A Brain-Inspired Trust Management Model to Assure Security in a Cloud based IoT Framework for Neuroscience Applications

Rapid popularity of Internet of Things (IoT) and cloud computing permits neuroscientists to collect multilevel and multichannel brain data to better understand brain functions, diagnose diseases, and devise treatments. To ensure secure and reliable data communication between end-to-end (E2E) devices supported by current IoT and cloud infrastructure, trust management is needed at the IoT and user ends. This paper introduces a Neuro-Fuzzy based Brain-inspired trust management model (TMM) to secure IoT devices and relay nodes, and to ensure data reliability. The proposed TMM utilizes node behavioral trust and data trust estimated using Adaptive Neuro-Fuzzy Inference System and weighted-additive methods respectively to assess the nodes trustworthiness. In contrast to the existing fuzzy based TMMs, the NS2 simulation results confirm the robustness and accuracy of the proposed TMM in identifying malicious nodes in the communication network. With the growing usage of cloud based IoT frameworks in Neuroscience research, integrating the proposed TMM into the existing infrastructure will assure secure and reliable data communication among the E2E devices.Comment: 17 pages, 10 figures, 2 table

Security of the Internet of Things: Vulnerabilities, Attacks and Countermeasures

Wireless Sensor Networks (WSNs) constitute one of the most promising third-millennium technologies and have wide range of applications in our surrounding environment. The reason behind the vast adoption of WSNs in various applications is that they have tremendously appealing features, e.g., low production cost, low installation cost, unattended network operation, autonomous and longtime operation. WSNs have started to merge with the Internet of Things (IoT) through the introduction of Internet access capability in sensor nodes and sensing ability in Internet-connected devices. Thereby, the IoT is providing access to huge amount of data, collected by the WSNs, over the Internet. Hence, the security of IoT should start with foremost securing WSNs ahead of the other components. However, owing to the absence of a physical line-of-defense, i.e., there is no dedicated infrastructure such as gateways to watch and observe the flowing information in the network, security of WSNs along with IoT is of a big concern to the scientific community. More specifically, for the application areas in which CIA (confidentiality, integrity, availability) has prime importance, WSNs and emerging IoT technology might constitute an open avenue for the attackers. Besides, recent integration and collaboration of WSNs with IoT will open new challenges and problems in terms of security. Hence, this would be a nightmare for the individuals using these systems as well as the security administrators who are managing those networks. Therefore, a detailed review of security attacks towards WSNs and IoT, along with the techniques for prevention, detection, and mitigation of those attacks are provided in this paper. In this text, attacks are categorized and treated into mainly two parts, most or all types of attacks towards WSNs and IoT are investigated under that umbrella: “Passive Attacks” and “Active Attacks”. Understanding these attacks and their associated defense mechanisms will help paving a secure path towards the proliferation and public acceptance of IoT technology

Location based services in wireless ad hoc networks

In this dissertation, we investigate location based services in wireless ad hoc networks from four different aspects - i) location privacy in wireless sensor networks (privacy), ii) end-to-end secure communication in randomly deployed wireless sensor networks (security), iii) quality versus latency trade-off in content retrieval under ad hoc node mobility (performance) and iv) location clustering based Sybil attack detection in vehicular ad hoc networks (trust). The first contribution of this dissertation is in addressing location privacy in wireless sensor networks. We propose a non-cooperative sensor localization algorithm showing how an external entity can stealthily invade into the location privacy of sensors in a network. We then design a location privacy preserving tracking algorithm for defending against such adversarial localization attacks. Next we investigate secure end-to-end communication in randomly deployed wireless sensor networks. Here, due to lack of control on sensors\u27 locations post deployment, pre-fixing pairwise keys between sensors is not feasible especially under larger scale random deployments. Towards this premise, we propose differentiated key pre-distribution for secure end-to-end secure communication, and show how it improves existing routing algorithms. Our next contribution is in addressing quality versus latency trade-off in content retrieval under ad hoc node mobility. We propose a two-tiered architecture for efficient content retrieval in such environment. Finally we investigate Sybil attack detection in vehicular ad hoc networks. A Sybil attacker can create and use multiple counterfeit identities risking trust of a vehicular ad hoc network, and then easily escape the location of the attack avoiding detection. We propose a location based clustering of nodes leveraging vehicle platoon dispersion for detection of Sybil attacks in vehicular ad hoc networks --Abstract, page iii

Advanced Dynamic Encryption – A Security Enhancement Protocol for IEEE 802.11 and Hybrid Wireless Network

Data integrity and privacy are the two most important security requirements in wireless communication. Most mechanisms rely on pre-share key data encryption to prevent unauthorized users from accessing confidential information. However, a fixed secret key is vulnerable to cracking by capturing sufficient packets or launching a dictionary attack. In this research, a dynamic re-keying encryption protocol was developed to enhance the security protection for IEEE 802.11 and hybrid wireless network. This protocol automatically updates the secret key during the end-to-end transmission between wireless devices to protect the network and the communication privacy. In addition, security analyses are given to verify the protection of this protocol. Experiment results also validate that the dynamic encryption approach can perform as efficiently as other security architectures while providing an additional layer of data protection

A layered security approach for cooperation enforcement in MANETs

In fully self-organized MANETs, nodes are naturally reluctant to spend their precious resources forwarding other nodes' packets and are therefore liable to exhibit selfish or sometimes malicious behaviour. This selfishness could potentially lead to network partitioning and network performance degradation. Cooperation enforcement schemes, such as reputation and trust based schemes have been proposed to counteract the issue of selfishness. The sole purpose of these schemes is to ensure selfish nodes bear the consequences of their bad actions. However, malicious nodes can exploit mobility and free identities available to breach the security of these systems and escape punishment or detection. Firstly, in the case of mobility, a malicious node can gain benefit even after having been detected by a reputation-based system, by interacting directly with its source or destination nodes. Secondly, since the lack of infrastructure in MANETs does not suit centralized identity management or centralized Trusted Third Parties, nodes can create zero-cost identities without any restrictions. As a result, a selfish node can easily escape the consequences of whatever misbehaviour it has performed by simply changing identity to clear all its bad history, known as whitewashing. Hence, this makes it difficult to hold malicious nodes accountable for their actions. Finally, a malicious node can concurrently create and control more than one virtual identity to launch an attack, called a Sybil attack. In the context of reputation-based schemes, a Sybil attacker can disrupt the detection accuracy by defaming other good nodes, self-promoting itself or exchanging bogus positive recommendations about one of its quarantined identities. This thesis explores two aspects of direct interactions (DIs), i. e. Dis as a selfish nodes' strategy and Dis produced by inappropriate simulation parameters. In the latter case DIs cause confusion in the results evaluation of reputation-based schemes. We propose a method that uses the service contribution and consumption information to discourage selfish nodes that try to increase their benefit through DIs. We also propose methods that categorize nodes' benefits in order to mitigate the confusion caused in the results evaluation. A novel layered security approach is proposed using proactive and reactive paradigms to counteract whitewashing and Sybil attacks. The proactive paradigm is aimed at removing the advantages that whitewashing can provide by enforcing a non-monetary entry fee per new identity, in the form of cooperation in the network. The results show that this method deters these attackers by reducing their benefits in the network. In the reactive case, we propose a lightweight approach to detect new identities of whitewashers and Sybil attackers on the MAC layer using the 802.11 protocol without using any extra hardware. The experiments show that a signal strength based threshold exists which can help us detect Sybil and whitewashers' identities. Through the help of extensive simulations and real-world testbed experimentations, we are able to demonstrate that our proposed solution detects Sybil or whitewashers' new identities with good accuracy and reduces the benefits of malicious activity even in the presence of mobility