Adversarial Nodes Research Articles

Cognisseum: Cognitive radios on Colosseum facing adversaries

Cognitive radio technology brings a lot of interesting features which affect the transmission and reception properties of modern communication devices. Dynamic spectrum sensing, channel hopping and allocation, and software-based control are among the many. The new features allow strategic defense mechanisms while also enabling more capable adversarial attacks. In this work, we study coalitions of secondary users (SUs) against adversaries. In the presence of primary users (PUs), we inspect the behavior of SU pairs in cognitive radio networks, before and after adversarial attacks. We propose algorithms for forming coalitions among SU pairs. We consider two attack strategies for the adversaries: smart or naïve. We study how the channels are allocated if there is an attack and how the payoffs of those SU pairs vary with varying number of channels. We also show the effects of attack from the attackers’ point-of-view and how the attack strategy changes if the adversaries act smart vs. naïve. Using Colosseum, a large-scale wireless channel emulator, we construct a functional cognitive radio network and use its software-defined radio (SDR) hardware as SU and adversarial nodes. Using this setup, we run experiments and record data by running network performance measurement tool iPerf3 for various coalitional setups.

Brand Network Booster: A new system for improving brand connectivity

This paper presents a new decision support system offered for an in-depth analysis of semantic networks, which can provide insights for a better exploration of a brand’s image and the improvement of its connectivity. In terms of network analysis, we show that this goal is achieved by solving an extended version of the Maximum Betweenness Improvement problem, which includes the possibility of considering adversarial nodes, constrained budgets, and weighted networks – where connectivity improvement can be obtained by adding links or increasing the weight of existing connections. Our contribution includes a new algorithmic framework and the integration of this framework into a software system called Brand Network Booster (BNB), which supports brand connectivity evaluation and improvement. We present this new system together with three case studies, and we also discuss its performance. Our tool and approach are valuable to both network scholars and in facilitating strategic decision-making processes for marketing and communication managers across various sectors, be it public or private.

Adversarial Node Placement in Decentralized Federated Learning: Maximum Spanning-Centrality Strategy and Performance Analysis

Adversarial Node Placement in Decentralized Federated Learning: Maximum Spanning-Centrality Strategy and Performance Analysis

Simultaneous Secure and Covert Transmissions Against Two Attacks Under Practical Assumptions

In practice, Internet-of-Things (IoT) applications may face two different hostile attacks i.e., overhearing the broadcasted data and detecting the presence of data communication. Previous works have assumed that only one of these attacks is present in the network and have addressed these attacks separately. In this paper, we investigate the security of a simple but practical IoT-based point-to-point communication which is facing with the above mentioned two attacks under some realistic assumptions. In other words, we aim to protect the data against two adversary nodes, namely Eve (who tries to capture the broadcasted data) and warden Willie (who tries to detect the presence of data communication between legitimate nodes). To tackle these attacks, we jointly employ the information-theoretic security and covert communication techniques. To hide information from Willies, we force the source to transmit its message in the selected time slot and the multiple-antennas cooperative jammer to inject jamming during all time slots contentiously which leads to deceive Eves and Willies jointly. To enhance the performance of this security design, we formulate an optimization problem, with the goal of maximizing the secrecy rate subject to power constraints at the source and jammer, while satisfying a covert communication requirement. Since the mentioned optimization problem is non-convex, we propose an algorithm to solve it. Then to obtain further insights, we extend our proposed system model to non-colluding and colluding Willies. Next, we study a practical communication scenario, where the source has uncertainty about Willie’s location and knows the channel state information (CSI) of Eves imperfectly. Our numerical results highlight that a more accurate estimation of Willie’s location has a more positive efficacy on the secrecy performance compared to the case with a more accuracy of Eves’ CSI estimation.

MWPoW+: A Strong Consensus Protocol for Intra-Shard Consensus in Blockchain Sharding

Blockchain sharding splits a blockchain into several shards where consensus is reached at the shard level rather than over the entire blockchain. It improves transaction throughput and reduces the computational resources required of individual nodes. But a derivation of trustworthy consensus within a shard becomes an issue as the longest chain based mechanisms used in conventional blockchains can no longer be used. Instead, a vote-based consensus mechanism must be employed. However, existing vote-based Byzantine fault tolerance consensus protocols do not offer sufficient security guarantees for sharded blockchains. First, when used to support consensus where only one block is allowed at a time (binary consensus), these protocols are susceptible to progress-hindering attacks (i.e., unable to reach a consensus). Second, when used to support a stronger type of consensus where multiple concurrent blocks are allowed (strong consensus), their tolerance of adversary nodes is low. This article proposes a new consensus protocol to address all these issues. We call the new protocol MWPoW +, as its basic framework is based on the existing Multiple Winners Proof of Work (MWPoW) protocol but includes new mechanisms to address the issues mentioned previously. MWPoW+ is a vote-based protocol for strong consensus, asynchronous in consensus derivation but synchronous in communication. We prove that it can tolerate up to f < n /2 adversary nodes in a n-node system as if using a binary consensus protocol and does not suffer from progress-hindering attacks.

Region Centric GL Feature Approximation Based Secure Routing for Improved QoS in MANET

Secure routing in Mobile Adhoc Network (Manet) is the key issue now a day in providing secure access to different network services. As mobile devices are used in accessing different services, performing secure routing becomes a challenging task. Towards this, different approaches exist which find the trusted route based on their previous transmission details and behavior of different nodes. Also, the methods focused on trust measurement based on tiny information obtained from local nodes or with global information which are incomplete. However, the adversary nodes are more capable and participate in each transmission not just to steal the data also to generate numerous threats in degrading QoS (Quality of Service) parameters like throughput, packet delivery ratio, and latency of the network. This encourages us in designing efficient routing scheme to maximize QoS performance. To solve this issue, a two stage trust verification scheme and secure routing algorithm named GL-Trust (Global-Local-Trust) is presented. The method involves in route discovery as like popular AODV (Adaptive On-demand Distance Vector) which upgrades the protocol to collect other information like transmission supported, successful transmissions, energy, mobility, the number of neighbors, and the number of alternate route to the same destination and so on. Further, the method would perform global trust approximation to measure the value of global trust and perform local trust approximation to measure local trust. Using both the measures, the method would select a optimal route to perform routing. The protocol is designed to perform localized route selection when there is a link failure which supports the achievement of higher QoS performance. By incorporating different features in measuring trust value towards secure routing, the proposed GL-Trust scheme improves the performance of secure routing as well as other QoS factors.

Resilient Synchronization of Pulse-coupled Oscillators with Time Continuity

Clock synchronization of wireless sensor networks (WSNs) using pulse-coupled oscillators has been extensively studied. In this paper, we propose a resilient clock synchronization algorithm that can mitigate the influence of adversarial nodes that emit pulses at arbitrary time instants. Under the assumption that a bound on the number of nodes in the network is known, we provide distributed protocols that guarantee continuity of clocks by varying the phase speeds. We illustrate the usefulness of the proposed algorithms by comparing them with a conventional method in a numerical example.

RZee: Cryptographic and statistical model for adversary detection and filtration to preserve blockchain privacy

Preserving anonymity and confidentiality of transactions has become crucial with widespread of the blockchain technology. Despite of the increased efforts for retaining privacy in blockchain networks, invasion attacks are still surfacing. Most of these attacks do not come from outsiders, but from the resident adversarial nodes. Existence of these insider adversaries lead to damaging of an organization’s internal network system and information leakage. Consequently, transaction anonymity and confidentiality are compromised. Hence, adversary detection and filtration play a vital role in protecting networks against unforeseen privacy and security threats. Therefore, in this paper, we propose RZee, a cryptographic and statistical privacy preserving model for adversary detection and filtering in blockchain networks. Firstly, RZee exploits zero-knowledge proofs to cryptographically secure the data. Secondly, based on certain identified conditions, RZee captures node behavior and blacklists malicious nodes to restrict those from injecting harmful data into the chain or viewing transactions as they propagate across the network. This adds an additional layer of protecting transactions from unauthorized and malicious intervention. The proposed framework is evaluated based on various privacy attributes as identified by literature. For this evaluation, 4 different types of experiments have been conducted. Further, the comparison of privacy perseverance of RZee with existing benchmark privacy-preserving frameworks is also done. The results depict that performance and privacy preservation in RZee exceeds the rest with an attribute score of 6.774 and a gain margin of 46.5%.

A Countermeasure Approach for Brute-Force Timing Attacks on Cache Privacy in Named Data Networking Architectures

One key feature of named data networks (NDN) is supporting in-network caching to increase the content distribution for today’s Internet needs. However, previously cached contents may be threatened by side-channel timing measurements/attacks. For example, one adversary can identify previously cached contents by distinguishing between uncached and cached contents from the in-network caching node, namely the edge NDN router. The attacks can be mitigated by the previously proposed methods effectively. However, these countermeasures may be against the NDN paradigm, affecting the content distribution performance. This work studied the side-channel timing attack on streaming over NDN applications and proposed a capable approach to mitigate it. Firstly, a recent side-channel timing attack, designated by brute-force, was implemented on ndnSIM using the AT&T network topology. Then, a multi-level countermeasure method, designated by detection and defense (DaD), is proposed to mitigate this attack. Simulation results showed that DaD distinguishes between legitimate and adversary nodes. During the attack, the proposed DaD multi-level approach achieved the minimum cache hit ratio (≈0.7%) compared to traditional countermeasures (≈4.1% in probabilistic and ≈3.7% in freshness) without compromising legitimate requests.

Covert Communication for Wireless Networks with Full-Duplex Multiantenna Relay

In this work, we investigated a covert communication method in wireless networks, which is realized by multiantenna full-duplex single relay. In the first stage, the source node sends covert messages to the relay, and the relay uses a single antenna to send interference signals to the adversary node to protect the covert information being transmitted. In the second stage, the relay decodes and forwards the covert information received in the first stage; at the same time, the relay uses zero-forcing beamforming to send interference signals to the warden to ensure covert transmission. The detection error rate, transmission outage probability, maximum effective covert rate, and other performance indicators are derived in two stages, and the total performance of the system is derived and analyzed. Then, the performance indicators are verified and analyzed by simulation. Our analysis shows that the maximum effective covert rate of using the characteristics of multiantenna to interfere with Willie in the second stage is taken as the total covert performance of the system, and the transmission interruption probability is significantly less than that of the first stage, so the corresponding maximum effective concealment efficiency will be greater.

Block diffusion delay attack and its countermeasures in a Bitcoin network

SummaryIn the Bitcoin system, transactions and their collections (i.e., blocks) are distributed over a peer‐to‐peer (P2P) network (i.e., Bitcoin network) constructed by participating nodes. Each node maintains a distributed ledger (i.e., blockchain) consisting of retrieved blocks. Therefore, speedy block distribution over the Bitcoin network is essential for all nodes to reach a global consensus on the blockchain. On the other hand, Bitcoin clients are developed as open source software, and thus they can be modified by malicious users. Existing work has pointed out that an attacker can delay the block propagation between neighboring nodes by exploiting the regular timeout mechanism for unexpected slow block transfer caused by temporal network trouble. In this paper, we focus on block diffusion delay attacks, where multiple attackers collude with a specific miner (i.e., a special node that creates new blocks and broadcasts these blocks to the other miners) to disturb the propagation of blocks generated by competing miners. Through simulation experiments, we first reveal that about 30% of honest nodes cannot normally retrieve a block when there are only 1% of the nodes in the system are high‐degree adversary nodes in the system. This indicates that the malicious miner colluding with the attackers can intentionally delay the diffusion of the block mined by the competing miner, so as to win the competitive block diffusion even if it loses at the competitive block mining. To alleviate the block diffusion delay attack, we propose two kinds of countermeasures: a proactive approach that is a speedy recovery method from the interruption by adjusting the timeout value and a reactive approach that is a block retrieval node selection method based on the past download rate from each neighbor. Through simulation experiments, we show the countermeasures can effectively alleviate the risk.

Survey on Approaches to Detect Sinkhole Attacks in Wireless Sensor Networks

Due to the wide range of applications in public and military domains, wireless sensor network (WSN) is evolving as a popular technology. This WSN consists of a large number of sensors that are spread across a geographical area thatare self-configuring in nature. These nodes are of low cost and resource-constrained nodes. Because these reasons the network becomes vulnerable to many network attacks. There are many types of attacks among which one of the serious attacks is the sinkhole attack, which is one of the destructive routing attacks. It causes the adversary node to attract all or most of the traffic from the neighbors by broadcasting false routing updates of having the shortest path to the central station. This paper is a survey on various methods implemented to overcome sinkhole attacks like Hop Count Monitoring scheme, Key Management Approach, Message-Digest Algorithm.

Robust coordination in adversarial social networks: From human behavior to agent-based modeling

AbstractDecentralized coordination is one of the fundamental challenges for societies and organizations. While extensively explored from a variety of perspectives, one issue that has received limited attention is human coordination in the presence of adversarial agents. We study this problem by situating human subjects as nodes on a network, and endowing each with a role, either regular (with the goal of achieving consensus among all regular players), or adversarial (aiming to prevent consensus among regular players). We show that adversarial nodes are, indeed, quite successful in preventing consensus. However, we demonstrate that having the ability to communicate among network neighbors can considerably improve coordination success, as well as resilience to adversarial nodes. Our analysis of communication suggests that adversarial nodes attempt to exploit this capability for their ends, but do so in a somewhat limited way, perhaps to prevent regular nodes from recognizing their intent. In addition, we show that the presence of trusted nodes generally has limited value, but does help when many adversarial nodes are present, and players can communicate. Finally, we use experimental data to develop computational models of human behavior and explore additional parametric variations: features of network topologies and densities, and placement, all using the resulting data-driven agent-based (DDAB) model.

An end to end key establishment scheme for detecting black hole attacks in mobile ad hoc networks

<p>The wireless technology is in consistent and rapid development in this century such that it produces fast data rate and strong connectivity. Mobile ad hoc network (MANET) is an independent network wherein nodes function as both host and router. Routing protocols in MANET are prone to different attacks. Malicious nodes usually interfere the process of establishing routes and make it hard to build a valid route. In the literature, different mechanisms proposed to prohibit black hole attacks in which an adversary node blindly drops data packets. In this paper, a study is fulfilled of the advantages and disadvantages of some of the protocols presented in the literature and a novel method proposed that detects black hole attacks. A thorough, precise, and theoretical analysis is presented to show how the proposed method can prevent malicious nodes from impersonating benign nodes. A theoretical compareison conducted between the proposed method and some of the other methods presented in the literature. The comparison shows that the attacks exist on these protocols are detected and prevented by the proposed protocol.</p>

Verifiable Computing Applications in Blockchain

From weak clients outsourcing computational tasks to more powerful machines, to distributed blockchain nodes needing to agree on the state of the ledger in the presence of adversarial nodes, there is a growing need to efficiently verify the results of computations delegated to untrusted third parties. Verifiable computing is a new and interesting research area that addresses this problem. Recently, new applications of verifiable computing techniques have emerged in blockchain technology for secure key management, sybil-resistance and distributed consensus, and smart contracts, while providing desired performance and privacy guarantees. In this paper, we provide an overview of common methods for verifying computation and present how they are applied to blockchain technology. We group the presented verifiable computing applications into five main application areas, i.e., multiparty approval for secure key management, sybil-resistance and consensus, smart contracts and oracles, scalability, and privacy. The main contribution of this survey is to answer two research questions: 1) what are the main application areas of verifiable computing in blockchain technology, and 2) how are verifiable computing techniques used in major blockchain projects today.

Event-Triggered Resilient Average Consensus With Adversary Detection in the Presence of Byzantine Agents

This paper addresses the problem of resilient average consensus in the presence of Byzantine agents in multi-agent networks. An event-triggered secure acceptance and broadcasting algorithm is proposed in which full knowledge of the network and high computational capabilities of each regular node are not required. The computational expense and communication times are also reduced for the event-triggered mechanism. We analyze the conditions for such a fully distributed algorithm to succeed in the f-local adversarial model. A new definition called an f-propagation graph, which is extended from r-robustness, turns out to be more accurate in describing the required topology conditions. Based on the proposed algorithm and topology conditions, we provide another algorithm to detect the adversarial nodes according to their abnormal behavior. When the network topology is an f-propagation graph, regular nodes that are equipped with the proposed algorithms update state values synchronously and eventually converge asymptotically to resilient average consensus. Simulation results are provided to verify the effectiveness of our proposed algorithms and the network topology conditions.

Rethinking Blockchains in the Internet of Things Era from a Wireless Communication Perspective

Due to the rapid development of Internet of Things (IoT), a massive number of devices are connected to the Internet. For these distributed devices in IoT networks, how to ensure their security and privacy becomes a significant challenge. The blockchain technology provides a promising solution to protect the data integrity, provenance, privacy, and consistency for IoT networks. In blockchains, communication is a prerequisite for participants, which are distributed in the system, to reach consensus. However, in IoT networks, most of the devices communicate through wireless links, which are not always reliable. Hence, the communication reliability of IoT devices influences the system security. In this article, we rethink the roles of communication and computing in blockchains by accounting for communication reliability. We analyze the tradeoff between communication reliability and computing power in blockchain security, and present a lower bound to the computing power that is needed to conduct an attack with a given communication reliability. Simulation results show that adversarial nodes can succeed in tampering a block with less computing power by hindering the propagation of blocks from other nodes.

Tactical approach to identify and quarantine spurious node participation request in sensory application

Securing Wireless Sensor Network (WSN) from variable forms of adversary is still an open end challenge. Review of diversified security apprroaches towards such problems that they are highly symptomatic with respect to resiliency strength against attack. Therefore, the proposed system highlights a novel and effective solution that is capable of identify the spurios request for participating in teh network building process from attacker and in return could deviate the route of attacker to some virtual nodes and links. A simple trust based mechanism is constructed for validating the legitimacy of such request generated from adversary node. The proposed system not only presents a security solution but also assists in enhancing the routing process significantly. The simulated outcome of the study shows that proposed system offers significantly good energy conservation, satisfactory data forwarding performance, reduced processing time in contrast to existing standard security practices.

A flexible n/2 adversary node resistant and halting recoverable blockchain sharding protocol

SummaryBlockchain sharding is a promising approach to solving the dilemma between decentralization and high performance (transaction throughput) for blockchain. The main challenge of blockchain sharding systems is how to reach a decision on a statement among a subgroup (shard) of people while ensuring the whole population recognizes this statement. Namely, the challenge is to prevent an adversary who does not have the majority of nodes globally but have the majority of nodes inside a shard. Most blockchain sharding approaches can only reach a correct consensus inside a shard with at most n/3 evil nodes in a n node system. There is a blockchain sharding approach which can prevent an incorrect decision to be reached when the adversary does not have n/2 nodes globally. However, the system can be stopped from reaching consensus (become deadlocked) if the adversary controls a smaller number of nodes. In this article, we present an improved Blockchain sharding approach that can withstand n/2 adversarial nodes and recover from deadlocks. The recovery is made by dynamically adjusting the number of shards and the shard size. A performance analysis suggests our approach has a high performance (transaction throughput) while requiring little bandwidth for synchronization.

ANGLE BASED ADVERSARY NODE DETECTION IN WIRELESS SENSOR NETWORKS

Wireless communication with the sensing power makes Wireless Sensor Networks (WSN) profitable now. However, the protection of data through WSN remains a challenge. The difficulties due to the battery life time, data storage space and computation cause the nodes of WSN to compromise. The adversary nodes cause the diversion of data route the base station. Sometimes those nodes may alter the data so that the base station will do misinformed decisions. It becomes difficult to detect and separate the correct nodes to avoid the process of false information passed by the adversary nodes. The security and routing of data is very important in the operation of WSN. A new method is aimed at providing analysis and design of strategy to detect and isolate adversary node in WSNs. The method is Angle Based Adversary Node Detection (ABAD). The threshold value is taken into consideration form the quality of service parameters and the node is decided whether it is a normal or an adversary node. All simulations are achieved in the network simulator tool that uses various scenarios (25 nodes and 50 nodes).