International Institute of Information Technology, Hyderabad

About: International Institute of Information Technology, Hyderabad is a education organization based out in Hyderabad, India. It is known for research contribution in the topics: Computer science & Authentication. The organization has 2048 authors who have published 3677 publications receiving 45319 citations. The organization is also known as: IIIT Hyderabad & International Institute of Information Technology (IIIT).

An Efficient Hybrid Anomaly Detection Scheme Using K-Means Clustering for Wireless Sensor Networks

Abstract: Sensor nodes in a wireless sensor network (WSN) may be lost due to enervation or malicious attacks by an adversary. WSNs deployed for several applications including military applications are prone to various attacks, which degrade the network performance very rapidly. Hybrid anomaly is a type of anomaly that contains the different types of attacker nodes such as blackhole, misdirection, wormhole etc. These multiple attacks can be launched in the network using the hybrid anomaly. In this situation, it is very difficult to find out which kind of attacker nodes are activated in the network. This motivates us to design a robust and efficient secure intrusion detection approach in order to extend the lifetime of a WSN. In this paper, we aim to propose a new intrusion detection technique for hybrid anomaly, which uses the existing data mining algorithm, called K-means clustering. For the detection purpose, patterns of intrusions are built automatically by the K-means clustering algorithm over training data. After that intrusions are detected by matching network activities against these detection patterns. We evaluate our approach over a WSN dataset that is created using Opnet modeler, which contains various attributes, such as end-to-end delay, traffic sent and traffic received. The training dataset contains the normal values of the network parameters. The testing dataset is created in actual working mode consists of normal and abnormal values of the network parameters. The proposed technique has the ability to detect two types of malicious nodes: blackhole and misdirection nodes. Our scheme achieves 98.6 % detection rate and 1.2 % false positive rate, which are significantly better than the existing related schemes.

The Hindi Discourse Relation Bank

Abstract: We describe the Hindi Discourse Relation Bank project, aimed at developing a large corpus annotated with discourse relations. We adopt the lexically grounded approach of the Penn Discourse Treebank, and describe our classification of Hindi discourse connectives, our modifications to the sense classification of discourse relations, and some cross-linguistic comparisons based on some initial annotations carried out so far.

IIIT Hyderabad at TAC 2008

Abstract: This paper describes our participation at TAC 2008 in all the three tracks. For the Summarization Track we introduced two major features. First, a feature based on Information Loss if we don’t pick a particular sentence. Second, a language modeling extension that boosts novel terms and penalizes stale terms. During our post-TAC analysis we observed that a simple sentence position based summarizer leads to better short summaries than most official runs submitted this year. In the Opinion QA and Summarization Track for the rigid list questions, we have added some additional features to handle opinion expressed in the question. and for the squishy list questions in Opinion QA and Summarization Track, we leveraged on our existing Summarization engine and used a classification based approach to both finding opinionated sentences and also the polarity of the opinions. Finally, for the RTE track we explored a simple graph partition matching based approach.

On the Design of Mutual Authentication and Key Agreement Protocol in Internet of Vehicles-Enabled Intelligent Transportation System

Abstract: Internet of Vehicles (IoV), a distributed network involving connected vehicles and Vehicular Ad Hoc Networks (VANETs), allows connected vehicles to communicate with other Internet-connected entities in real time. The communications among these entities (e.g. vehicles, pedestrians, fleet management systems, and road-side infrastructure) generally take place via an open channel. In other words, such an open communication can be targeted by the adversary to eavesdrop, modify, insert fabricated (or malicious) messages, or delete any data-in-transit; thus, resulting in replay, impersonation, man-in-the-middle, privileged-insider, and other related attacks. In addition to security, anonymity and untraceability are two other important features that should be achieved in an authentication protocol. In this paper, we propose a new mutual authentication and key agreement protocol in an IoV-enabled Intelligent Transportation System (ITS). Using both formal and informal security analysis, as well as formal security verification using an automated verification tool, we show that the proposed scheme is secure against several known attacks in an IoV-enabled ITS environment. Furthermore, a detailed comparative analysis shows that the proposed scheme has low communication and computational overheads, and offers better security and functionality attributes in comparison to seven other competing schemes. We also evaluate the performance of the proposed scheme using NS2.