Survey on data aggregation based security attacks in wireless sensor network

Wireless sensor network (WSN) has applications in military, health care, environmental monitoring, infrastructure, industrial and commercial applications. The WSN is expected to maintain data integrity in all its network operations. However, due to the nature of wireless connectivity, WSN is prone to various attacks that alter or steal the data exchanged between the nodes. These attacks can disrupt the network processes and also the accuracy of its results. In this survey paper, we have reviewed various attacks available in the literature till date. We have also listed existing methods that focus on data aggregation based security mechanisms in WSN to counter the attacks. We have classified and compared these methods owing to their encryption techniques. This paper intends to support researchers to understand the basic attacks prevalent in WSN and schemes to counter such attacks

State of the art in privacy preservation in video data

Active and Assisted Living (AAL) technologies and services are a possible solution to address the crucial challenges regarding health and social care resulting from demographic changes and current economic conditions. AAL systems aim to improve quality of life and support independent and healthy living of older and frail people. AAL monitoring systems are composed of networks of sensors (worn by the users or embedded in their environment) processing elements and actuators that analyse the environment and its occupants to extract knowledge and to detect events, such as anomalous behaviours, launch alarms to tele-care centres, or support activities of daily living, among others. Therefore, innovation in AAL can address healthcare and social demands while generating economic opportunities. Recently, there has been far-reaching advancements in the development of video-based devices with improved processing capabilities, heightened quality, wireless data transfer, and increased interoperability with Internet of Things (IoT) devices. Computer vision gives the possibility to monitor an environment and report on visual information, which is commonly the most straightforward and human-like way of describing an event, a person, an object, interactions and actions. Therefore, cameras can offer more intelligent solutions for AAL but they may be considered intrusive by some end users. The General Data Protection Regulation (GDPR) establishes the obligation for technologies to meet the principles of data protection by design and by default. More specifically, Article 25 of the GDPR requires that organizations must "implement appropriate technical and organizational measures [...] which are designed to implement data protection principles [...] , in an effective manner and to integrate the necessary safeguards into [data] processing.” Thus, AAL solutions must consider privacy-by-design methodologies in order to protect the fundamental rights of those being monitored. Different methods have been proposed in the latest years to preserve visual privacy for identity protection. However, in many AAL applications, where mostly only one person would be present (e.g. an older person living alone), user identification might not be an issue; concerns are more related to the disclosure of appearance (e.g. if the person is dressed/naked) and behaviour, what we called bodily privacy. Visual obfuscation techniques, such as image filters, facial de-identification, body abstraction, and gait anonymization, can be employed to protect privacy and agreed upon by the users ensuring they feel comfortable. Moreover, it is difficult to ensure a high level of security and privacy during the transmission of video data. If data is transmitted over several network domains using different transmission technologies and protocols, and finally processed at a remote location and stored on a server in a data center, it becomes demanding to implement and guarantee the highest level of protection over the entire transmission and storage system and for the whole lifetime of the data. The development of video technologies, increase in data rates and processing speeds, wide use of the Internet and cloud computing as well as highly efficient video compression methods have made video encryption even more challenging. Consequently, efficient and robust encryption of multimedia data together with using efficient compression methods are important prerequisites in achieving secure and efficient video transmission and storage.This publication is based upon work from COST Action GoodBrother - Network on Privacy-Aware Audio- and Video-Based Applications for Active and Assisted Living (CA19121), supported by COST (European Cooperation in Science and Technology). COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks. Our Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation. www.cost.e

Wireless multimedia sensor networks, security and key management

Wireless Multimedia Sensor Networks (WMSNs) have emerged and shifted the focus from the typical scalar wireless sensor networks to networks with multimedia devices that are capable to retrieve video, audio, images, as well as scalar sensor data. WMSNs are able to deliver multimedia content due to the availability of inexpensive CMOS cameras and microphones coupled with the significant progress in distributed signal processing and multimedia source coding techniques. These mentioned characteristics, challenges, and requirements of designing WMSNs open many research issues and future research directions to develop protocols, algorithms, architectures, devices, and testbeds to maximize the network lifetime while satisfying the quality of service requirements of the various applications. In this thesis dissertation, we outline the design challenges of WMSNs and we give a comprehensive discussion of the proposed architectures and protocols for the different layers of the communication protocol stack for WMSNs along with their open research issues. Also, we conduct a comparison among the existing WMSN hardware and testbeds based on their specifications and features along with complete classification based on their functionalities and capabilities. In addition, we introduce our complete classification for content security and contextual privacy in WSNs. Our focus in this field, after conducting a complete survey in WMSNs and event privacy in sensor networks, and earning the necessary knowledge of programming sensor motes such as Micaz and Stargate and running simulation using NS2, is to design suitable protocols meet the challenging requirements of WMSNs targeting especially the routing and MAC layers, secure the wirelessly exchange of data against external attacks using proper security algorithms: key management and secure routing, defend the network from internal attacks by using a light-weight intrusion detection technique, protect the contextual information from being leaked to unauthorized parties by adapting an event unobservability scheme, and evaluate the performance efficiency and energy consumption of employing the security algorithms over WMSNs

Optimizing Source Anonymity Of Wireless Sensor Networks Against Global Adversary Using Fake Packet Injections

Wireless Sensor Networks WSNs have been utilized for many applications such as tracking and monitoring of endangered species in a national park, soldiers in a battlefield, and many others, which require anonymity of the origin, known as the Source Location Privacy (SLP). The aim of SLP is to prevent unauthorized observers from tracing the source of a real event (an asset) by analyzing the traffic of the network. We develop the following six techniques to provide anonymity: Dummy Uniform Distribution (DUD), Dummy Adaptive Distribution (DAD), Controlled Dummy Adaptive Distribution (CAD), Exponential Dummy Adaptive Distribution (EDAD), Exponential Dummy Adaptive Distribution Plus One (EDADP1), and Exponential Dummy Adaptive Distribution Plus Two (EDADP2). Moreover, an enhanced version of the well-known FitProbRate technique is also developed. The purpose of these techniques is to overcome the anonymity problem against a global adversary model that has the capability of analyzing and monitoring the entire network. We perform an extensive verification of the proposed techniques via simulation, statistical, and visualization approaches. Three analytical models are developed to verify the performance of our techniques: A Visualization model is performed on the simulation data to confirm anonymity. A Neural Network model is developed to ensure that the introduced techniques preserve SLP. In addition, a Steganography model based on statistical empirical data is implemented to validate the anonymity of the proposed techniques. The Simulation demonstrates that the proposed techniques provide a reasonable delay, delivery ratio, and overhead of the real event's packets while keeping a high level of anonymity. Results show that the improved version of FitProbRate massively reduces the number of operations needed to detect the distribution type of a data sequence despite the number of intervals when compared to the original. A comprehensive comparison between EDADP1, EDADP2, and FitProbRate in terms of the average delay, anonymity level, average processing time, Anderson-Darling test, and polluted scenarios is conducted. Results show that all three techniques have a similar performance regarding the average delay and Anderson-Darling test. However, the proposed techniques outperform FitProbRate in terms of anonymity level, average processing time, and polluted scenarios. WSN applications that need privacy can select the suitable proposed technique based on the required level of anonymity with respect to delay, delivery ratio, and overhead