Showing papers by "Mayank Dave published in 2019"

Software-defined Networking-based DDoS Defense Mechanisms

Abstract: Distributed Denial of Service attack (DDoS) is recognized to be one of the most catastrophic attacks against various digital communication entities. Software-defined networking (SDN) is an emerging technology for computer networks that uses open protocols for controlling switches and routers placed at the network edges by using specialized open programmable interfaces. In this article, a detailed study on DDoS threats prevalent in SDN is presented. First, SDN features are examined from the perspective of security, and then a discussion on SDN security features is done. Further, two viewpoints on protecting networks against DDoS attacks are presented. In the first view, SDN utilizes its abilities to secure conventional networks. In the second view, SDN may become a victim of the threat itself because of the centralized control mechanism. The main focus of this research work is on discovering critical security implications in SDN while reviewing the current ongoing research studies. By emphasizing the available state-of-the-art techniques, an extensive review of the advancement of SDN security is provided to the research and IT communities.

Securing IoT Devices and SecurelyConnecting the Dots Using REST API and Middleware

Abstract: Internet of Things (IoT) is a fairly disruptive technology with inconceivable growth, impact, and capability. We present the role of REST API in the IoT Systems and some initial concepts of IoT, whose technology is able to record and count everything. We as well highlight the concept of middleware that connects these devices and cloud. The appearance of new IoT applications in the cloud has brought new threats to security and privacy of data. Therefore it is required to introduce a secure IoT system which doesn't allow attackers infiltration in the network through IoT devices and also to secure data in transit from IoT devices to cloud. We provide the details on how Representational State Transfer (REST) API allows to securely expose connected devices to applications on cloud and users. In the proposed model, middleware is primarily used to expose device data through REST and to hide details and act as an interface to the user to interact with sensor data.

Protocol Stack of Underwater Wireless Sensor Network: Classical Approaches and New Trends

Abstract: The oceans and rivers remain the least explored frontiers on earth but due to frequent occurrences of disasters or calamities, the researchers have shown keen interest towards underwater monitoring. Underwater Wireless Sensor Networks (UWSN) envisioned as an aquatic medium for variety of applications like oceanographic data collection, disaster management or prevention, assisted navigation, attack protection, and pollution monitoring. Like terrestrial Wireless Sensor Networks (WSN), UWSN consists of sensor nodes that collect the information and pass it to sink, however researchers have to face many challenges in executing the network in aquatic medium. Some of these challenges are mobile sensor nodes, large propagation delays, limited link capacity, and multiple message receptions. In this manuscript, broad survey of issues concerning underwater sensor networks is presented. We provide an overview of test beds, routing protocols, experimental projects, simulation platforms, tools and analysis that are available with research fraternity.

Image-to-Image Translation Using Generative Adversarial Network

Abstract: Now a days, Generative Adversarial Networks (GANs) are an arising technology for both supervised and unsupervised learning which have capability to generate data of high standard. Image to Image translation is one of the application of GANs as a data augmentation which we have used in this proposed framework. Generative Networks makes the mapping between source image and target image easier and it calculates the loss function also to improve the quality of generated target image. In this paper, Conditional GANs are used which translates the images based upon some conditions. The performance is also analyzed of the model by doing hyper-parameter tuning.

Defending DDoS against Software Defined Networks using Entropy

Abstract: Software defined networking (SDN) has gained the attention of many researchers and networking data centers. SDN provides flexibility and programmability to the network which makes it easy to adapt the changes. As SDN controller has a centralized visibility to the complete network topology, it may be targeted by the attackers. By breaking the integration of forwarding and routing rules in a single device, it offers cost-efficient networking services. However, SDN may suffer from various types of Distributed denial of service (DDoS) attacks. DDoS can disturb the complete network functionality by consuming resources and processing power of controller. Some researchers have designed many efficient defense mechanisms recently. In this research work, entropy which is used to compute the randomness of any event is utilized to detect the DDoS attacks. The attack detection module is implemented in POX controller which monitors the statistics of all the incoming flows. The suggested entropy based detection offers to identify the attack in a short duration and gives a fast response.

Data Augmentation Using Generative Adversarial Network

Abstract: Now a days, Deep Learning has made appreciable development which introduces intelligence in machines to work like human brain. For this learning, the presence of large and balanced dataset is essential so that we can train the machines more efficiently. However finding such data in real world is rare, and creating these data sets is a complex task. So Generative Ad- versarial Networks (GANs) are used to create dataset to enhance the unsupervised learning. In this proposed work, Convolutional GAN is used for data augmentation which produces more realistic datasets and then we analyse the performance of this GAN by doing hyper-parameter tuning of opitmizers and activation functions.

Hybrid Color Image Watermarking Algorithm Based on DSWT-DCT-SVD and Arnold Transform

Abstract: With emergence of new technologies it is now easier to communicate through multimedia like image, audio, video and text. But at the same time the problem of unauthorized access and copyright protection has also emerged. In order to handle these problems digital image watermarking is one of the best technique. In this paper we present an optimized color image watermarking technique to protect an image data from any unauthorized access. The technique presented in the paper uses a combination of Discrete Stationary Wavelet Transform (DSWT), Singular Value Decomposition (SVD), Discrete Cosine Transform (DCT) and Arnold Transform. In this technique we hide a color image watermark into a colored cover image without hampering the perceptibility of the cover image. Peak-signal-to-noise-ratio (PSNR) and Normalized Correlation (NC) are used to analyze the proposed watermarking technique for the imperceptibility and robustness measures.

Securing User Access at IoT Middleware Using Attribute Based Access Control

Abstract: IoT middleware is an additional layer between IoT devices and the cloud applications that reduces computation and data handling on the cloud. In a typical IoT system model, middleware primarily connects to different IoT devices via IoT gateway. Device data stored on middleware is sensitive and private to a user. Middleware must have built-in mechanisms to address these issues, as well as the implementation of user authentication and access control. This paper presents the current methods used for access control on middleware and introduces Attribute-based encryption (ABE) on middleware for access control. ABE combines access control with data encryption for ensuring the integrity of data. In this paper, we propose Ciphertext-policy attribute-based encryption, abbreviated CP-ABE scheme on the middleware layer in the IoT system architecture for user access control. The proposed scheme is aimed to provide security and efficiency while reducing complexity on middleware. We have used the AVISPA tool to strengthen the proposed scheme.

Robust Hybrid Image and Audio Watermarking Using Cyclic Codes and Arnold Transform

Abstract: Hybrid watermarking is a prevailing technique in the latest research and has a significant amount of real-time applications. Digital watermarking is utilized to protect copyright and security to multimedia content. In this paper, an algorithm is an amalgamation of image watermarking and audio watermarking algorithms. In case of image watermarking algorithm discrete cosine transform (DCT) and in case of audio, discrete cosine transforms (DCT) and discrete wavelet transform (DWT) are used to propose this Hybrid watermarking algorithm. Moreover, to refine the performance of the proposed scheme, error correction technique and Arnold transforms are employed. Peak sound to noise ratio and Bit Error Rate (BER) is applied to estimate the performance of this scheme to counter the Time-Scale Modification and numerous attacks possible on images and audio as well.

Improving Result Diversity Using Query Term Proximity in Exploratory Search

Abstract: In the information retrieval system, relevance manifestation is pivotal and regularly based on document-term statistics, i.e. term frequency (tf), inverse document frequency (idf), etc. Query term proximity within matched documents is mostly under-explored. In this paper, a novel information retrieval framework is proposed, to promote the documents among all relevant retrieved ones. The relevance estimation is a weighted combination of document statistics and query term statistics, and term-term proximity is a simply aggregates of diverse user preferences aspects in query formation, thus adapted into the framework with conventional relevance measures. Intuitively, QTP is exploited to promote the documents for balanced exploitation-exploration, and eventually navigate a search towards goals. The evaluation asserts the usability of QTP measures to balance several seeking tradeoffs, e.g. relevance, novelty, result diversity (Coverage and Topicality), and overall retrieval. The assessment of user search trails indicates significant growth in a learning outcome.

Key Management in WSN Security: An Attacker's Perspective

Abstract: To create a secure communication among the sensor nodes, a key establishment scheme is very important. Wireless sensor networks (WSN) are usually left unattended and thus may attract the adversary to launch several attacks to the network operation. The exposure of the key during a node capture may disturb a large part of network communication. If there is a reliable, efficient, and secure KMS, disruption in the network to such an extent may not occur during a node capture attack. Several researchers have presented several key agreement schemes, but still the area is open to design an efficient attack resistant KMS. Sometimes, during the design of security protocols, the assumptions taken for the adversary behavior in sensor field may not reflect their actual behavior of the adversary in sensor field making these schemes less feasible in many real-world WSN applications. This chapter first discusses the challenges and security requirements, node capture attacks, its impact on the network, and some open issues of KMS solutions to this problem.

Robust Hybrid Watermarking using Image and Audio against Synchronization Attacks

Abstract: Hybrid Watermarking Approach is one of the trending approaches in the field of information security. Watermarking has a variety of applications to ensure data authentication, security, verification, and copyrights protection of digital media. The proposed approach is hybrid watermarking applied on image and audio. We proposed a scheme in which the image is blindly embedded over original data with the help of Discrete Wavelength Transformation(DWT) and Singular value decomposition(SVD). Now the watermarked image is embedded into an audio signal by taking advantage of the histogram by making a gathering of three neighboring bins having various samples into it and later histogram is pulled out from embedding range by quoting to the modified mean. There is appropriate security analysis of the hybrid watermarking with respect to robustness and imperceptibility mainly against synchronization attacks and we also analyze the robustness in the case of common attacks