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The large-scale deployment of Mobile Ad hoc Networks (MANETs) requires dealing with the issues like low throughput, end-to-end delay, and energy exhaustion. In order to resolve these issues, a MANET is organized into a hierarchical structure using a suitable clustering scheme. The nodes belonging to a cluster are referred to as the member nodes. One of the member nodes in each cluster is elected as the cluster head based on its characteristics like identity, residual energy, node degree, and mobility. The representative node is assigned all the cluster management responsibilities making it liable to be the main target for the attackers. After having control of a cluster, the Sybil attacker may disrupt various functions of the MANET. This paper proposes a transmission power-controlled approach by which a Sybil attack is capable of violating the functioning of the mobility-based clustering algorithm in MANETs. We have shown that the transmission power-controlled approach can be used to bias the cluster head election process by repeatedly tilting the results in favor of the Sybil attacker node. The supporting simulation results clearly indicate that the proposed Sybil attack considerably increases the probability of the Sybil attacker node becoming the cluster head. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has recently gained significance as a means of connecting various physical devices to the Internet, enabling various innovative applications. However, the security of IoT networks is a significant concern due to the large volume of data generated and transmitted over them. The limited resources of IoT devices, along with their mobility and diverse characteristics, pose significant challenges for maintaining security in routing protocols, such as the Routing Protocol for Low-Power and Lossy Networks (RPL). This lacks effective defense mechanisms against routing attacks, including Sybil and rank attacks. Various techniques have been proposed to address this issue, including cryptography and intrusion-detection systems. The use of these techniques on IoT nodes is limited by their low power and lossy nature, primarily due to the significant computational overhead they involve. In addition, conventional trust-management systems for addressing security concerns need to be improved due to their high computation, memory, and energy costs. Therefore, this paper presents a novel, Lightweight, and Efficient Trust-based Mechanism (LETM-IoT) for resource-limited IoT networks to mitigate Sybil attacks. We conducted extensive simulations in Cooja, the Contiki OS simulator, to assess the efficacy of the proposed LETM-IoT against three types of Sybil attack (A, B, and C). A comparison was also made with standard RPL and state-of-the-art approaches. The experimental findings show that LETM-IoT outperforms both of these in terms of average packet-delivery ratio by 0.20 percentage points, true-positive ratio by 1.34 percentage points, energy consumption by 2.5%, and memory utilization by 19.42%. The obtained results also show that LETM-IoT consumes increased storage by 5.02% compared to the standard RPL due to the existence of an embedded security module. [ABSTRACT FROM AUTHOR]

Routing in wireless sensor networks (WSNs) are based on multi-hop communication in which the messages pass through multiple sensor nodes, and hence routing algorithms must rely on trust relationships between neighboring nodes. The open access nature of WSNs leads to the possibility of nodes becoming compromised and consequently being turned into malicious objects. One such attack on WSNs is the Sybil attack, in which an attacker can take control of a legitimate node or enter a malicious node into the network and create fake identities. Consequently, they can change the behavior of the WSN, such as its routing schema to cause loops or wrong directions to manipulate data and consume the energy of the network, or even target cluster heads. In this paper, we present a novel technique based on IOTA Tangle, a distributed ledger technology, for the detection and prevention of Sybil attacks by protecting routing data. A transaction history on IOTA is maintained for detecting malicious node injection, and IOTA currency is used as a reputation score to prevent malicious nodes and protect the routing table. Even if an attacker gains access to the network, all routing data can be tracked in IOTA Tangle that will alert the base station about this attack. The technique has been simulated and evaluated using a proof-of-concept prototype. [ABSTRACT FROM AUTHOR]

The safety of cloud services within a Trust Model System (TMS) is certainly compromised by a lack of defense against security threats as well as by inaccuracy of the trust results. Our proposed model addresses well-known security threats to the reputation trust model system, and is shown to deal with all possible potential attack threats, such as Sybil, on–off, and collusion attacks, by specifying the identity of users and tracking activities undertaken by them in order to easily track unauthorized consumers or attackers and to provide proof of any kind of data leakage. The TMS can also oversee the authorization of whoever uploads feedback into the system. It can also identify invalid feedback and discard it from the system. The algorithms of the TMS first establish a variety of trust criteria in which trustworthiness is calculated. Then, feedback from the cloud service provider nodes is accepted only according to the rules of the TMS. A consumer's trust value is finally computed using a flexible system capable of guaranteeing a good balance of consumer trust and owners' feedback. Furthermore, a majority of the existing TMS models do not take full account of interaction importance, thus impeding the accuracy of the trust values, a shortcoming that has been rectified in our proposed model. [ABSTRACT FROM AUTHOR]

Online social networks (OSNs) are known to be vulnerable to Sybil Attack, where attackers leverage the openness to create multiple fake identities for launching many malicious activities. In this paper, we define a weighted-strong-social (WSS) graph that integrates the OSN structure and user behavior patterns and propose a novel hybrid graph-based sybil detection approach. The hybrid approach estimates the trustworthiness of users and user pairs based on user behaviors that can be obtained locally and add them to the OSN structure to construct a WSS graph for sybil detection. The evaluation results show that the AUC of the hybrid approach is 0.954, which is significantly higher than that of previous sybil detection methods. [ABSTRACT FROM AUTHOR]

Cyber Physical System (CPS) links physical world with virtual world of information processing through sensors and actuators. CPS is advanced smart and intelligent embedded system to construct it a combination of different engineering competencies is required, spanning the technical domain as well as corresponding application sectors.CPS and Internet of Things (IoT) have significant overlaps. CPSs have strong emphasis on the integration of computation, communication and the physical world. These systems entrust our significant infrastructure and have the ability to impact our life as these are emerging with smart services. Besides, elevated use of CPS comes up with more threats outcome of which could major consequences for users. Huge research is going in this area including vulnerabilities, reliability, communication model, control system model, threats and security. One of the crucial facets of these issues is privacy and security. Different modules of CPS architecture are vulnerable to different threats that can be used by attackers to exploit the CPS. One of them is Sybil Attack which is used at the communication module of CPS. In this paper we propose a detection scheme against the Sybil Attack unlike the other scheme this scheme works in least time and for each situation. [ABSTRACT FROM AUTHOR]

Reputation mechanisms of a network or p2p applications can be compromised by a large number of fake or stolen identities recommending higher trust values of a malicious node. A high trust value classify such malicious or selfish nodes as legitimate nodes and help them to gain more access to network resource. It is detrimental to network security and makes a network vulnerable to Sybil attacks. In this paper, a game theoretical defense strategy based on zero sum and imperfect information game is proposed to discourage sybil attacks which exploit underlying reputation mechanism of a network. An attacker tries to maintain an optimum level of trusts of its sybil identities in the network in an intention to launch a successful sybil attack and obtain an attack benefit. Simultaneously, the attacker has to incur some cost to maintain trustworthiness of its identities. A rational attacker analyses associated costs and benefits prior to launch an attack. The proposed mechanism uses this idea and makes the attack costly by setting a global trust threshold for nodes or identities to remain trustworthy and active in network. In this work, utility functions of attacker and defender are defined. Nash Equilibrium strategies of the game are discussed and experiments are carried out which suggest the effectiveness of proposed mechanism to enhance network security against sybil attacks. [ABSTRACT FROM AUTHOR]

The huge amount of exchanged data in the internet between entities and the quick development of edge computing has increased users frustration about the future generations. We expect a future where transactions will be based on clouds and virtual machines, gathered from sensors and IoT devices and processed by different artificial intelligence algorithms or agents. The speed and backlash change in the world has driven researchers to work on privacy and security for entities' information and transactions. Different concepts arise and still in their early stage as digital identity, self sovereign identity, global unique identifier and identity of things (IDoT). Therefore, motivated by the recent explosion of interest around Blockchains, we examine whether they make a good fit for the Identity Internet of Things (IDoT) sector. Blockchain a major distributed peer-to-peer network where non-trusting members can interact together without a need for a trusted third party, it actually make available many advantages to providers and consumers and solve data protection features lifelong a transaction existing. As being immutable, transparent and trustful platform the Blockchain allows managing identities and privacy of its nodes information. Our contribution is a new architecture eventually using a public Blockchain and creating a smart identity wallet. It contains standard node data and will also integrate proactive data behavior and the reactive one. The main target is to protect users from sybil attack at early stage. We will define a new digital wallet based on entities behavior in order to prevent 51% attack and Sybil attack [ABSTRACT FROM AUTHOR]

Food wastage is a major problem in today's world and the distribution of food surplus is undoubtedly one of the leading solutions to the problem. Surplus distribution is widely practised across the globe and there are several communities for the same as well. However, the success of these movements are determined by the active participation of volunteers. In addition, volunteer availability is an issue that is dependent on several different factors. An incentive module for the volunteers can normalize the availability of the volunteers. Such incentive modules are prone to identity duplication attacks and the implemented solutions do not really encourage volunteer hierarchical structures. In this paper, an incentive module that resists identity duplication and promotes the hierarchical structure between volunteers is presented. In addition, an improved matching module to match the food donors to the receivers utilizing the available volunteers optimally is also proposed. For the simulation, we have used real data taken from a real life smart city context, namely, we have used the OPEN DATA BARCELONA at https://opendata-ajuntament.barcelona.cat/data/en/dataset/est-cadastre-carrecs-us and cast it to our simulation settings using Python libraries. [Display omitted] • The modified food donor to receiver matching mechanism considers more volunteers. • An incentive mechanism is proposed for the volunteers for better participation. • Two methods for the disbursal of volunteer incentives are proposed. • One of the methods favours the volunteers in terms of a higher incentive amount. • The other method is resistant to identity duplication, thus favouring the system. [ABSTRACT FROM AUTHOR]

Sybil attack is a special kind of attack which is difficult to be detected in Wireless Sensor Network (WSN). So a lightweight detection mechanism based on LEACH-RSSI-ID (LRD) is proposed in this paper. Due to the characteristic of Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol, none of nodes can be the cluster head forever. Meanwhile, in order to consume less energy, both factors which are called the remaining energy of nodes and relative density of nodes are taken into account. Therefore, Sybil attack can be found by analyzing the RSSI-ID tables. Different from the previous detection methods, even though Sybil attack occurs in the initialization phase, the malicious nodes can be detected by sink node. What's more, when each malicious node frequently changes identification, it will be detected in a short time. Through the simulations, it is revealed that the LRD mechanism can detect the Sybil attack with high detection rate and accuracy. [ABSTRACT FROM AUTHOR]

Abstract: Sybil attack is considered one of the most damaged attack that menace structured p2p overlay networks. It's the most sophisticated node active, used for a variety of illicit activities. A key requirement for these activities is the ability of such malicious user to generate a huge number of node identifiers and possibly choose some of them in order to disrupt availability and integrity in such systems. This paper highlights the problem of Sybil attack and presents a Sybil tracking process to deal with such problem. [Copyright &y& Elsevier]

Abstract: As one of the most fundamental problems in open-membership systems, Sybil attack has attracted wide attentions from both industrial and academic fields. Many anonymous communication and censorship-resistant systems have incorporated Sybil defense in their designs based on social networks. This paper proposed two-class undirected mixed membership stochastic blockmodels to discover adversary's Sybil identities in the network. Different from existing algorithms, our model discriminates Sybil nodes by simulating the generative process of social networks. And we gave a matrix B to describe the interaction probability of Sybil and honest nodes, which can be used to observe contaminated situation of the network. The effectiveness of the algorithm is validated by experiments over both simulated and real-world social networks. The method can be also used to further improve the accessibility of anonymous and anti-censorship systems. [Copyright &y& Elsevier]

Sybil attack has been proved effective in mitigating the P2P botnet, but the impacts of some important parameters were not studied, and no model to estimate the effectiveness was proposed. In this paper, taking Kademlia-based botnets as the example, the model which has the upper and lower bound to estimate the mitigating performance of the Sybil attack is proposed. Through simulation, how three important factors affect the performance of the Sybil attack is analyzed, which is proved consistent with the model. The simulation results not only confirm that for P2P botnets in large scale, the Sybil attack is an effective countermeasure, but also imply that the model can give suggestions for the deployment of Sybil nodes to get the ideal performance in mitigating the P2P botnet. [ABSTRACT FROM AUTHOR]

Distributed systems particularly suffer from Sybil attacks, where a malicious user creates numerous bogus nodes to influence the functions of the system. In this letter, we propose a Bloom filter-based scheme, SybilBF, to fight against Sybil attacks. A Bloom filter presents a set of Sybil nodes according to historical behavior, which can be disseminated to at least n·(e-1)/e honest nodes. Our evaluation shows that SybilBF outperforms state of the art mechanisms improving SybilLimit by a factor of (1/e)γ at least. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) networks consume the most bandwidth in the current Internet and file sharing accounts for the majority of the P2P traffic. Thus it is important for a P2P file sharing application to be efficient in bandwidth consumption. Bandwidth consumption as much as downloaded file sizes is inevitable, but those in file search and bad downloads, e.g. wrong, corrupted, or malicious file downloads, are overheads. In this paper, we target to reduce these overheads even in the presence of high volume of malicious users and their bad files. Sybil attacks are the example of such hostile environment. Sybil attacker creates a large number of identities (Sybil nodes) and unfairly influences the system. When a large portion of the system is subverted, either in terms of the number of users or the number of files shared in the system, the overheads due to the bad downloads rapidly increase. We propose ELiSyR, a file search protocol that can tolerate such a hostile environment. ELiSyR uses social networks for P2P file search and finds benign files in 71% of searches even when more than half of the users are malicious. Furthermore, ELiSyR provides similar success with less bandwidth than other general efforts against Sybil attacks. We compare our algorithm to SybilGuard, SybilLimit and EigenTrust in terms of bandwidth consumption and the likelihood of bad downloads. Our algorithm shows lower bandwidth consumption, similar chances of bad downloads and fairer distribution of computation loads than these general efforts. In return, our algorithm takes more rounds of search than them. However the time required for search is usually much less than the time required for downloads, so the delay in search is justifiable compared to the cost of bad downloads and subsequent re-search and downloads. [ABSTRACT FROM AUTHOR]

As there is no central authority in a distributed network, Thus an agent lacks sufficient global knowledge, and it is difficult to evaluate the degree of trust on an agent. After consideration on synthetic reputation value in the nature of globalization and objectivity and trust value in the nature of localization and subjectivity, in dealing with problems a new trust evaluation model called the four rule model is proposed. This model contains the reputation computing rule, trust recommendation rule, reputation weight rule and trust computing rule. And the paper compares this model with the attack-resistant trust metrics model in the aspect of security. Theoretical analysis and simulation experiment showed that the proposed model is more robust on trust security problems. [ABSTRACT FROM AUTHOR]

Vehicular Ad Hoc Networks (VANETs) are expected to play an important role in our lives. They will improve traffic safety and bring a revolution on the driving experience. However, these benefits are counterbalanced by possible attacks that threaten not only the vehicle's security, but also passengers lives. One of the most common ones is the Sybil attack, which is more dangerous than others since it could be the starting point of many other attacks in VANETs. This paper proposes a distributed approach allowing the detection of Sybil attacks using the traffic flow theory. The key idea here is that each vehicle will monitor its neighbourhood in order to detect an eventual Sybil attack. This is achieved by comparing between the real accurate speed of the vehicle and the one estimated using the V2V communications with vehicles in the vicinity. This estimated speed is obtained using the traffic flow fundamental diagram of the road's portion where the vehicles are moving. A mathematical model that evaluates the rate of Sybil attack detection according to the traffic density is proposed. Then, this model is validated through some extensive simulations conducted using the well-known NS3 network simulator together with SUMO traffic simulator. [ABSTRACT FROM AUTHOR]