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.

Inkjet-Printed Human Body Temperature Sensor for Wearable Electronics

Abstract: This paper presents an all-printed human body temperature sensor developed on a plastic substrate with high deformation characteristics. The sensors are developed on $50~\mu \text{m}$ thick Kapton substrate with structural configuration of silver interdigital electrodes (IDEs) fabricated through inkjet material printer DMP 2850 and the sensing film based on carbon black deposited through doctor blade coating. Interdigital distance of the IDEs were optimized by evaluating sensors’ performance against changing the fingers spacing within a close range of 0.1–1 mm. Good sensitivity i.e. 0.00375 °C −1 is achieved at a temperature range of 28 to 50 °C with response and recovery times of 4 and 8.5 sec, respectively. Robustness of the sensor was also evaluated for a period of 50 days and a negligible drift ( $1\Omega$ ) in the base resistance was recorded. The sensor exhibited bendability down to 5 mm and was also characterized for the chemical and electrical properties i.e. resistance variation, surface morphology and Raman shift analysis of the carbon black. This wearable sensor can potentially be applied on human body for continuous temperature monitoring as well as on the artificial skin for social and industrial robotic applications.

ELF-Miner: using structural knowledge and data mining methods to detect new (Linux) malicious executables

Abstract: Linux malware can pose a significant threat—its (Linux) penetration is exponentially increasing—because little is known or understood about Linux OS vulnerabilities. We believe that now is the right time to devise non-signature based zero-day (previously unknown) malware detection strategies before Linux intruders take us by surprise. Therefore, in this paper, we first do a forensic analysis of Linux executable and linkable format (ELF) files. Our forensic analysis provides insight into different features that have the potential to discriminate malicious executables from benign ones. As a result, we can select a features’ set of 383 features that are extracted from an ELF headers. We quantify the classification potential of features using information gain and then remove redundant features by employing preprocessing filters. Finally, we do an extensive evaluation among classical rule-based machine learning classifiers—RIPPER, PART, C4.5 Rules, and decision tree J48—and bio-inspired classifiers—cAnt Miner, UCS, XCS, and GAssist—to select the best classifier for our system. We have evaluated our approach on an available collection of 709 Linux malware samples from vx heavens and offensive computing. Our experiments show that ELF-Miner provides more than 99% detection accuracy with less than 0.1% false alarm rate.

Evaluating DoS Attacks against Sip-Based VoIP Systems

Abstract: The multimedia communication is rapidly converging towards Voice over Internet - commonly known as Voice over Internet Protocol (VoIP). Session Initiation Protocol (SIP) is the standard used for session signaling in VoIP. Crafty attackers can launch a number of Denial of Service (DoS) attacks on a SIP based VoIP infrastructure that can severely compromise its reliability. In contrast, little work is done to analyze the robustness and reliability of SIP severs under DoS attacks. In this paper, we show that the robustness and reliability of generic SIP servers is inadequate than commonly perceived. We have done our study using a customized analysis tool that has the ability to synthesize and launch different types of attacks. We have integrated the tool in a real SIP test bed environment to measure the performance of SIP servers. Our measurements show that a standard SIP server can be easily overloaded by sending simple call requests. We define the performance metrics to measure the effects of flooding attacks on real time services - VoIP in SIP environment - and show the results on different SIP server implementations. Our results also provide insight into resources' usage by SIP servers under flooding attacks. Moreover, we show that how a well known open source SIP server can be crashed through 'INVITE of Death' - a malformed SIP packet maliciously crafted by our tool.