy re-encryption scheme -- 7.6 Detecting common functions -- 7.7 Proposed algorithm -- 7.7.1 Pre-deployment phase -- 7.7.2 Pre-dissemination -- 7.7.3 Code dissemination -- 7.7.4 Activity on the nodes -- 7.8 A discussion on security -- 7.8.1 Confidentiality of code -- 7.8.2 Integrity of code -- 7.9 Summary --

Bibliography -- Authors' biographies.

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The sensor cloud is a new model of computing paradigm for Wireless Sensor Networks (WSNs), which facilitates resource sharing and provides a platform to integrate different sensor networks where multiple users can build their own sensing applications at the same time. It enables a multi-user on-demand sensory system, where computing, sensing, and wireless network resources are shared among applications. Therefore, it has inherent challenges for providing security and privacy across the sensor cloud infrastructure. With the integration of WSNs with different ownerships, and users running a variety of applications including their own code, there is a need for a risk assessment mechanism to estimate the likelihood and impact of attacks on the life of the network. The data being generated by the wireless sensors in a sensor cloud need to be protected against adversaries, which may be outsiders as well as insiders. Similarly, the code disseminated to the sensors within the sensor cloud needs to be protected against inside and outside adversaries. Moreover, since the wireless sensors cannot support complex and energy-intensive measures, the lightweight schemes for integrity, security, and privacy of the data have to be redesigned. The book starts with the motivation and architecture discussion of a sensor cloud. Due to the integration of multiple WSNs running user-owned applications and code, the possibility of attacks is more likely. Thus, next, we discuss a risk assessment mechanism to estimate the likelihood and impact of attacks on these WSNs in a sensor cloud using a framework that allows the security administrator to better understand the threats present and take necessary actions. Then, we discuss integrity and privacy preserving data aggregation in a sensor cloud as it becomes harder to protect data in this environment. Integrity of data can be compromised as it becomes easier for an attacker to inject false data in a sensor cloud, and due to hop by hop nature, privacy of data could be leaked as well. Next, the book discusses a fine-grained access control scheme which works on the secure aggregated data in a sensor cloud. This scheme uses Attribute Based Encryption (ABE) to achieve the objective. Furthermore, to securely and efficiently disseminate application code in sensor cloud, we present a secure code dissemination algorithm which first reduces the amount of code to be transmitted from the base station to the sensor nodes. It then uses Symmetric Proxy Re-encryption along with Bloom filters and Hashbased Message Authentication Code (HMACs) to protect the code against eavesdropping and false code injection attacks.

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Title from PDF title page (viewed on January 3, 2019).