Prabaharan Poornachandran

Amrita Vishwa Vidyapeetham | AMRITA · School of Engineering

Alzheimer’s disease (AD) is one of the most prevalent medical conditions with no effective medical treatment or cure. The issue lies in the fact that it is also a condition which is chronic, with irreversible effects on the brain, like cognitive impairment. The diagnosis of Alzheimer’s in elderly people is quite difficult and requires a highly disc...

The voltage fluctuations are caused by variations in renewable energy source outputs, increased usage of nonlinear loads, high reactive power consumption of loads, etc. This results in damage to electric components and enormous economic losses. It is necessary to measure the parameters of voltage fluctuations and flicker levels to achieve a secure...

Linear algebra is the backbone of modern applied data analytics. Not only does it provide the theoretical substratum for the development of analytical algorithms, it also lends the technological support for extremely efficient implementations. The linear algebra ecosystem consists of remarkably fast hardware support with equally efficient software...

Power quality monitoring and parameter estimation are essential for the proper functioning of modern power grids. Various techniques have been proposed to estimate the characteristics of power signals and to gain insight into their dynamics. Non-stationary Fourier mode decomposition (NFMD) is a new interpretable time-frequency analysis framework fo...

The techniques of deep learning have become the state of the art methodology for executing complicated tasks from various domains of computer vision, natural language processing, and several other areas. Due to its rapid development and promising benchmarks in those fields, researchers started experimenting with this technique to perform in the are...

Automated accounts which are otherwise known as bots are rampant in most of the popular online social networks. Similar to email spam, these social media bots are used for spreading information with the goal of propaganda or advertisements for profit. Due to the impact they pose on influencing the user communities, understanding the bot behaviour i...

Social Networks has become the biggest medium of expression of one’s thoughts and emotions. With more than one-third of the global population expressing their thoughts, opinions and events, these networks become rich with direct indicators about the subject. Multimedia based social networking services are gaining popularity than text-based ones. In...

This paper presents the description of the system used by the team Amrita CEN for the shared task on FACT (Factuality Analysis and Classification Task) at IberLEF2019 (Iberian Languages Evaluation Forum) workshop. The goal of the task was to automatically annotate an event with its factuality status. Factuality status is categorized into three as F...

Real-time prediction of domain names that are generated using the Domain Generation Algorithms (DGAs) is a challenging cyber security task. Scope to collect the vast amount of data for training favored data-driven techniques and deep learning architectures have the potential to address this challenge. This paper proposes a deep learning framework u...

This article describes how sequential data modeling is a relevant task in Cybersecurity. Sequences are attributed temporal characteristics either explicitly or implicitly. Recurrent neural networks (RNNs) are a subset of artificial neural networks (ANNs) which have appeared as a powerful, principle approach to learn dynamic temporal behaviors in an...

Botnets play an important role in malware distribution and they are widely used for spreading malicious activities in the Internet. The study of the literature shows that a large subset of botnets use DNS poisoning to spread out malicious activities and that there are various methods for their detection using DNS queries. However, since botnets gen...

In recent years, modern botnets employ the technique of domain generation algorithm (DGA) to evade detection solutions that use either reverse engineering methods, or blacklisting of malicious domain names. DGA facilitates generation of large number of pseudo random domain names to connect to the command and control server. This makes DGAs very con...

Recently, due to the advance and impressive results of deep learning techniques in the fields of image recognition, natural language processing and speech recognition for various long-standing artificial intelligence (AI) tasks, there has been a great interest in applying towards security tasks too. This article focuses on applying these deep taxon...

Spamming and Phishing attacks are the most common security challenges we face in today’s cyber world. The existing methods for the Spam and Phishing detection are based on blacklisting and heuristics technique. These methods require human intervention to update if any new Spam and Phishing activity occurs. Moreover, these are completely inefficient...

Recent families of malware have largely adopted domain generation algorithms (DGAs). This is primarily due to the fact that the DGA can generate a large number of domain names after that utilization a little subset for real command and control (C&C) server communication. DNS blacklist based on blacklisting and sink-holing is the most commonly used...

At present time, malware is one of the biggest threats to Internet service security. This chapter propose a novel file agnostic deep learning architecture for malware family identification which converts malware binaries into gray scale images and then identifies their families by a hybrid in-house model, Convolutional Neural Network and Long Short...

Machine learning has played an important role in the last decade mainly in natural language processing, image processing and speech recognition where it has performed well in comparison to the classical rule based approach. The machine learning approach has been used in cyber security use cases namely, intrusion detection, malware analysis, traffic...

Malicious uniform resource locator (URL) host unsolicited content and are a serious threat and are used to commit cyber crime. Malicious URL’s are responsible for various cyber attacks like spamming, identity theft, financial fraud, etc. The internet growth has also resulted in increase of fraudulent activities in the web. The classical methods lik...

The techniques of deep learning have become the state of the art methodology for executing complicated tasks from various domains of computer vision, natural language processing, and several other areas. Due to its rapid development and promising benchmarks in those fields, researchers started experimenting with this technique to perform in the are...

Malicious software or malware continues to pose a major security concern in this digital age as computer users, corporations, and governments witness an exponential growth in malware attacks. Current malware detection solutions adopt Static and Dynamic analysis of malware signatures and behaviour patterns that are time consuming and ineffective in...

Machine learning techniques are being widely used to develop an intrusion detection system (IDS) for detecting and classifying cyber-attacks at the network-level and host-level in a timely and automatic manner. However, many challenges arise since malicious attacks are continually changing and are occurring in very large volumes requiring a scalabl...

One of the objectives of signal processing is to extract features of the data which is considered as the first step toward data analysis. Number of oscillating components, the rate at which it oscillates, starting and ending time of the oscillation, duration of the oscillation, and strength of the oscillation are some of the features that help to m...

Ransomware is a type of malicious software that holds access to computer resources for a ransom amount. This is accomplished through encrypting the personal files or denying access to the user interface. The access is reinstated only once ransom amount is paid to the attacker. There is a significant increase in ransomware attacks involving crypto r...

Part-of-Speech (POS) tagging is an important task in Natural Language Processing and numerous taggers have been developed for POS tagging in several languages. In Sanskrit also, one of the oldest languages in the world, many POS taggers were developed. However, less attention was given to the machine learning based POS tagging. In this paper, vario...

The increasing number of cyberattacks in recent years has expedited development of innovative tools to quickly detect new threats. A recent approach to this problem is to analyze the content of online social networks to discover the rising of ransomware attacks. Twitter is a popular micro-blogging platform which allows millions of users to share th...

A computer virus or malware is a computer program, but with the purpose of causing harm to the system. This year has witnessed the rise of malware and the loss caused by them is high. Cyber criminals have continually advancing their methods of attack. The existing methodologies to detect the existence of such malicious programs and to prevent them...

Deep neural networks (DNNs) have witnessed as a powerful approach in this year by solving long-standing Artificial intelligence (AI) supervised and unsupervised tasks exists in natural language processing, speech processing, computer vision and others. In this paper, we attempt to apply DNNs on three different cyber security use cases: Android malw...

Intrusion detection system (IDS) has become an essential layer in all the latest ICT system due to an urge towards cyber safety in the day-to-day world. Reasons including uncertainty in finding the types of attacks and increased the complexity of advanced cyber attacks, IDS calls for the need of integration of Deep Neural Networks (DNNs). In this pa...

Deep Encrypted Text Categorization

Deep Android Malware Detection and Classification

Long Short-Term Memory based Operation Log Anomaly Detection

Evaluating Shallow and Deep Networks for Secure Shell (SSH)Traffic Analysis

There are myriad of security solutions that have been developed to tackle the Cyber Security attacks and malicious activities in digital world. They are firewalls, intrusion detection and prevention systems, anti-virus systems, honeypots etc. Despite employing these detection measures and protection mechanisms, the number of successful attacks and...

Understanding the user intention from text is a problem of growing interest. The social media like Twitter, Facebook etc. extract user intention to analyze the behaviour of a user which in turn is employed for bot recognition, satire detection, fake news detection etc.. The process of identifying stance of a user from the text is called stance dete...

Phishing represents a genuine risk to the Internet economy. Email has turned out to be a necessary verbal exchange tool in contemporary lifestyles. In recent days, email remains as the foremost generally utilized medium to dispatch phishing attacks. As a result, detection of phishing emails has been considered as an important task in the field of C...

A computer virus or malware is a computer program, but with the purpose of causing harm to the system. This year has witnessed the rise of malware and the loss caused by them is high. Cyber criminals have continually advancing their methods of attack. The existing methodologies to detect the existence of such malicious programs and to prevent them...

This chapter focuses on the aspects of making mobile applications and networks for public safety, especially those catering to emergency situations, context-aware. Making public safety systems context-aware would redefine how critical situations are handled today. This would enable a quick response to a situation, based on a holistic understanding...

From search engines to e-commerce websites and online video channels to smartphone applications, most of the internet applications use advertising as one of their primary source of revenue generation. Malvertising is the act of distributing malicious software to users via advertisements on websites. The major causes of malvertisement are the presen...

This paper discusses deepyCybErNet submission methodology to the task on Stance and Gender Detection in Tweets on Catalan Independence@Ibereval 2017. The goal of the task is to detect the stance and gender of the user in tweets on the subject ”independence of Catalonia”. Tweets are available in two languages: Spanish and Catalan. In task 1 and 2, t...

Network traffic prediction aims at predicting the subsequent network traffic by using the previous network traffic data. This can serve as a proactive approach for network management and planning tasks. In this paper, recurrent neural network (RNN) is employed to predict the future time series based on the past information.