National University of Computer and Emerging Sciences

About: National University of Computer and Emerging Sciences is a education organization based out in Islamabad, Pakistan. It is known for research contribution in the topics: Computer science & The Internet. The organization has 1506 authors who have published 2438 publications receiving 26786 citations.

URLdeepDetect: A Deep Learning Approach for Detecting Malicious URLs Using Semantic Vector Models

Abstract: Malicious Uniform Resource Locators (URLs) embedded in emails or Twitter posts have been used as weapons for luring susceptible Internet users into executing malicious content leading to compromised systems, scams, and a multitude of cyber-attacks. These attacks can potentially might cause damages ranging from fraud to massive data breaches resulting in huge financial losses. This paper proposes a hybrid deep-learning approach named URLdeepDetect for time-of-click URL analysis and classification to detect malicious URLs. URLdeepDetect analyzes semantic and lexical features of a URL by applying various techniques, including semantic vector models and URL encryption to determine a given URL as either malicious or benign. URLdeepDetect uses supervised and unsupervised mechanisms in the form of LSTM (Long Short-Term Memory) and k-means clustering for URL classification. URLdeepDetect achieves accuracy of 98.3% and 99.7% with LSTM and k-means clustering, respectively.

On the reliability of ad hoc routing protocols for loss-and-delay sensitive applications

Abstract: In this paper, we analyze the packet delivery reliability of ad hoc routing protocols for loss-and-delay sensitive applications. Since a typical flooding-based route discovery used in ad hoc routing protocols -DSR for instance - can only discover node-disjoint paths. In this context, we first show that the reliability function of such a multipath system is concave with respect to the total number of paths. Therefore, maximum steady-state reliability may be attained by routing each packet through a small set of node-disjoint paths. Subsequently, we prove that a partially-disjoint path is more reliable than a node-disjoint path. Hence, high reliability and significant energy savings may be achieved by routing a packet through fewer partially-disjoint paths. Based on these findings, we suggest modifications to flooding-based route discovery procedure to discover partially-disjoint paths. We complement our theoretical outcomes through extensive simulations. Finally, we analyze the reliability of beacon-based routing protocols and derive an upper bound on the number of hops at which a beacon should be placed to satisfy a given packet reliability constraint.

Securing SIP-based VoIP infrastructure against flooding attacks and Spam Over IP Telephony

Abstract: Security of session initiation protocol (SIP) servers is a serious concern of Voice over Internet (VoIP) vendors. The important contribution of our paper is an accurate and real-time attack classification system that detects: (1) application layer SIP flood attacks that result in denial of service (DoS) and distributed DoS attacks, and (2) Spam over Internet Telephony (SPIT). The major advantage of our framework over existing schemes is that it performs packet-based analysis using a set of spatial and temporal features. As a result, we do not need to transform network packet streams into traffic flows and thus save significant processing and memory overheads associated with the flow-based analysis. We evaluate our framework on a real-world SIP traffic—collected from the SIP server of a VoIP vendor—by injecting a number of application layer anomalies in it. The results of our experiments show that our proposed framework achieves significantly greater detection accuracy compared with existing state-of-the-art flooding and SPIT detection schemes.