Security in Mobile Wireless Sensor Networks – A Survey <s> I. Intrusion Resilience <s> Unattended Wireless Sensor Networks (UWSNs) are composed of many small resource-constrained devices and operate autonomously, gathering data which is periodically collected by a visiting sink. Unattended mode of operation, deployment in hostile environments and value (or criticality) of collected data are some of the factors that complicate UWSN security. This paper makes two contributions. First, it explores a new threat model involving a mobile adversary who periodically compromises and releases sensors aiming to maximize its advantage and overall knowledge of collected data. Second, it constructs a self-healing protocol that allows sensors to continuously and collectively recover from compromise. The proposed protocol is both effective and efficient, as supported by analytical and simulation results. <s> BIB001 </s> Security in Mobile Wireless Sensor Networks – A Survey <s> I. Intrusion Resilience <s> Wireless Sensor Networks (WSNs) are susceptible to a wide range of attacks due to their distributed nature, limited sensor resources and lack of tamper-resistance. Once a sensor is corrupted, the adversary learns all secrets and (even if the sensor is later released) it is very difficult for the sensor to regain security, i.e., to obtain intrusion-resilience. Existing solutions rely on the presence of an on-line trusted third party, such as a sink, or on the availability of secure hardware on sensors. Neither assumption is realistic in large-scale Unattended WSNs (UWSNs), characterized by long periods of disconnected operation and periodic visits by the sink. In such settings, a mobile adversary can gradually corrupt the entire network during the intervals between sink visits. As shown in some recent work, intrusionresilience in UWSNs can be attained (to a degree) via cooperative self-healing techniques. In this paper, we focus on intrusion-resilience in Mobile Unattended Wireless Sensor Networks (μUWSNs) where sensors move according to some mobility model. We argue that sensor mobility motivates a specific type of adversary and defending against it requires new security techniques. Concretely, we propose a cooperative protocol that - by leveraging sensor mobility - allows compromised sensors to recover secure state after compromise. This is obtained with very low overhead and in a fully distributed fashion. We provide a thorough analysis of the proposed protocol and support it by extensive simulation results. <s> BIB002 </s> Security in Mobile Wireless Sensor Networks – A Survey <s> I. Intrusion Resilience <s> A color image quality assessment (C-IQA) method was proposed based on the primary and fundamental image quality parameters perceived by human vision system. The methods for measuring these parameters were given. A comprehensive image quality assessment model, called as the best quality assessment function for the color image, was established through trials by means of these parameters. The maximum of the function corresponds to the color image with the best quality. The function could be used either in FR-IQA or in NR-IQA. Not only it does not relied to any reference image but also could be used to assess the reference image quality. The method could also be used to acquire the color image with the best quality by means of a reference image through a gray transformation our called Zadeh-X transformation if the reference image quality is not good enough. <s> BIB003
We now turn to the area of intrusion resilience in MWSNs. It is worth mentioning that in this subsection we regard intrusion resilience as that sensors exhibit resistance to attacks by themselves, rather than the other popular intrusion resilient approaches which rely on a trusted third party. In MWSN, while sensors may move according to certain common mobility models (e.g., random walk) within an interest area, the mobile adversary can just occupy a certain area (we will hereafter call it "corruption area") and wait for sensors to come across there. Once a sensor moves to the corruption area, the mobile adversary can compromise its security. As a consequence, it is difficult for the sensor to regain security, i.e., to obtain intrusion-resilience. To solve this problem, the authors in BIB002 proposed a sensor cooperation protocol that allows compromised sensors to recover their secure state after being compromised. In brief, sensors take advantage of mobility and cooperation with peers to regain security even after having been compromised by a read-only adversary which aims to learn as much data as possible. The basic idea of the sensor cooperation protocol (more detailed information can be found in subsection V-A.) is similar with  , BIB001 that sensors receive contributions from their neighbors and use those contributions, along with its current secret state, to compute the next round secret. To distinguish the states of sensors, the sensor sets are divided into three distinct groups: red, yellow and green, defined as follows: • Red: the state of a sensor is red if it is currently within the corruption area. • Yellow: a sensor is yellow if it is not in the corruption area anymore, but the mobile adversary still knows its state (i.e., secret key). • Green: a sensor is green if it has never visited the corruption area, or it was red (or yellow), but is now healed by the cooperation of its neighbors. Let us give an example to explain how a sensor, say s i , in Yellow state can be transformed into Green. At round r+1, s i moves out of the corruption area, but its secret key K r i is still known by the mobile adversary. For simplicity, we assume that s i only receives three contributions φ ). Thus, it is easy to conclude that the healing is successful if at least one of the three contributions is unknown by the mobile adversary that at least one of three neighbors is green. However, the adversary considered in BIB002 is static and passive. It controls a fixed portion of the network deployment area and compromises all sensors moving within it. As a further step based on BIB002 , the authors in BIB003 investigate another envisaged scenario where an active adversary exists. It is active in that it chooses the portion of the deployment area to compromise at each round and aim to compromise various sets of sensors per round. Generally speaking, BIB003 is also based on sensor collaborative protocol addressed in BIB002 . To summarize, in this section we have classified and surveyed various security mechanisms proposed so far for MWSNs. In the next section, we identify a few relevant open questions for future research in this field.