Sachin Shetty

Physical layer security in wireless cooperative relay networks: state of the art and beyond

Cooperative relaying is an effective method of increasing the range and reliability of wireless networks, and several relaying strategies have been adopted in major wireless standards. Recently, cooperative relaying has also been considered in the context of PHY security, which is a new security paradigm to supplement traditional cryptographic schemes that usually handle security at the upper layers. In wireless PHY security, relay nodes can be used to exploit the physical layer properties of wireless channels in order to support a secured transmission from a source to a destination in the presence of one or more eavesdroppers. While some breakthroughs have been made in this emerging research area, to date, the problem of how to effectively adopt advanced relaying protocols to enhance PHY security is still far from being fully understood. In this article, we present a comprehensive summary of current state-of-theart PHY security concepts in wireless relay networks. A case study is then provided to quantify the benefits of power allocation and relay location for enhanced security. We finally outline important future research directions in relaying topologies, full-duplex relaying, and cross-layer design that can ignite new interests and ideas on the topic.

Rogue Access Point Detection by Analyzing Network Traffic Characteristics

One of the most challenging network security concerns for network administrators is the presence of rogue access points. Rogue access points, if undetected, can be an open door to sensitive information on the network. Many data raiders have taken advantage of the undetected rogue access points in enterprises to not only get free Internet access, but also to view confidential information. Most of the current solutions to detect rouge access points are not automated and are dependent on a specific wireless technology. In this paper, we present a rogue access point detection approach. The approach is an automated solution which can be installed on any router at the edge of a network. The main premise of our approach is to distinguish authorized WLAN hosts from unauthorized WLAN hosts connected to rogue access points by analyzing traffic characteristics at the edge of a network. Simulation results verify the effectiveness of our approach in detecting rogue access points in a heterogeneous network comprised of wireless and wired subnets.

ProvChain: A Blockchain-based Data Provenance Architecture in Cloud Environment with Enhanced Privacy and Availability

Cloud data provenance is metadata that records the history of the creation and operations performed on a cloud data object. Secure data provenance is crucial for data accountability, forensics and privacy. In this paper, we propose a decentralized and trusted cloud data provenance architecture using blockchain technology. Blockchain-based data provenance can provide tamper-proof records, enable the transparency of data accountability in the cloud, and help to enhance the privacy and availability of the provenance data. We make use of the cloud storage scenario and choose the cloud file as a data unit to detect user operations for collecting provenance data. We design and implement ProvChain, an architecture to collect and verify cloud data provenance, by embedding the provenance data into blockchain transactions. ProvChain operates mainly in three phases: (1) provenance data collection, (2) provenance data storage, and (3) provenance data validation. Results from performance evaluation demonstrate that ProvChain provides security features including tamper-proof provenance, user privacy and reliability with low overhead for the cloud storage applications.

Stackelberg-Game-Based Dynamic Spectrum Access in Heterogeneous Wireless Systems

In this paper, we investigate a two-stage Stackelberg game for dynamic spectrum access (DSA) in cognitive radio networks using a leader [spectrum provider (SP)] subgame and a follower [secondary user (SU)] subgame. Our research distinguishes itself in a number of ways. First, a two-stage Stackelberg game has been proposed to provide a unique optimal solution that facilitates a tradeoff between quality of service (QoS) of unlicensed SUs and revenue of SPs. Second, comprehensive budget and QoS constraints imposed by the signal-to-interference-plus-noise ratio are defined to fully take into account QoS requirements. Third, a necessary condition and closed form for the existence of the Stackelberg equilibrium are presented for multiradio multichannel DSA. Analytical and simulation studies are carried out to assess the performance of the proposed game, and the numerical results verify that the proposed approach reaches the unique Stackelberg equilibrium.

A Learning-based Multiuser Opportunistic Spectrum Access Approach in Unslotted Primary Networks

Opportunistic spectrum access presents a new approach to wireless spectrum utilization and management. In this paper, we propose a non-cooperative based OSA approach: learning-based approach to allow multiple secondary users to achieve maximal throughput in an unslotted opportunistic spectrum access (OSA) network. In this approach, collisions among secondary users are taken into consideration while making channel sensing decisions. Spectrum maps for secondary users are estimated based on occurrence of collisions. Our approach allows secondary users to achieve maximal throughput by seeking independent spectrum opportunities without exchanging any control information among secondary users. Numerical results show that the learning-based approach obtains near-optimal performance in most of the scenarios.

A Hidden Markov Model based approach to detect Rogue Access Points

One of the most challenging security concerns for network administrators is the presence of rogue access points. In this paper, we propose a statistical based approach to detect rogue access points using a hidden Markov model applied to passively measure packet-header data collected at a gateway router. Our approach utilizes variations in packet inter-arrival time to differentiate between authorized access points and rouge access points. We designed and developed our hidden Markov model by analyzing denial of service attacks and the traffic characteristics of 802.11 based wireless local area networks. Experimental validations demonstrate the effectiveness of our approach. Our trained Hidden Markov Model can detect the presence of a rogue access point promptly within one second with extreme accuracy (very low false positive and false negative ratios are obtained). The success of our approach lies in the fact that it leverages knowledge about the behaviour of the traffic characteristics of 802.11 based WLANs and properties of denial of service attacks. Our approach is scalable and non-intrusive, requiring little deployment cost and effort, and is easy to manage and maintain.

Detecting Compromised Nodes in Wireless Sensor Networks

With embedded system being used in every corner of military and civil electronic industries, its security problem is prominent. Inspired by the natural immune system, the paper proposes an immune middleware to prevent embedded system from misacting when net intrusion or inner mistake happens. Firstly a flexible bus that has three-layer architecture is presented to help the embedded system acquire compatibility, multi- functionality and standardization. Then based on this multiplayer bus architecture, the middleware evolved from the concept of antigen and antibody is proposed. The design principle, the immune strategy, the architecture and the working flow of the immune middleware are introduced in detail afterwards. Finally an experimental case demonstrates the validity of the proposed method.While wireless sensor networks are proving to be a versatile tool, many of the applications in which they are implemented have sensitive data. In other words, security is crucial in many of these applications. Once a sensor node has been compromised, the security of the network degrades quickly if there are not measures taken to deal with this event. There have been many approaches researched to tackle the issue. In this paper, we look into an anomaly-based intrusion detection system to detect compromised nodes in wireless sensor networks. An algorithm to detect the compromised sensor nodes has been developed. Simulations are conducted to verify the design.

Secure Radio Resource Management in Cloud Computing Based Cognitive Radio Networks

With the rapid development of cognitive radios, spectrum efficiency in cognitive radio networks (CRN) has increased by secondary users (SU) accessing the licensed spectrum dynamically and opportunistically without creating harmful interference to primary users. However, the performance and security of CRN is considerably constrained by its limited power, memory and computational capacity. Fortunately, the advent of cloud computing has the potential to mitigate these constraints due its vast storage and computational capacity. In this paper, we propose secure radio resource management algorithm for CRN where cloud computing unit stores the spectrum occupancy information of heterogeneous wireless networks in CRN and facilitates the access of spectrum opportunities for secondary users. The proposed algorithm leverages the geolocation of secondary user and idle licensed bands to facilitate the secure allocation of radio resources to SU. Furthermore, the secondary users who provide high benefit are admitted while satisfying the quality of service (QoS) requirement of secondary users in terms of data rate and service time. We also present the design to implement the proposed algorithm on Cloud computing platform, and propose a scalable mapping method under the Storm, real time processing model to dynamically partition the geographical area according to the SU density. Simulation results are presented to demonstrate the performance of the proposed secure radio resource management algorithm.

The impact of antenna orientation on wireless sensor network performance

In this paper, we investigate the impact of antenna orientation on the performance of wireless sensor networks. In the experiments conducted using Crossbow MicaZ motes we realized that the antenna orientation has a significant impact on the received signal strength (RSSI). It thus becomes important to incorporate the effects on RSSI due to variations in antenna orientations while performing simulations and analyzing the performance of wireless sensor networks. We have successfully validated the experimental results with an analytical model. The significant deviations have been explained based on other factors that affect the performance of wireless sensor networks, viz. mulitpath, interference etc. However, it must be noticed that we do not generalize the results obtained, as it depends upon the type of antenna used, and in our case, it is a quarter wavelength tilt and swivel antenna that is usually used for MicaZ sensor motes. In order to determine the routing path from one node to the other, we propose Distance and Orientation based Protocol for Energy conservation, or in short DOPE. Using this protocol, the data is routed based on the least energy consuming path. Matlab simulation of sensor network yields that if the data is routed from one node to the other based on antenna orientation consideration, a lot of energy (on an average 30 percent) can be saved as compared to the networks where antenna orientation is not taken into consideration.

Dynamic Spectrum Access for Wireless Networks

This SpringerBrief presents adaptive resource allocation schemes for secondary users for dynamic spectrum access (DSA) in cognitive radio networks (CRNs) by considering Quality-of-Service requirements, admission control, power/rate control, interference constraints, and the impact of spectrum sensing or primary user interruptions. It presents the challenges, motivations, and applications of the different schemes. The authors discuss cloud-assisted geolocation-aware adaptive resource allocation in CRNs by outsourcing computationally intensive processing to the cloud. Game theoretic approaches are presented to solve resource allocation problems in CRNs. Numerical results are presented to evaluate the performance of the proposed methods. Adaptive Resource Allocation in Cognitive Radio Networks is designed for professionals and researchers working in the area of wireless networks. Advanced-level students in electrical engineering and computer science, especially those focused on wireless networks, will find this information helpful.