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Lecturer, University of Hull Centre for Internet Computing

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Presentation on theme: "Lecturer, University of Hull Centre for Internet Computing"— Presentation transcript:

1 Lecturer, University of Hull Centre for Internet Computing
Digital Evidence Angus M. Marshall BSc CEng MBCS FRSA Lecturer, University of Hull Centre for Internet Computing Director, n-gate ltd. Programme Chair, FIDES 2004

2 Content Digital Evidence Forensic Computing Future Trends
Sources & Role Forensic Computing Principles & Practice Future Trends Challenges

3 Digital Evidence Evidence in digital form
Data recovered from digital devices Data relating to digital devices

4 Source of digital evidence
More than the obvious PCs PDAs Mobile Phones GPS Digital TV systems CCTV Other Embedded Devices

5 Use of digital evidence
Nature of crime determines probability of digital evidence & usefulness of evidence Evidence of criminal act Copyright theft, identity theft, blackmail etc. Alibi / presence at crime scene Habits & interests (propensity to commit crime) “Malice aforethought” Maps, knives ordered from e-bay...... Information retrieval “H-bombs for dummies”

6 Taxonomy * Application guides investigative strategy
Potential sources & nature of evidence Highlights challenges *Marshall & Tompsett, “Spam 'n' Chips”, Science & Justice, 2002

7 Next steps Once the nature of the activity is determined, investigation can proceed Carefully

8 Principles and Practice
Forensic Computing Principles and Practice

9 Forensic Computing – purpose
Forensic computing techniques may be deployed to : Recover evidence from digital sources Witness – factual only Interpret recovered evidence Expert witness – opinion & experience

10 Forensic Computing – definition
Relating to the recovery, examination and/or production of evidence for legal purposes Computing Through the application of computer-based techniques

11 Alternative definition
“...the application of science and engineering to the legal problem of digital evidence. It is a synthesis of science and law” Special Agent Mark Pollitt, FBI – quoted in “Forensic Computing : A practitioner's guide” by Sammes & Jenkinson

12 Conventional Sources of Evidence
Magnetic Media Disks, Tapes Optical media CD, DVD Data e.g. Log files, Deleted files, Swap space Paper documents printing, bills etc. Handhelds, mobile phones etc. (solid-state transient memory)

13 ACPO principles Association of Chief Police Officers of England, Wales and Northern Ireland Good Practice Guide for Computer Based Evidence, Version 2. ACPO Crime Committee, 23 June 1999 Similar guidelines for Scotland New version out November 2003

14 ACPO principles 4 principles relating to the recovery and investigation of computer based evidence intended to guarantee the integrity of evidence and allow accurate replication of results remove doubt / opportunity for challenge in court

15 Principle 1 No action taken by Police or their agents should change data held on a computer or other media which may subsequently be relied upon in Court. Why ?

16 Principle 2 In exceptional circumstances where a person finds it necessary to access original data held on a target computer that person must be competent to do so and to give evidence explaining the relevance and implications of their actions.

17 Principle 3 An audit trail or other record of all processes applied to computer-based evidence should be created and preserved. An independent third party should be able to examine those processes and achieve the same result.

18 Principle 4 The Officer in charge of the case is responsible for ensuring that the law and these principles are adhered to. This applies to the possession of, and access to, information contained in a computer. They must be satisfied that anyone accessing the computer, or any use of a copying device, complies with these laws and principles.

19 Caveats Apply primarily to “single source of evidence” investigations
Networks cause problems Locard's principle may not apply Does not allow for ‘real-time’ investigation Assumes that equipment can be seized and investigated offline

20 Constraints Human Rights Act Regulation of Investigatory Powers Act
P.A.C.E. & equivalents Data Protection Act(s) Computer Misuse Act Direct impact on validity of evidence, rights of the suspect, ability to investigate

21 Internet Investigations – Special Features
Locality of Offence* RIPA / HR / DP / CM contraventions Covert nature sysadmins unwilling to disclose real time requirement Network configuration High disk activity systems little coordination of “intelligence” CERTs try *Marshall & Tompsett, “Spam 'n' Chips”, Science & Justice, 2002

22 Static Evidence / Single Source
“Standard” case Static Evidence / Single Source

23 Background Role of the forensic examiner Retrieve any and all evidence
Provide possible interpretations How the evidence got there What it may mean Implication The “illicit” activity has already been identified Challenge is to determine who did it and how

24 Single source cases According to Marshall &Tompsett [1]
Any non-internet connected system can be treated as a single source of evidence, following the same examination principles as a single computer Even a large network Is this a valid proposition ?

25 Single source Implies that the locus of evidence can be determined
i.e. There are no unidentified or external entities involved Even in a large network, all nodes can be identified as long as the network is closed (i.e. The limit of extent of the network can be determined) “Computer-assisted/enabled/only” categories.

26 Static Evidence Time is the enemy
Primary sources of evidence are 2o storage devices Floppies, hard disks, CD, Zip etc. Log files, swap files, slack space, temporary files Data may be deleted, overwritten, damaged or compromised if not captured quickly (See ACPO guidelines – No.1)

27 Standard seizure procedure [2]
Quarantine the scene Move everyone away from the suspect equipment Kill communications Modem, network Visual inspection Photograph, notes Screensavers ? Kill power Seize all associated equipment and removable media Bag 'n' tag immediately Record actions Ask user/owner for passwords

28 Imaging and Checksumming
After seizure, before examination Make forensically sound copies of media Produce image files on trusted workstation Produce checksums For integrity checking

29 Why image ? Why not just boot the suspect equipment and check it directly

30 Forensically sound copy
Byte by byte, block by block copy of ALL data on the medium, including deleted and/or bad blocks. Device level and logical level (partitions) Identical to the original Specialist programs (e.g. Encase) Adapt standard tools (e.g. “dd” on Unix/Linux/*BSD MacOS X)

31 Checksumming During/immediately after imaging
Calculate checksum files for the image. Ideally 1 per block. Use later to verify that Image file has not changed Source media has not been modified Difficult at device level – differences between devices. (manufacturing defects) Possible algorithms MD5, SHA, SNEFRU

32 Sources of evidence in the image
Image is a forensically sound copy Can be treated as the original disk Examine for “live” files Deleted files Swap space Slack space

33 Live Files “live” files Rely on suspect not having time to take action
Files in use on the system Saved data Temporary files Cached files Rely on suspect not having time to take action

34 Deleted files O/S rarely deletes all data associated with a file
More commonly marks space used by file as available for re-use e.g. In FAT systems, change 1st character of name to “deleted” marker In Unix/Linux – add inodes to free list Data may still be on disk, recoverable using sector-level tools

35 Swap space Both O/S and program swap
Areas of 10 memory swapped out to disk may contain usable data Created by O/S during scheduling Created by programs when required

36 Slack space Files rarely completely fill all allocated sectors
e.g. Sector size of 512 bytes, file size 514 bytes – 2 sectors, but one only contains 2 bytes of real data Disk controller must write a complete sector. Using DMA, grabs “spare” bytes from 10 memory and pads the sector Padding may contain useful evidence, potentially from past programs – same rules apply to RAM as Disk! (unless powered down)

37 What about edited files ?
e.g. Entries deleted from log files ?

38 Recovered data Needs thorough analysis to reconstruct full or partial files May not contain sufficient contextual information e.g. missing file types, timestamps, filenames etc.

39 Challenges Current & Future

40 Challenges - Current Recovered data may be Analytical challenges
Hashed Encrypted Steganographic Analytical challenges

41 Hashed Data Non-reversible process
i.e. Original data cannot be determined from the hashed value cf. Unix/Linux password files Aka (erroneously) “one-way” encryption “Brute Force” attack may be required Is this good enough for legal purposes ?

42 Encryption Purpose Costly for criminal, costly for investigator
To increase the cost of recovery to a point where it is not worth the effort Symmetric and Asymmetric Reversible – encrypted version contains full representation of original Costly for criminal, costly for investigator

43 Steganography Information hiding e.g.
Maps tattooed on heads Books with pinpricks through letters Low-order bits in image files Difficult to detect, plenty of free tools Often combined with cryptographic techniques.

44 Worse yet CryptoSteg SteganoCrypt Combination of two techniques...
layered

45 Additional challenges
Emerging technologies Wireless Bluetooth “Bluejacking”, bandwidth theft b/g/a Insecure networks, Insecure devices Bandwidth theft, storage space theft Forms of identity theft

46 Additional challenges
Viral propagation Proxy implantation Sobig, SuperZonda Pornography, SPAM Evidence “planting” Proven defence

47 Case studies Choose from : IPR theft Identity theft & financial fraud
Murder Street crime (mugging) Blackmail Fraudulent trading etc. etc. etc.

48 Conclusion Digital Evidence now forms an almost essential adjunct to other investigative sciences Can be a source of “prima facie” evidence Requires specialist knowledge Will continue to evolve Current research areas : Silicon DNA profile, Steg. Detection, ID theft


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