ENCRYPTION POLICY for HUMAN RIGHTS DEFENDERS “It Is Neither Fanciful Nor an Exaggeration to Say That, Without Encryption Tools, Lives May Be Endangered.”
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Operating System Boot from Fully Encrypted Device
Masaryk University Faculty of Informatics Operating system boot from fully encrypted device Bachelor’s Thesis Daniel Chromik Brno, Fall 2016 Replace this page with a copy of the official signed thesis assignment and the copy of the Statement of an Author. Declaration Hereby I declare that this paper is my original authorial work, which I have worked out by my own. All sources, references and literature used or excerpted during elaboration of this work are properly cited and listed in complete reference to the due source. Daniel Chromik Advisor: ing. Milan Brož i Acknowledgement I would like to thank my advisor, Ing. Milan Brož, for his guidance and his patience of a saint. Another round of thanks I would like to send towards my family and friends for their support. ii Abstract The goal of this work is description of existing solutions for boot- ing Linux and Windows from fully encrypted devices with Secure Boot. Before that, though, early boot process and bootloaders are de- scribed. A simple Linux distribution is then set up to boot from a fully encrypted device. And lastly, existing Windows encryption solutions are described. iii Keywords boot process, Linux, Windows, disk encryption, GRUB 2, LUKS iv Contents 1 Introduction ............................1 1.1 Thesis goals ..........................1 1.2 Thesis structure ........................2 2 Boot Process Description ....................3 2.1 Early Boot Process ......................3 2.2 Firmware interfaces ......................4 2.2.1 BIOS – Basic Input/Output System . .4 2.2.2 UEFI – Unified Extended Firmware Interface .5 2.3 Partitioning tables ......................5 2.3.1 MBR – Master Boot Record . -
Effective Crypto Ransomawre Detection Using Hardware
Effective Crypto Ransomawre Detection Using Hardware Performance Counters John Podolanko Department of Computer Science & Engineering The University of Texas at Arlington Supervisor Jiang Ming, PhD In partial fulfillment of the requirements for the degree of Master of Science in Computer Science May 2019 Abstract Systems affected by malware in the past 10 years has risen from 29 million to 780 million, which tells us it is a rapidly growing threat. Viruses, ransomware, worms, backdoors, botnets, etc. all come un- der malware. Ransomware alone is predicted to cost $11.5 billion in 2019. As the downtime, data loss, and financial damages are ris- ing, researchers continue to look for new ways to mitigate this threat. However, the common approaches have shown to yield high false posi- tive rates or delayed detection rates resulting in data loss. My research explores a dynamic approach for early-stage ransomware detection by modeling its behavior using hardware performance counters with low overhead. The analysis begins on a bare-metal machine running ran- somware which is profiled for hardware calls using Intel R VTuneTM Amplifier before it compromises the system. By using this approach, I am able to generate models using hardware performance counters extracted by VTuneTM on known ransomware samples collected from VirusTotal and Hybrid Analysis, and I use that data to train the de- tection system using machine learning techniques. I have shown that hardware performance counters can provide effective metrics for use in detecting and mitigating the ever-growing ransomware threat faced by the world while ensuring no data is lost. ii Acknowledgements The author thanks the supervisory committee for all their guidance, support, and patience. -
Quantum Cryptography Without Basis Switching 2004
Quantum Cryptography Without Basis Switching Christian Weedbrook B.Sc., University of Queensland, 2003. A thesis submitted for the degree of Bachelor of Science Honours in Physics The Australian National University October 2004 ii iii Listen, do you want to know a secret? Do you promise not to tell? - John Lennon and Paul McCartney iv Declaration This thesis is an account of research undertaken with the supervision of Dr Ping Koy Lam, Dr Tim Ralph and Dr Warwick Bowen between February 2004 and October 2004. It is a partial fulfilment of the requirements for the degree of a Bachelor of Science with Honours in theoretical physics at the Australian National University, Canberra, Australia. Except where acknowledged in the customary manner, the material presented in this thesis is, to the best of my knowledge, original and has not been submitted in whole or part for a degree in any university. Christian Weedbrook 29th October 2004 v vi Acknowledgements During the three years of residency, it was the relationships that got you through. - J.D., Scrubs I have met a lot of people during my Honours year, and a lot of people to thank and be thankful for. First I would like to thank my supervisors Ping Koy Lam, Tim Ralph, Warwick Bowen and my “unofficial” supervisor Andrew Lance. Ping Koy, thank you for your positive approach and enthusiasm. It was excellent having you as my supervisor, as you have many ideas and the ability to know the best way to proceed. I would like to thank you for my scholarship and also for organizing that I could do my Honours at ANU, and to spend some time up at UQ. -
Inside Dropbox: Understanding Personal Cloud Storage Services
Inside Dropbox: Understanding Personal Cloud Storage Services → Idilio Drago → Marco Mellia → Maurizio M. Munafo` → Anna Sperotto → Ramin Sadre → Aiko Pras IRTF – Vancouver Motivation and goals 1 Personal cloud storage services are already popular Dropbox in 2012 “the largest deployed networked file system in history” “over 50 million users – one billion files every 48 hours” Little public information about the system How does Dropbox work? What are the potential performance bottlenecks? Are there typical usage scenarios? Methodology – How does Dropbox work? 2 Public information Native client, Web interface, LAN-Sync etc. Files are split in chunks of up to 4 MB Delta encoding, deduplication, encrypted communication To understand the client protocol MITM against our own client Squid proxy, SSL-bump and a self-signed CA certificate Replace a trusted CA certificate in the heap at run-time Proxy logs and decrypted packet traces How does Dropbox (v1.2.52) work? 3 Clear separation between storage and meta-data/client control Sub-domains identifying parts of the service sub-domain Data-center Description client-lb/clientX Dropbox Meta-data notifyX Dropbox Notifications api Dropbox API control www Dropbox Web servers d Dropbox Event logs dl Amazon Direct links dl-clientX Amazon Client storage dl-debugX Amazon Back-traces dl-web Amazon Web storage api-content Amazon API Storage HTTP/HTTPs in all functionalities How does Dropbox (v1.2.52) work? 4 Notification Kept open Not encrypted Device ID Folder IDs How does Dropbox (v1.2.52) work? 4 Client control Login File hash Meta-data How does Dropbox (v1.2.52) work? 4 Storage Amazon EC2 Retrieve vs. -
NSA's Efforts to Secure Private-Sector Telecommunications Infrastructure
Under the Radar: NSA’s Efforts to Secure Private-Sector Telecommunications Infrastructure Susan Landau* INTRODUCTION When Google discovered that intruders were accessing certain Gmail ac- counts and stealing intellectual property,1 the company turned to the National Security Agency (NSA) for help in securing its systems. For a company that had faced accusations of violating user privacy, to ask for help from the agency that had been wiretapping Americans without warrants appeared decidedly odd, and Google came under a great deal of criticism. Google had approached a number of federal agencies for help on its problem; press reports focused on the company’s approach to the NSA. Google’s was the sensible approach. Not only was NSA the sole government agency with the necessary expertise to aid the company after its systems had been exploited, it was also the right agency to be doing so. That seems especially ironic in light of the recent revelations by Edward Snowden over the extent of NSA surveillance, including, apparently, Google inter-data-center communications.2 The NSA has always had two functions: the well-known one of signals intelligence, known in the trade as SIGINT, and the lesser known one of communications security or COMSEC. The former became the subject of novels, histories of the agency, and legend. The latter has garnered much less attention. One example of the myriad one could pick is David Kahn’s seminal book on cryptography, The Codebreakers: The Comprehensive History of Secret Communication from Ancient Times to the Internet.3 It devotes fifty pages to NSA and SIGINT and only ten pages to NSA and COMSEC. -
4-BAY RACKMOUNT NAS Technical Specifications
4-BAY RACKMOUNT NAS Technical Specifications Operating System Seagate® NAS OS (embedded Linux) Number of Drive Bays 4 hot-swappable 3.5-inch SATA II/SATA III Processor Dual-core 2.13GHz Intel® 64-bit Atom™ processor Memory 2GB DDR III Networking Two (2) 10/100/1000 Base-TX (Gigabit Ethernet) • Two (2) USB 3.0 (rear) • Two (2) USB 2.0 (rear) External Ports • One (1) eSATA (rear) • One (1) USB 2.0 (front) Hard Drive Capacity Seagate NAS HDD 2TB, 3TB, 4TB for preconfigured models Total Capacity 4TB, 8TB, 12TB, 16TB Compatible Drives 3.5-inch SATA II or SATA III (see NAS Certified Drive list PDF for more details) Power 100V to 240V AC, 50/60Hz, 180W Power Supply and • Sleep mode for power saving • Scheduled power on/off Power Management • Wake-on-LAN Cooling Management Two (2) fans Transfer Rate 200MB/s reads and writes1 Network Protocols CIFS/SMB, NFS v3, AFP, HTTP(s), FTP, sFTP, iSCSI, Print serve, failover and load balancing and Services (LACP 802.3ad), Wuala file system integration (W:/ network drive), Active Directory™ • RAID 0, 1, 5, 6, 10 RAID • Hot spare • SimplyRAID™ technology with mixed capacity support, volume expansion and migration • Web-based interface through http/https • Hardware monitoring (S.M.A.R.T., casing cooling and temperature, CPU and RAM load) Management • Log management and email notification • NAS OS Installer for diskless setup, data recovery and restore to factory settings • Product discovery with Seagate Network Assistant 1 Tested in RAID 5 configuration utilizing load balancing for Ethernet ports. Actual performance may vary depending on system environment. -
The Application Usage and Risk Report an Analysis of End User Application Trends in the Enterprise
The Application Usage and Risk Report An Analysis of End User Application Trends in the Enterprise 8th Edition, December 2011 Palo Alto Networks 3300 Olcott Street Santa Clara, CA 94089 www.paloaltonetworks.com Table of Contents Executive Summary ........................................................................................................ 3 Demographics ............................................................................................................................................. 4 Social Networking Use Becomes More Active ................................................................ 5 Facebook Applications Bandwidth Consumption Triples .......................................................................... 5 Twitter Bandwidth Consumption Increases 7-Fold ................................................................................... 6 Some Perspective On Bandwidth Consumption .................................................................................... 7 Managing the Risks .................................................................................................................................... 7 Browser-based Filesharing: Work vs. Entertainment .................................................... 8 Infrastructure- or Productivity-Oriented Browser-based Filesharing ..................................................... 9 Entertainment Oriented Browser-based Filesharing .............................................................................. 10 Comparing Frequency and Volume of Use -
Building Large-Scale Distributed Applications on Top of Self-Managing Transactional Stores
Building large-scale distributed applications on top of self-managing transactional stores June 3, 2010 Peter Van Roy with help from SELFMAN partners Overview Large-scale distributed applications Application structure: multi-tier with scalable DB backend Distribution structure: peer-to-peer or cloud-based DHTs and transactions Basics of DHTs Data replication and transactions Scalaris and Beernet Programming model and applications CompOz library and Kompics component model DeTransDraw and Distributed Wikipedia Future work Mobile applications, cloud computing, data-intensive computing Programming abstractions for large-scale distribution Application structure What can be a general architecture for large-scale distributed applications? Start with a database backend (e.g., IBM’s “multitier”) Make it distributed with distributed transactional interface Keep strong consistency (ACID properties) Allow large numbers of concurrent transactions Horizontal scalability is the key Vertical scalability is a dead end “NoSQL”: Buzzword for horizontally scalable databases that typically don’t have a complete SQL interface Key/value store or column-oriented ↑ our choice (simplicity) The NoSQL Controversy NoSQL is a current trend in non-relational databases May lack table schemas, may lack ACID properties, no join operations Main advantages are excellent performance, with good horizontal scalability and elasticity (ideal fit to clouds) SQL databases have good vertical scalability but are not elastic Often only weak consistency guarantees, such as eventual consistency (e.g., Google BigTable) Some exceptions: Cassandra also provides strong consistency, Scalaris and Beernet provide a key-value store with transactions and strong consistency Distribution structure Two main infrastructures for large-scale applications Peer-to-peer: use of client machines ← our choice (loosely coupled) Very popular style, e.g., BitTorrent, Skype, Wuala, etc. -
Mass Surveillance
Mass Surveillance Mass Surveillance What are the risks for the citizens and the opportunities for the European Information Society? What are the possible mitigation strategies? Part 1 - Risks and opportunities raised by the current generation of network services and applications Study IP/G/STOA/FWC-2013-1/LOT 9/C5/SC1 January 2015 PE 527.409 STOA - Science and Technology Options Assessment The STOA project “Mass Surveillance Part 1 – Risks, Opportunities and Mitigation Strategies” was carried out by TECNALIA Research and Investigation in Spain. AUTHORS Arkaitz Gamino Garcia Concepción Cortes Velasco Eider Iturbe Zamalloa Erkuden Rios Velasco Iñaki Eguía Elejabarrieta Javier Herrera Lotero Jason Mansell (Linguistic Review) José Javier Larrañeta Ibañez Stefan Schuster (Editor) The authors acknowledge and would like to thank the following experts for their contributions to this report: Prof. Nigel Smart, University of Bristol; Matteo E. Bonfanti PhD, Research Fellow in International Law and Security, Scuola Superiore Sant’Anna Pisa; Prof. Fred Piper, University of London; Caspar Bowden, independent privacy researcher; Maria Pilar Torres Bruna, Head of Cybersecurity, Everis Aerospace, Defense and Security; Prof. Kenny Paterson, University of London; Agustín Martin and Luis Hernández Encinas, Tenured Scientists, Department of Information Processing and Cryptography (Cryptology and Information Security Group), CSIC; Alessandro Zanasi, Zanasi & Partners; Fernando Acero, Expert on Open Source Software; Luigi Coppolino,Università degli Studi di Napoli; Marcello Antonucci, EZNESS srl; Rachel Oldroyd, Managing Editor of The Bureau of Investigative Journalism; Peter Kruse, Founder of CSIS Security Group A/S; Ryan Gallagher, investigative Reporter of The Intercept; Capitán Alberto Redondo, Guardia Civil; Prof. Bart Preneel, KU Leuven; Raoul Chiesa, Security Brokers SCpA, CyberDefcon Ltd.; Prof. -
I – Basic Notions
Provable Security in the Computational Model I – Basic Notions David Pointcheval MPRI – Paris Ecole normale superieure,´ CNRS & INRIA ENS/CNRS/INRIA Cascade David Pointcheval 1/71 Outline Cryptography Provable Security Basic Security Notions Conclusion ENS/CNRS/INRIA Cascade David Pointcheval 2/71 Cryptography Outline Cryptography Introduction Kerckhoffs’ Principles Formal Notations Provable Security Basic Security Notions Conclusion ENS/CNRS/INRIA Cascade David Pointcheval 3/71 Secrecy of Communications One ever wanted to communicate secretly The treasure Bob is under Alice …/... ENS/CNRS/INRIA Cascade David Pointcheval 4/71 Secrecy of Communications One ever wanted to communicate secretly The treasure Bob is under Alice …/... ENS/CNRS/INRIA Cascade David Pointcheval 4/71 Secrecy of Communications One ever wanted to communicate secretly The treasure Bob is under Alice …/... ENS/CNRS/INRIA Cascade David Pointcheval 4/71 Secrecy of Communications One ever wanted to communicate secretly The treasure Bob is under Alice …/... ENS/CNRS/INRIA Cascade David Pointcheval 4/71 Secrecy of Communications One ever wanted to communicate secretly The treasure Bob is under Alice …/... With the all-digital world, security needs are even stronger ENS/CNRS/INRIA Cascade David Pointcheval 4/71 Old Methods Substitutions and permutations Security relies on the secrecy of the mechanism ENS/CNRS/INRIA Cascade David Pointcheval 5/71 Old Methods Substitutions and permutations Security relies on the secrecy of the mechanism Scytale - Permutation ENS/CNRS/INRIA -
Short History Polybius's Square History – Ancient Greece
CRYPTOLOGY : CRYPTOGRAPHY + CRYPTANALYSIS Polybius’s square Polybius, Ancient Greece : communication with torches Cryptology = science of secrecy. How : 12345 encipher a plaintext into a ciphertext to protect its secrecy. 1 abcde The recipient deciphers the ciphertext to recover the plaintext. 2 f g h ij k A cryptanalyst shouldn’t complete a successful cryptanalysis. 3 lmnop 4 qrstu Attacks [6] : 5 vwxyz known ciphertext : access only to the ciphertext • known plaintexts/ciphertexts : known pairs TEXT changed in 44,15,53,44. Characteristics • (plaintext,ciphertext) ; search for the key encoding letters by numbers chosen plaintext : known cipher, chosen cleartexts ; • shorten the alphabet’s size • search for the key encode• a character x over alphabet A in y finite word over B. Polybius square : a,...,z 1,...,5 2. { } ! { } Short history History – ancient Greece J. Stern [8] : 3 ages : 500 BC : scytale of Sparta’s generals craft age : hieroglyph, bible, ..., renaissance, WW2 ! • technical age : complex cipher machines • paradoxical age : PKC • Evolves through maths’ history, computing and cryptanalysis : manual • electro-mechanical • by computer Secret key : diameter of the stick • History – Caesar Goals of cryptology Increasing number of goals : secrecy : an enemy shouldn’t gain access to information • authentication : provides evidence that the message • comes from its claimed sender signature : same as auth but for a third party • minimality : encipher only what is needed. • Change each char by a char 3 positions farther A becomes d, B becomes e... The plaintext TOUTE LA GAULE becomes wrxwh od jdxoh. Why enciphering ? The tools Yesterday : • I for strategic purposes (the enemy shouldn’t be able to read messages) Information Theory : perfect cipher I by the church • Complexity : most of the ciphers just ensure computational I diplomacy • security Computer science : all make use of algorithms • Mathematics : number theory, probability, statistics, Today, with our numerical environment • algebra, algebraic geometry,.. -
Taxonomy for Anti-Forensics Techniques & Countermeasures
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by St. Cloud State University St. Cloud State University theRepository at St. Cloud State Culminating Projects in Information Assurance Department of Information Systems 4-2020 Taxonomy for Anti-Forensics Techniques & Countermeasures Ziada Katamara [email protected] Follow this and additional works at: https://repository.stcloudstate.edu/msia_etds Recommended Citation Katamara, Ziada, "Taxonomy for Anti-Forensics Techniques & Countermeasures" (2020). Culminating Projects in Information Assurance. 109. https://repository.stcloudstate.edu/msia_etds/109 This Starred Paper is brought to you for free and open access by the Department of Information Systems at theRepository at St. Cloud State. It has been accepted for inclusion in Culminating Projects in Information Assurance by an authorized administrator of theRepository at St. Cloud State. For more information, please contact [email protected]. Taxonomy for Anti-Forensics Techniques and Countermeasures by Ziada Katamara A Starred Paper Submitted to the Graduate Faculty of St Cloud State University in Partial Fulfillment of the Requirements for the Degree Master of Science in Information Assurance June, 2020 Starred Paper Committee: Abdullah Abu Hussein, Chairperson Lynn A Collen Balasubramanian Kasi 2 Abstract Computer Forensic Tools are used by forensics investigators to analyze evidence from the seized devices collected at a crime scene or from a person, in such ways that the results or findings can be used in a court of law. These computer forensic tools are very important and useful as they help the law enforcement personnel to solve crimes. Computer criminals are now aware of the forensics tools used; therefore, they use countermeasure techniques to efficiently obstruct the investigation processes.