Robust detection of false data injection attacks for data aggregation in an Internet of Things-based environmental surveillance

Yang, Lei; Ding, Chao; Wu, Meng; Wang, Kun

doi:10.1016/j.comnet.2017.05.027

Cited by 49 publications

(34 citation statements)

References 28 publications

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“…Therefore, it is important to have a Intrusion detection system that fulfills two important characteristics: 1) any IDS should not incur significant computational and communication overhead, and 2) IDS should achieve high detection accuracy. In particular, the use of anomaly based detection systems [53] [52] [51] requires more resources than the signature based detection systems while having a tradeoff between detection accuracy and overheads. For instance, anomaly detection is particularly effective against previously unknown attacks, but is expected to incur significant performance overhead.…”

Section: ) Constrained Resources: a Typical Iot Device Hasmentioning

confidence: 99%

A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT

et al. 2020

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Internet of Things (IoT) is a disruptive technology with applications across diverse domains such as transportation and logistics systems, smart grids, smart homes, connected vehicles, and smart cities. Alongside the growth of these infrastructures, the volume and variety of attacks on these infrastructures has increased highlighting the significance of distinct protection mechanisms. Intrusion detection is one of the distinguished protection mechanisms with notable recent efforts made to establish effective intrusion detection for IoT and IoV. However, unique characteristics of such infrastructures including battery power, bandwidth and processors overheads, and the network dynamics can influence the operation of an intrusion detection system. This paper presents a comprehensive study of existing intrusion detection systems for IoT systems including emerging systems such as Internet of Vehicles (IoV). The paper analyzes existing systems in three aspects: computational overhead, energy consumption and privacy implications. Based on a rigorous analysis of the existing intrusion detection approaches, the paper also identifies open challenges for an effective and collaborative design of intrusion detection system for resource-constrained IoT system in general and its applications such as IoV. These efforts are envisaged to highlight state of the art with respect to intrusion detection for IoT and open challenges requiring specific efforts to achieve efficient intrusion detection within these systems.

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Section: ) Constrained Resources: a Typical Iot Device Hasmentioning

confidence: 99%

A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT

et al. 2020

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“…Recent studies in the literature have highlighted the needs of sophisticated IDS to meet security requirements in IoT environments [3,[7][8][9][10]. In a nutshell, IDSs aim to identify attack behavior and locate an attacker within a system [3].…”

Section: Related Workmentioning

confidence: 99%

“…Watchdog is one of most traditional techniques applied to monitor networked system [19]. The authors in [10] proposed an IDS based on watchdog for the detection of false data injection attacks. It takes into account Bayesian Spatial-Temporal Hierarchical Model (HBT) to describe the features of the sensed data, and a sequential probability test is applied to identify an attacking device.…”

Section: Related Workmentioning

confidence: 99%

“…The neighbors number is computed through the control messages received by the node. After knowing the number of neighbors, nodes broadcast such information to their neighboring nodes (l. [10][11][12][13][14][15][16][17][18][19] to run the leader election. For that, the node with the largest number of neighbors is chosen as the leader node, and its category is changed to leader (l. [20][21][22].…”

Section: The Thatachi Idsmentioning

confidence: 99%

“…Next, the confidence of the suspicious node (l.7) is calculated. It will be taken the node as SH attacker when it has a reputation and trust below [0.5]; so it will not forward the information sent by other nodes (l. [10][11][12][13][14][15][16]. Whereas the procedure for detecting SF attack initially calculates the expected CPPT (l. [18][19][20].…”

Section: If the Message Is From An Associate The New Leader Only Estmentioning

confidence: 99%

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Clustering and reliability-driven mitigation of routing attacks in massive IoT systems

Santos

Cervantes

Nogueira

et al. 2019

J Internet Serv Appl

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As an integral component of the 5G communications, the massive Internet of Things (IoT) are vulnerable to various routing attacks due to their dynamic infrastructure, distinct computing resources, and heterogeneity of mobile objects. The sinkhole and selective forwarding attacks stand out among the most destructive ones for infrastructureless networks. Despite the countermeasures introduced by legacy intrusion detection systems (IDS), the massive IoT seeks novel solutions to address their unique requirements. This paper introduces DeTection of SinkHole And SelecTive ForwArding for Supporting SeCure routing for Internet of THIngs (THATACHI), a new IDS against sinkhole and selective forwarding attacks that target routing mechanism in massive and mobile IoT networks. To cope with the density and mobility challenges in the detection of attackers and ensuring reliability, THATACHI exploits watchdog, reputation and trust strategies. Our performance evaluation under an urban scenario shows that THATACHI can perform with a 99% detection rate, 6% of false negative and false positive rates. Moreover, when compared to its closest predecessor against sinkhole attacks for IoT, THATACHI runs with at least 50% less energy consumption.

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Future IoT‐enabled threats and vulnerabilities: State of the art, challenges, and future prospects

Srivastava

Gupta

Quamara

et al. 2020

Int J Communication

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SummaryIn the recent era, the security issues affecting the future Internet‐of‐Things (IoT) standards has fascinated noteworthy consideration from numerous research communities. In this view, numerous assessments in the form of surveys were proposed highlighting several future IoT‐centric subjects together with threat modeling, intrusion detection systems (IDS), and various emergent technologies. In contrast, in this article, we have focused exclusively on the emerging IoT‐related vulnerabilities. This article is a multi‐fold survey that emphasizes on understanding the crucial causes of novel vulnerabilities in IoT paradigms and issues in existing research. Initially, we have emphasized on different layers of IoT architecture and highlight various emerging security challenges associated with each layer along with the key issues of different IoT systems. Secondly, we discuss the exploitation, detection, and defense methodologies of IoT malware‐enabled distributed denial of service (DDoS), Sybil, and collusion attack capabilities. We have also discussed numerous state‐of‐the‐art strategies for intrusion detection and methods for IDS setup in future IoT systems. Third, we have presented a brief classification of existing IoT authentication protocols and a comparative analysis of such protocols based on different IoT‐enabled cyber attacks. For conducting a real‐time future IoT research, we have presented some emerging blockchain solutions. We have also discussed a comparative examination of some of the recently developed simulation tools and IoT test beds that are characterized based on different layers of IoT infrastructure. We have also outlined some of the open issues and future research directions and also facilitate the readers with broad classification of existing surveys in this domain that addresses several scopes related to the IoT paradigm. This survey article focuses in enabling IoT‐related research activities by comparing and merging scattered surveys in this domain.

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Robust detection of false data injection attacks for data aggregation in an Internet of Things-based environmental surveillance

Cited by 49 publications

References 28 publications

A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT

A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT

Clustering and reliability-driven mitigation of routing attacks in massive IoT systems

Future IoT‐enabled threats and vulnerabilities: State of the art, challenges, and future prospects

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