The idea of Internet of Things (IoT) is implanting networked heterogeneous detectors into our daily life. It opens extra channels for information submission and remote control to our physical world. A significant feature of an IoT network is that it collects data from network edges. Moreover, human involvement for network and devices maintenance is greatly reduced, which suggests an IoT network need to be highly self-managed and self-secured. For the reason that the use of IoT is growing in many important fields, the security issues of IoT need to be properly addressed. Among all, Distributed Denial of Service (DDoS) is one of the most notorious attacking behaviors over network which interrupt and block genuine user requests by flooding the host server with huge number of requests using a group of zombie computers via geographically distributed internet connections. DDoS disrupts service by creating network congestion and disabling normal functions of network components, which is even more disruptive for IoT. In this paper, a lightweight defensive algorithm for DDoS attack over IoT network environment is proposed and tested against several scenarios to dissect the interactive communication among different types of network nodes.

Communication security in internet of thing: preventive measure and avoid DDoS attack over IoT network

Internet of Things (IoT) refers to the networked interconnection of everyday objects. IoT is an upcoming research field and is being regarded as the revolution in the world of communication because of its extensible applications in numerous fields. Due to open and self-assimilation nature of these networks they are highly prone to attacks. Because of this reason security is of primary concern here. The security attack can be of various types, the idea here is to prevent IoT networks from Distributed Denial of Service (DDoS) attack. The objective of Denial of Service (DoS) is to make the server resources unavailable to the intended user, and when several such DoS attacks are present in a network then the attack is known as a DDoS attack. Our strategy is to prevent DDoS attack in IoT networks by using Learning Automata (LA) concepts. In this paper, we present a Service Oriented Architecture (SOA) which is used as a system model for IoT here. SOA provides a platform to the developers using which they can develop various applications for IoT without any concern regarding the nature of the objects, thereby acting as a middleware. The DDoS prevention strategy has been targeted for the SOA based architecture for IoT. The simulation results show that the proposed scheme is effective in preventing DDoS attacks in IoT.

A Learning Automata Based Solution for Preventing Distributed Denial of Service in Internet of Things

The development of personalized recommendation systems has been an interesting research topic after the rapid evolution in social networking sites. In this paper, we propose a recommendation system using Learning automata (LA) and sentiment analysis. LA is used to optimize the recommendation score produced by the proposed system using sentiment analysis. The proposed Learning Automata-Based Sentiment Analysis System (LASA) recommends the places nearby the current location of the users by analyzing the feedback from the places and thus calculating the score based on it. Experiments performed by us indicate that by using LA, we can improve the performance of the proposed system, and, thus, help a user to find a specific location according to the need.

Learning Automata Based Sentiment Analysis for recommender system on cloud

Underwater sensor networks (UWSNs) can be deployed for sensing the environment in oceanographic columns and other water bodies in which they are deployed. The peculiar characteristic of the underwater medium, coupled with the queer nature of the sound waves in water, poses an enigmatic problem for UWSN researchers. In this study, the authors focus on the problem of UWSN jamming, which is a popular type of denial-of-service attack. The existing jamming detection solutions for sensor networks are primarily targeted towards the terrestrial ones. In this work, the authors study the unique characteristics of jamming in UWSN, and propose a protocol, known as underwater jamming detection protocol (UWJDP), to detect and mitigate jamming in underwater environments. The results show that if the packet delivery ratio (PDR) is less than or equal to 0.8, the authors have the maximum probability of detecting jamming. The jamming detection ratio is around 2-11- more for the said PDR.

Jamming in underwater sensor networks: detection and mitigation

In recent times, there is increasing consensus that the traditional Internet architecture needs to be evolved for it to sustain unstinted growth and innovation. A major reason for the perceived architectural ossification is the lack of the ability to program the network as a system. This situation has resulted partly from historical decisions in the original Internet design which emphasized decentralized network operations through colocated data and control planes on each network device. The situation for wireless networks is no different resulting in a lot of complexity and a plethora of largely incompatible wireless technologies. With traditional architectures providing limited support for programmability, there is a broad realization in the wireless community that future programmable wireless networks would require significant architectural innovations. In this paper, we will present an unified overview of the programmability solutions that have been proposed at the device and the network level. In particular, we will discuss software-defined radio (SDR), cognitive radio (CR), programmable MAC processor, and programmable routers as device-level programmability solutions, and software-defined networking (SDN), cognitive wireless networking (CWN), virtualizable wireless networking (VWN) and cloud-based wireless networking (CbWN) as network-level programmability solutions. We provide both a self-contained exposition of these topics as well as a broad survey of the application of these trends in modern wireless networks.

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Building programmable wireless networks: an architectural survey

Wireless Mesh Networks (WMNs) have potentially unlimited applications in the future. Therefore, establishing a viable and secure wireless network routing protocol for these networks is essential. Currently, these networks are being used in connecting large sections of cities by setting up wireless routers at strategic points all around the city. These networks can also support connecting remote areas of the country, instead of having to lay a cable all the way. The nature of applications mentioned above make these networks prone to different attacks. Thus, security of these networks is a serious concern. In this paper, we study the impact of Distributed Denial of Service (DDoS) attacks on WMNs. We base our work on the existing Optimized Link State Routing protocol (OLSR) and we weave in concepts of Learning Automata (LA) to protect the network from this kind of attack. The simulation results for the proposed scheme show that the proposed protocol is effective in the prevention of DDoS attacks in WMNs.

Navin Sasikumar

Papers

An adaptive learning routing protocol for the prevention of distributed denial of service attacks in wireless mesh networks