arXiv subjects

Mohammad Saidur Rahman

Publications and source records attributed to Mohammad Saidur Rahman.

24 records · Page 2Linked to original sources

arXiv2020

Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces

Website Fingerprinting (WF) is a type of traffic analysis attack that enables a local passive eavesdropper to infer the victim's activity, even when the traffic is protected by a VPN or an anonymity system like Tor. Leveraging a deep-learning classifier, a WF attacker can gain over 98% accuracy on Tor traffic. In this paper, we explore a novel defense, Mockingbird, based on the idea of adversarial examples that have been shown to undermine machine-learning classifiers in other domains. Since the attacker gets to design and train his attack classifier based on the defense, we first demonstrate that at a straightforward technique for generating adversarial-example based traces fails to protect against an attacker using adversarial training for robust classification. We then propose Mockingbird, a technique for generating traces that resists adversarial training by moving randomly in the space of viable traces and not following more predictable gradients. The technique drops the accuracy of the state-of-the-art attack hardened with adversarial training from 98% to 42-58% while incurring only 58% bandwidth overhead. The attack accuracy is generally lower than state-of-the-art defenses, and much lower when considering Top-2 accuracy, while incurring lower bandwidth overheads.

cs.CR↗

arXiv2020

Optimizing Smart Grid Aggregators and Measuring Degree of Privacy in a Distributed Trust Based Anonymous Aggregation System

A smart grid is an advanced method for supplying electricity to the consumers alleviating the limitations of the existing system. It causes frequent meter reading transmission from the end-user to the supplier. This frequent data transmission poses privacy risks. Several works have been proposed to solve this problem but cannot ensure privacy at the optimal level. This work is based on a distributed trust-based data aggregation system leveraging a secret sharing mechanism. In this work, we show that {\em three aggregators} are enough for ensuring consumer's privacy in a distributed trust-based system. We leverage the idea of anonymity in our research and show that neither an active attacker nor a passive attacker can breach consumer's privacy. We show proof of our concept mathematically and in a cryptographic game based mechanism. We name our new proposed system \emph{"Distributed Trust Based Anonymous System (DTBAS)"}.

cs.CR↗

arXiv2020

Tik-Tok: The Utility of Packet Timing in Website Fingerprinting Attacks

A passive local eavesdropper can leverage Website Fingerprinting (WF) to deanonymize the web browsing activity of Tor users. The value of timing information to WF has often been discounted in recent works due to the volatility of low-level timing information. In this paper, we more carefully examine the extent to which packet timing can be used to facilitate WF attacks. We first propose a new set of timing-related features based on burst-level characteristics to further identify more ways that timing patterns could be used by classifiers to identify sites. Then we evaluate the effectiveness of both raw timing and directional timing which is a combination of raw timing and direction in a deep-learning-based WF attack. Our closed-world evaluation shows that directional timing performs best in most of the settings we explored, achieving: (i) 98.4% in undefended Tor traffic; (ii) 93.5% on WTF-PAD traffic, several points higher than when only directional information is used; and (iii) 64.7% against onion sites, 12% higher than using only direction. Further evaluations in the open-world setting show small increases in both precision (+2%) and recall (+6%) with directional-timing on WTF-PAD traffic. To further investigate the value of timing information, we perform an information leakage analysis on our proposed handcrafted features. Our results show that while timing features leak less information than directional features, the information contained in each feature is mutually exclusive to one another and can thus improve the robustness of a classifier.

cs.CR↗

arXiv2017

Channel Transition Invariant Fast Broadcasting Scheme

Fast broadcasting (FB) is a popular near video-on-demand system where a video is divided into equal size segments those are repeatedly transmitted over a number of channels following a pattern. For user satisfaction, it is required to reduce the initial user waiting time and client side buffer requirement at streaming. Use of additional channels can achieve the objective. However, some augmentation is required to the basic FB scheme as it lacks any mechanism to realise a well defined relationship among the segment sizes at channel transition. Lack of correspondence between the segments causes intermediate waiting for the clients while watching videos. Use of additional channel requires additional bandwidth. In this paper, we propose a modified FB scheme that achieves zero initial clients waiting time and provides a mechanism to control client side buffer requirement at streaming without requiring additional channels. We present several results to demonstrate the effectiveness of the proposed FB scheme over the existing ones.

cs.MM↗

arXiv2015

Student Satisfaction mining in a typical core course of Computer Science

Students' satisfaction plays a vital role in success of an educational institute. Hence, many educational institutes continuously improve their service to produce a supportive learning environment to satisfy the student need. For this reason, educational institutions collect student satisfaction data to make decision about institutional quality, but till now it cannot be determined because student satisfaction is a complex matter which is influenced by variety of characteristics of students and institutions. There are many studies have been performed to inspect student satisfaction in the form of college services, programs, student accommodation facility, student-faculty interaction, consulting hours etc. So, still we cannot have a standard method to know what is going on about satisfaction in the case of a core course. In this research we determined the attributes that heavily affect student satisfaction in a core course of computer science and the current status of other attributes as well.

cs.CY↗

arXiv2012

A Coherent Distributed Grid Service for Assimilation and Unification of Heterogeneous Data Source

Grid services are heavily used for handling large distributed computations. They are also very useful to handle heavy data intensive applications where data are distributed in different sites. Most of the data grid services used in such situations are meant for homogeneous data source. In case of Heterogeneous data sources, most of the grid services that are available are designed such a way that they must be identical in schema definition for their smooth operation. But there can be situations where the grid site databases are heterogeneous and their schema definition is different from the central schema definition. In this paper we propose a light weight coherent grid service for heterogeneous data sources that is very easily install. It can map and convert the central SQL schema into that of the grid members and send queries to get according results from heterogeneous data sources.

cs.DB↗