Skypemorph: Protocol Obfuscation for Tor Bridges
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Cisco SCA BB Protocol Reference Guide
Cisco Service Control Application for Broadband Protocol Reference Guide Protocol Pack #60 August 02, 2018 Cisco Systems, Inc. www.cisco.com Cisco has more than 200 offices worldwide. Addresses, phone numbers, and fax numbers are listed on the Cisco website at www.cisco.com/go/offices. THE SPECIFICATIONS AND INFORMATION REGARDING THE PRODUCTS IN THIS MANUAL ARE SUBJECT TO CHANGE WITHOUT NOTICE. ALL STATEMENTS, INFORMATION, AND RECOMMENDATIONS IN THIS MANUAL ARE BELIEVED TO BE ACCURATE BUT ARE PRESENTED WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED. USERS MUST TAKE FULL RESPONSIBILITY FOR THEIR APPLICATION OF ANY PRODUCTS. THE SOFTWARE LICENSE AND LIMITED WARRANTY FOR THE ACCOMPANYING PRODUCT ARE SET FORTH IN THE INFORMATION PACKET THAT SHIPPED WITH THE PRODUCT AND ARE INCORPORATED HEREIN BY THIS REFERENCE. IF YOU ARE UNABLE TO LOCATE THE SOFTWARE LICENSE OR LIMITED WARRANTY, CONTACT YOUR CISCO REPRESENTATIVE FOR A COPY. The Cisco implementation of TCP header compression is an adaptation of a program developed by the University of California, Berkeley (UCB) as part of UCB’s public domain version of the UNIX operating system. All rights reserved. Copyright © 1981, Regents of the University of California. NOTWITHSTANDING ANY OTHER WARRANTY HEREIN, ALL DOCUMENT FILES AND SOFTWARE OF THESE SUPPLIERS ARE PROVIDED “AS IS” WITH ALL FAULTS. CISCO AND THE ABOVE-NAMED SUPPLIERS DISCLAIM ALL WARRANTIES, EXPRESSED OR IMPLIED, INCLUDING, WITHOUT LIMITATION, THOSE OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OR ARISING FROM A COURSE OF DEALING, USAGE, OR TRADE PRACTICE. IN NO EVENT SHALL CISCO OR ITS SUPPLIERS BE LIABLE FOR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, OR INCIDENTAL DAMAGES, INCLUDING, WITHOUT LIMITATION, LOST PROFITS OR LOSS OR DAMAGE TO DATA ARISING OUT OF THE USE OR INABILITY TO USE THIS MANUAL, EVEN IF CISCO OR ITS SUPPLIERS HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. -
Skype Voip Service- Architecture and Comparison Hao Wang Institute of Communication Networks and Computer Engineering University of Stuttgart Mentor: Dr.-Ing
INFOTECH Seminar Advanced Communication Services (ACS), 2005 Skype VoIP service- architecture and comparison Hao Wang Institute of Communication Networks and Computer Engineering University of Stuttgart Mentor: Dr.-Ing. S. Rupp ABSTRACT Skype is a peer-to-peer (P2P) overlay network for VoIP and other applications, developed by KaZaa in 2003. Skype can traverse NAT and firewall more efficiently than traditional VoIP networks and it offers better voice quality. To find and locate users, Skype uses “supernodes” that are running on peer machines. In contrast, traditional systems use fixed central servers. Also Skype uses encrypted media channel to protect the dada. The main contribution of this article is illustrating the architecture and components of Skype networks and basically analyzing key Skype functions such as login, NAT and firewall traversal. Furthermore, it contains comparisons of Skype networks with VoIP networks regarding different scenarios. On that basis it reveals some reasons why Skype has much better performance than previous VoIP products. Keywords Voice over IP (VoIP), Skype, Peer-to-peer (p2p), Super Node (SN) 1. Introduction It is expected that real-time person-to-person communication, like IP telephony (VoIP), instant messaging, voice, video and data collaboration will be the next big wave of Internet usage. VoIP refers to technology that enables routing of voice conversations over the Internet or any other IP network. Another technology is peer-to-peer, which is used for sharing content like audio, video, data or anything in digital format. Skype is a combination of these two technologies. It has much better performance by making use of advantages of both technologies. -
Devicelock® DLP 8.3 User Manual
DeviceLock® DLP 8.3 User Manual © 1996-2020 DeviceLock, Inc. All Rights Reserved. Information in this document is subject to change without notice. No part of this document may be reproduced or transmitted in any form or by any means for any purpose other than the purchaser’s personal use without the prior written permission of DeviceLock, Inc. Trademarks DeviceLock and the DeviceLock logo are registered trademarks of DeviceLock, Inc. All other product names, service marks, and trademarks mentioned herein are trademarks of their respective owners. DeviceLock DLP - User Manual Software version: 8.3 Updated: March 2020 Contents About This Manual . .8 Conventions . 8 DeviceLock Overview . .9 General Information . 9 Managed Access Control . 13 DeviceLock Service for Mac . 17 DeviceLock Content Security Server . 18 How Search Server Works . 18 ContentLock and NetworkLock . 20 ContentLock and NetworkLock Licensing . 24 Basic Security Rules . 25 Installing DeviceLock . .26 System Requirements . 26 Deploying DeviceLock Service for Windows . 30 Interactive Installation . 30 Unattended Installation . 35 Installation via Microsoft Systems Management Server . 36 Installation via DeviceLock Management Console . 36 Installation via DeviceLock Enterprise Manager . 37 Installation via Group Policy . 38 Installation via DeviceLock Enterprise Server . 44 Deploying DeviceLock Service for Mac . 45 Interactive Installation . 45 Command Line Utility . 47 Unattended Installation . 48 Installing Management Consoles . 49 Installing DeviceLock Enterprise Server . 52 Installation Steps . 52 Installing and Accessing DeviceLock WebConsole . 65 Prepare for Installation . 65 Install the DeviceLock WebConsole . 66 Access the DeviceLock WebConsole . 67 Installing DeviceLock Content Security Server . 68 Prepare to Install . 68 Start Installation . 70 Perform Configuration and Complete Installation . 71 DeviceLock Consoles and Tools . -
Insight Into the Gtalk Protocol
1 Insight into the Gtalk Protocol Riyad Alshammari and A. Nur Zincir-Heywood Dalhousie University, Faculty of Computer Science Halifax NS B3H 1W5, Canada (riyad,zincir)@cs.dal.ca Abstract Google talk (Gtalk) is an instant messeger and voice over IP client developed by Google in 2005. Gtalk can work across firewalls and has very good voice quality. It encrypts calls end-to-end, and stores user information in a centralized fashion. This paper analyzes fundamental Gtalk functions such as login, firewall traversal, and call establishment under different network scenarios. The analysis is performed by both active and passive measurement techniques to understand the Gtalk network traffic. Based on our analysis, we devised algorithms for login and call establishment processes as well as data flow models. I. INTRODUCTION Voice over IP (VoIP) is becoming a major communication service for enterprises and individuals since the cost of VoIP calls is low and the voice quality is getting better. To date, there are many VoIP products that are able to provide high call quality such as Skype [1], Google Talk (Gtalk) [2], Microsoft Messenger (MSN) [3], and Yahoo! Messenger (YMSG) [4]. However, few information has been documented about protocol design used by these VoIP clients since the protocols are not standardized, many of them are proprietary, and the creators of these softwares want to keep their information confidential and protect their protocol design form competitors. In this paper, we have generated and captured network traffic in order to determine the broad characteristics of one of the most recent and fast growing VoIP applications, Google Talk. -
BPGC at Semeval-2020 Task 11: Propaganda Detection in News Articles with Multi-Granularity Knowledge Sharing and Linguistic Features Based Ensemble Learning
BPGC at SemEval-2020 Task 11: Propaganda Detection in News Articles with Multi-Granularity Knowledge Sharing and Linguistic Features based Ensemble Learning Rajaswa Patil1 and Somesh Singh2 and Swati Agarwal2 1Department of Electrical & Electronics Engineering 2Department of Computer Science & Information Systems BITS Pilani K. K. Birla Goa Campus, India ff20170334, f20180175, [email protected] Abstract Propaganda spreads the ideology and beliefs of like-minded people, brainwashing their audiences, and sometimes leading to violence. SemEval 2020 Task-11 aims to design automated systems for news propaganda detection. Task-11 consists of two sub-tasks, namely, Span Identification - given any news article, the system tags those specific fragments which contain at least one propaganda technique and Technique Classification - correctly classify a given propagandist statement amongst 14 propaganda techniques. For sub-task 1, we use contextual embeddings extracted from pre-trained transformer models to represent the text data at various granularities and propose a multi-granularity knowledge sharing approach. For sub-task 2, we use an ensemble of BERT and logistic regression classifiers with linguistic features. Our results reveal that the linguistic features are the reliable indicators for covering minority classes in a highly imbalanced dataset. 1 Introduction Propaganda is biased information that deliberately propagates a particular ideology or political orientation (Aggarwal and Sadana, 2019). Propaganda aims to influence the public’s mentality and emotions, targeting their reciprocation due to their personal beliefs (Jowett and O’donnell, 2018). News propaganda is a sub-type of propaganda that manipulates lies, semi-truths, and rumors in the disguise of credible news (Bakir et al., 2019). -
Sailpoint Direct Connectors Administration and Configuration Guide for Version 7.3
SailPoint Direct Connectors Version 7.3 Administration and Configuration Guide Copyright © 2018 SailPoint Technologies, Inc., All Rights Reserved. SailPoint Technologies, Inc. makes no warranty of any kind with regard to this manual, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose. SailPoint Technologies shall not be liable for errors contained herein or direct, indirect, special, incidental or consequential damages in connection with the furnishing, performance, or use of this material. Restricted Rights Legend. All rights are reserved. No part of this document may be published, distributed, reproduced, publicly displayed, used to create derivative works, or translated to another language, without the prior written consent of SailPoint Technologies. The information contained in this document is subject to change without notice. Use, duplication or disclosure by the U.S. Government is subject to restrictions as set forth in subparagraph (c) (1) (ii) of the Rights in Technical Data and Computer Software clause at DFARS 252.227-7013 for DOD agencies, and subparagraphs (c) (1) and (c) (2) of the Commercial Computer Software Restricted Rights clause at FAR 52.227-19 for other agencies. Regulatory/Export Compliance. The export and re-export of this software is controlled for export purposes by the U.S. Government. By accepting this software and/or documentation, licensee agrees to comply with all U.S. and foreign export laws and regulations as they relate to software and related documentation. Licensee will not export or re-export outside the United States software or documentation, whether directly or indirectly, to any Prohibited Party and will not cause, approve or otherwise intentionally facilitate others in so doing. -
Dataset of Propaganda Techniques of the State-Sponsored Information Operation of the People’S Republic of China
Dataset of Propaganda Techniques of the State-Sponsored Information Operation of the People’s Republic of China Rong-Ching Chang Chun-Ming Lai [email protected] [email protected] Tunghai University Tunghai University Taiwan Taiwan Kai-Lai Chang Chu-Hsing Lin [email protected] [email protected] Tunghai University Tunghai University Taiwan Taiwan ABSTRACT ACM Reference Format: The digital media, identified as computational propaganda provides Rong-Ching Chang, Chun-Ming Lai, Kai-Lai Chang, and Chu-Hsing Lin. a pathway for propaganda to expand its reach without limit. State- 2021. Dataset of Propaganda Techniques of the State-Sponsored Informa- tion Operation of the People’s Republic of China. In KDD ’21: The Sec- backed propaganda aims to shape the audiences’ cognition toward ond International MIS2 Workshop: Misinformation and Misbehavior Min- entities in favor of a certain political party or authority. Further- ing on the Web, Aug 15, 2021, Virtual. ACM, New York, NY, USA, 5 pages. more, it has become part of modern information warfare used in https://doi.org/10.1145/nnnnnnn.nnnnnnn order to gain an advantage over opponents. Most of the current studies focus on using machine learning, quantitative, and qualitative methods to distinguish if a certain piece 1 INTRODUCTION of information on social media is propaganda. Mainly conducted Propaganda has the purpose of framing and influencing opinions. on English content, but very little research addresses Chinese Man- With the rise of the internet and social media, propaganda has darin content. From propaganda detection, we want to go one step adopted a powerful tool for its unlimited reach, as well as multiple further to providing more fine-grained information on propaganda forms of content that can further drive engagement online and techniques that are applied. -
An Analysis of the Skype P2P Internet Telephony Protocol
An Analysis of the Skype P2P Internet Telephony Protocol 王永豪 B91902114 杜明可 B91902104 吳治明 B91902110 Outline z Intro z The Skype Network z Key Components z Experiment setup explained z Experiment performed and results z Startup z Login z User search z Call Establishment and teardown z Logout z Media Transfer z Conferencing z Other Skype facts z Conclusion Introduction z Previous solutions are cost saving however falls short on quality. z Call-completion rate are low due to NATs and Firewalls. z Bloated interface makes usage a hassle. Requires technical expertise. The Skype Network (as it used to be) z Central Login Server z Super Nodes z Ordinary Nodes The Skype Network (as it used to be) z NAT and Firewall traversal z STUN and TURN z No global traversal server z Function distributed among nodes z A 3G P2P network z Global Index Technology z Multi-tiered network where supernodes communicate in such a way that every node in the network has full knowledge of all available users and resources with minimal latency z 72 hour guaranteed user find z TCP for signaling z UDP & TCP for media traffic The way it looks now Key Components (as they used to be) z Ports z A Skype Client (SC) opens TCP and UDP listening ports as configured in the client itself z SC also listens on ports 80(HTTP) and 443(HTTPS) z No default listening port z Host Cache (HC) z Skype is an overlay network z Thus the HC contains IP address and port# of super nodes. -
Global Manipulation by Local Obfuscation ∗
Global Manipulation by Local Obfuscation ∗ Fei Liy Yangbo Songz Mofei Zhao§ August 26, 2020 Abstract We study information design in a regime change context. A continuum of agents simultaneously choose whether to attack the current regime and will suc- ceed if and only if the mass of attackers outweighs the regime’s strength. A de- signer manipulates information about the regime’s strength to maintain the status quo. The optimal information structure exhibits local obfuscation, some agents receive a signal matching the true strength of the status quo, and others receive an elevated signal professing slightly higher strength. Public signals are strictly sub- optimal, and in some cases where public signals become futile, local obfuscation guarantees the collapse of agents’ coordination. Keywords: Bayesian persuasion, coordination, information design, obfuscation, regime change JEL Classification: C7, D7, D8. ∗We thank Yu Awaya, Arjada Bardhi, Gary Biglaiser, Daniel Bernhardt, James Best, Jimmy Chan, Yi-Chun Chen, Liang Dai, Toomas Hinnosaar, Tetsuya Hoshino, Ju Hu, Yunzhi Hu, Chong Huang, Nicolas Inostroza, Kyungmin (Teddy) Kim, Qingmin Liu, George Mailath, Laurent Mathevet, Stephen Morris, Xiaosheng Mu, Peter Norman, Mallesh Pai, Alessandro Pavan, Jacopo Perego, Xianwen Shi, Joel Sobel, Satoru Takahashi, Ina Taneva, Can Tian, Kyle Woodward, Xi Weng, Ming Yang, Jidong Zhou, and Zhen Zhou for comments. yDepartment of Economics, University of North Carolina, Chapel Hill. Email: [email protected]. zSchool of Management and Economics, The Chinese University of Hong Kong, Shenzhen. Email: [email protected]. §School of Economics and Management, Beihang University. Email: [email protected]. 1 1 Introduction The revolution of information and communication technology raises growing con- cerns about digital authoritarianism.1 Despite their tremendous effort to establish in- formation censorship and to spread disinformation, full manipulation of information remains outside autocrats’ grasp in the modern age. -
Improving Meek with Adversarial Techniques
Improving Meek With Adversarial Techniques Steven R. Sheffey Ferrol Aderholdt Middle Tennessee State University Middle Tennessee State University Abstract a permitted host [10]. This is achieved by manipulating the Host header of the underlying encrypted HTTP payload in As the internet becomes increasingly crucial to distributing in- order to take advantage of cloud hosting services that forward formation, internet censorship has become more pervasive and HTTP traffic based on this header. Domain fronting exploits advanced. Tor aims to circumvent censorship, but adversaries censors’ unwillingness to cause collateral damage, as block- are capable of identifying and blocking access to Tor. Meek, ing domain fronting would require also blocking the typically a traffic obfuscation method, protects Tor users from censor- more reputable, permitted host. From the point of view of ship by hiding traffic to the Tor network inside an HTTPS an adversary using DPI and metadata-based filtering, there is connection to a permitted host. However, machine learning no difference between Meek and normal HTTPS traffic. All attacks using side-channel information against Meek pose unencrypted fields in Meek traffic that could indicate its true a significant threat to its ability to obfuscate traffic. In this destination such as DNS requests, IP addresses, and the Server work, we develop a method to efficiently gather reproducible Name Indication (SNI) inside HTTPS connection headers do packet captures from both normal HTTPS and Meek traffic. not reveal its true destination. We then aggregate statistical signatures from these packet However, recent work has shown that Meek is vulnerable captures. Finally, we train a generative adversarial network to machine learning attacks that use side-channel informa- (GAN) to minimally modify statistical signatures in a way tion such as packet size and timing distributions to differenti- that hinders classification. -
The Production and Circulation of Propaganda
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by RMIT Research Repository The Only Language They Understand: The Production and Circulation of Propaganda A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Christian Tatman BA (Journalism) Hons RMIT University School of Media and Communication College of Design and Social Context RMIT University February 2013 Declaration I Christian Tatman certify that except where due acknowledgement has been made, the work is that of the author alone; the work has not been submitted previously, in whole or in part, to qualify for any other academic award; the content of the thesis is the result of work which has been carried out since the official commencement date of the approved research program; any editorial work, paid or unpaid, carried out by a third party is acknowledged; and, ethics procedures and guidelines have been followed. Christian Tatman February 2013 i Acknowledgements I would particularly like to thank my supervisors, Dr Peter Williams and Associate Professor Cathy Greenfield, who along with Dr Linda Daley, have provided invaluable feedback, support and advice during this research project. Dr Judy Maxwell and members of RMIT’s Research Writing Group helped sharpen my writing skills enormously. Dr Maxwell’s advice and the supportive nature of the group gave me the confidence to push on with the project. Professor Matthew Ricketson (University of Canberra), Dr Michael Kennedy (Mornington Peninsula Shire) and Dr Harriet Speed (Victoria University) deserve thanks for their encouragement. My wife, Karen, and children Bethany-Kate and Hugh, have been remarkably patient, understanding and supportive during the time it has taken me to complete the project and deserve my heartfelt thanks. -
Machine Learning Model That Successfully Detects Russian Trolls 24 3
Human–machine detection of online-based malign information William Marcellino, Kate Cox, Katerina Galai, Linda Slapakova, Amber Jaycocks, Ruth Harris For more information on this publication, visit www.rand.org/t/RRA519-1 Published by the RAND Corporation, Santa Monica, Calif., and Cambridge, UK © Copyright 2020 RAND Corporation R® is a registered trademark. RAND Europe is a not-for-profit research organisation that helps to improve policy and decision making through research and analysis. RAND’s publications do not necessarily reflect the opinions of its research clients and sponsors. Limited Print and Electronic Distribution Rights This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited. Permission is given to duplicate this document for personal use only, as long as it is unaltered and complete. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial use. For information on reprint and linking permissions, please visit www.rand.org/pubs/permissions. Support RAND Make a tax-deductible charitable contribution at www.rand.org/giving/contribute www.rand.org www.randeurope.org III Preface This report is the final output of a study proof-of-concept machine detection in a known commissioned by the UK Ministry of Defence’s troll database (Task B) and tradecraft analysis (MOD) Defence Science and Technology of Russian malign information operations Laboratory (Dstl) via its Defence and Security against left- and right-wing publics (Task C). Accelerator (DASA).