Malicious Node Identification in Coded Distributed Storage Systems under Pollution Attacks

In coding-based distributed storage systems (DSSs), a set of storage nodes (SNs) hold coded fragments of a data unit that collectively allow one to recover the original information. It is well known that data modification (a.k.a. pollution attack) is the Achilles’ heel of such coding systems; indeed, intentional modification of a single coded fragment has the potential to prevent the reconstruction of the original information because of error propagation induced by the decoding algorithm. The challenge we take in this work is to devise an algorithm to identify polluted coded fragments within the set encoding a data unit and to characterize its performance. To this end, we provide the following contributions: (i) We devise MIND (Malicious node IdeNtification in DSS), an algorithm that is general with respect to the encoding mechanism chosen for the DSS, it is able to cope with a heterogeneous allocation of coded fragments to SNs, and it is effective in successfully identifying polluted coded fragments in a low-redundancy scenario; (ii) We formally prove both MIND termination and correctness; (iii) We derive an accurate analytical characterization of MIND performance (hit probability and complexity); (iv) We develop a C++ prototype that implements MIND to validate the performance predictions of the analytical model. Finally, to show applicability of our work, we define performance and robustness metrics for an allocation of coded fragments to SNs and we apply the results of the analytical characterization of MIND performance to select coded fragments allocations yielding robustness to collusion as well as the highest probability to identify actual attackers.

On the robustness of three classes of rateless codes against pollution attacks in P2P networks

Rateless codes (a.k.a. fountain codes, digital fountain) have found their way in numerous peer-to-peer based applications although their robustness to the so called pollution attack has not been deeply investigated because they have been originally devised as a solution for dealing with block erasures and not for block modification. In this paper we provide an analysis of the intrinsic robustness of three rateless codes algorithms, i.e., random linear network codes (RLNC), Luby transform (LT), and band codes (BC) against intentional data modification. By intrinsic robustness we mean the ability of detecting as soon as possible that modification of at least one equation has occurred as well as the possibility a receiver can decode from the set of equations with and without the modified ones. We focus on bare rateless codes where no additional information is added to equations (e.g., tags) or higher level protocol are used (e.g., verification keys to pre-distribute to receivers) to detect and recover from data modification. We consider several scenarios that combine both random and targeted selection of equations to alter and modification of an equation that can either change the rank of the coding matrix or not. Our analysis reveals that a high percentage of attacks goes undetected unless a minimum code redundancy is achieved, LT codes are the most fragile in virtually all scenarios, RLNC and BC are quite insensitive to the victim selection and type of alteration of chosen equations and exhibit virtually identical robustness although BC offer a low complexity of the decoding algorithm.

A Novel Privacy-Preserving Mobile-Coverage Scheme Based on Trustworthiness in HWSNs

To solve the problem of security deployment in a hybrid wireless sensor network, a novel privacy-preserving mobile coverage scheme based on trustworthiness is proposed. The novel scheme can efficiently mitigate some malicious attacks such as eavesdropping and pollution and optimize the coverage of hybrid wireless sensor networks (HWSNs) at the same time. Compared with the traditional mobile coverage scheme, the security of data transmission and mobility are considered in the deployment of HWSNs. Firstly, our scheme can mitigate the eavesdropping attacks efficiently utilizing privacy-preserving signature. Then, the trust mobile protocol based on the trustworthiness is used to defend the pollution attacks and improve the security of mobility. In privacy-preserving signature, the hardness of discrete logarithm determines the degree of security of the privacy-preserving signature. The correctness and effectiveness of signature algorithm are proven by the probabilities of the native messages which can be recovered and forged which is negligible. Furthermore, a mobile scheme based on the trustworthiness (MSTW) is proposed to optimize the network coverage and improve the security of mobility. Finally, the simulation compared with a previous algorithm is carried out, in which the communication overhead, computational complexity, and the coverage are given. The result of the simulation shows that our scheme has roughly the same network coverage as the previous schemes on the basis of ensuring the security of the data transmission and mobility.

Cache Pollution Detection Method Based on GBDT in Information-Centric Network

There is a new cache pollution attack in the information-centric network (ICN), which fills the router cache by sending a large number of requests for nonpopular content. This attack will severely reduce the router cache hit rate. Therefore, the detection of cache pollution attacks is also an urgent problem in the current information center network. In the existing research on the problem of cache pollution detection, most of the methods of manually setting the threshold are used for cache pollution detection. The accuracy of the detection result depends on the threshold setting, and the adaptability to different network environments is weak. In order to improve the accuracy of cache pollution detection and adaptability to different network environments, this paper proposes a detection algorithm based on gradient boost decision tree (GBDT), which can obtain cache pollution detection through model learning. Method. In feature selection, the algorithm uses two features based on node status and path information as model input, which improves the accuracy of the method. This paper proves the improvement of the detection accuracy of this method through comparative experiments.

A Secure Protocol against Selfish and Pollution Attacker Misbehavior in Clustered WSNs

Wireless sensor networks (WSNs) have been widely used for applications in numerous fields. One of the main challenges is the limited energy resources when designing secure routing in such networks. Hierarchical organization of nodes in the network can make efficient use of their resources. In this case, a subset of nodes, the cluster heads (CHs), is entrusted with transmitting messages from cluster nodes to the base station (BS). However, the existence of selfish or pollution attacker nodes in the network causes data transmission failure and damages the network availability and integrity. Mainly, when critical nodes like CH nodes misbehave by refusing to forward data to the BS, by modifying data in transit or by injecting polluted data, the whole network becomes defective. This paper presents a secure protocol against selfish and pollution attacker misbehavior in clustered WSNs, known as (SSP). It aims to thwart both selfish and pollution attacker misbehaviors, the former being a form of a Denial of Service (DoS) attack. In addition, it maintains a level of confidentiality against eavesdroppers. Based on a random linear network coding (NC) technique, the protocol uses pre-loaded matrices within sensor nodes to conceive a larger number of new packets from a set of initial data packets, thus creating data redundancy. Then, it transmits them through separate paths to the BS. Furthermore, it detects misbehaving nodes among CHs and executes a punishment mechanism using a control counter. The security analysis and simulation results demonstrate that the proposed solution is not only capable of preventing and detecting DoS attacks as well as pollution attacks, but can also maintain scalable and stable routing for large networks. The protocol means 100% of messages are successfully recovered and received at the BS when the percentage of lost packets is around 20%. Moreover, when the number of misbehaving nodes executing pollution attacks reaches a certain threshold, SSP scores a reception rate of correctly reconstructed messages equal to 100%. If the SSP protocol is not applied, the rate of reception of correctly reconstructed messages is reduced by 90% at the same case.