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The Internet of Things (IoT) is a network of sensors that helps collect data 24/7 without human intervention. However, the network may suffer from problems such as the low battery, heterogeneity, and connectivity issues due to the lack of standards. Even though these problems can cause several performance hiccups, security issues need immediate attention because hackers access vital personal and financial information and then misuse it. These security issues can allow hackers to hijack IoT devices and then use them to establish a Botnet to launch a Distributed Denial of Service (DDoS) attack. Blockchain technology can provide security to IoT devices by providing secure authentication using public keys. Similarly, Smart Contracts (SCs) can improve the performance of the IoT–blockchain network through automation. However, surveyed work shows that the blockchain and SCs do not provide foolproof security; sometimes, attackers defeat these security mechanisms and initiate DDoS attacks. Thus, developers and security software engineers must be aware of different techniques to detect DDoS attacks. In this survey paper, we highlight different techniques to detect DDoS attacks. The novelty of our work is to classify the DDoS detection techniques according to blockchain technology. As a result, researchers can enhance their systems by using blockchain-based support for detecting threats. In addition, we provide general information about the studied systems and their workings. However, we cannot neglect the recent surveys. To that end, we compare the state-of-the-art DDoS surveys based on their data collection techniques and the discussed DDoS attacks on the IoT subsystems. The study of different IoT subsystems tells us that DDoS attacks also impact other computing systems, such as SCs, networking devices, and power grids. Hence, our work briefly describes DDoS attacks and their impacts on the above subsystems and IoT. For instance, due to DDoS attacks, the targeted computing systems suffer delays which cause tremendous financial and utility losses to the subscribers. Hence, we discuss the impacts of DDoS attacks in the context of associated systems. Finally, we discuss Machine-Learning algorithms, performance metrics, and the underlying technology of IoT systems so that the readers can grasp the detection techniques and the attack vectors. Moreover, associated systems such as Software-Defined Networking (SDN) and Field-Programmable Gate Arrays (FPGA) are a source of good security enhancement for IoT Networks. Thus, we include a detailed discussion of future development encompassing all major IoT subsystems.
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Community Cleanup: Incentivizing Network Hygiene via Distributed Attack Reporting
Residential networks are difficult to secure due to resource constraints and lack of local security expertise. These networks primarily use consumer-grade routers that lack meaningful security mechanisms, providing a safe-haven for adversaries to launch attacks, including damaging distributed denial-of-service (DDoS) attacks. Prior efforts have suggested outsourcing residential network security to experts, but motivating user adoption has been a challenge. This work explores combining residential SDN techniques with prior work on collaborative DDoS reporting to identify residential network compromises. This combination provides incentives for end-users to deploy the technique, including rapid notification of compromises on their own devices and reduced upstream bandwidth consumption, while incurring minimal performance overheads.
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- Award ID(s):
- 1651540
- PAR ID:
- 10225847
- Date Published:
- Journal Name:
- IEEE/IFIP Network Operations and Management Symposium
- Page Range / eLocation ID:
- 1 to 9
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The security of residential networks can vary greatly. These networks are often administrated by end-users who may lack security expertise or the resources to adequately defend their networks. Insecure residential networks provide attackers with opportunities to infiltrate systems and create a platform for launching powerful attacks. To address these issues, we introduce a new approach that uses software-defined networking (SDN) to allow home users to outsource their security maintenance to a cloud-based service provider. Using this architecture, we show how a novel network-based two-factor authentication approach can be used to protect Internet of Things devices. Our approach works without requiring modifications to end-devices. We further show how security modules can enforce protocol messages to limit the attack surface in vulnerable devices. Our analysis shows that the system is effective and adds less than 50 milliseconds of delay to the start of a connection with less than 100 microseconds of delay for subsequent packets.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/NOMS47738.2020.9110446
