skip to main content
10.1145/2995289.2995290acmconferencesArticle/Chapter ViewAbstractPublication PagesccsConference Proceedingsconference-collections
research-article

Security of CCTV and Video Surveillance Systems: Threats, Vulnerabilities, Attacks, and Mitigations

Published:28 October 2016Publication History

ABSTRACT

Video surveillance, closed-circuit TV and IP-camera systems became virtually omnipresent and indispensable for many organizations, businesses, and users. Their main purpose is to provide physical security, increase safety, and prevent crime. They also became increasingly complex, comprising many communication means, embedded hardware and non-trivial firmware. However, most research to date focused mainly on the privacy aspects of such systems, and did not fully address their issues related to cyber-security in general, and visual layer (i.e., imagery semantics) attacks in particular. In this paper, we conduct a systematic review of existing and novel threats in video surveillance, closed-circuit TV and IP-camera systems based on publicly available data. The insights can then be used to better understand and identify the security and the privacy risks associated with the development, deployment and use of these systems. We study existing and novel threats, along with their existing or possible countermeasures, and summarize this knowledge into a comprehensive table that can be used in a practical way as a security checklist when assessing cyber-security level of existing or new CCTV designs and deployments. We also provide a set of recommendations and mitigations that can help improve the security and privacy levels provided by the hardware, the firmware, the network communications and the operation of video surveillance systems. We hope the findings in this paper will provide a valuable knowledge of the threat landscape that such systems are exposed to, as well as promote further research and widen the scope of this field beyond its current boundaries.

References

  1. ABUS TVIP 11550/21550 Multiple vulnerabilities. http://www.securityfocus.com/archive/1/520045.Google ScholarGoogle Scholar
  2. Anonymous authenticated access to MJPEG stream. http://goo.gl/sYkUAF.Google ScholarGoogle Scholar
  3. 'Baby Monitor Hack' Could Happen To 40,000 Other Foscam Users. http://goo.gl/2cdYy0.Google ScholarGoogle Scholar
  4. BuggedPlanet -- Surveillance Industry and Country's Actings. http://buggedplanet.info/.Google ScholarGoogle Scholar
  5. CVE-2013--1391 -- File disclosure in Hunt DVR and generic brands, discloses authentication information.Google ScholarGoogle Scholar
  6. CVE-2013--2560 -- Directory traversal in the web interface on Foscam devices.Google ScholarGoogle Scholar
  7. CVE-2013--4981 -- Denial-of-service in AVTECH AVN801 DVR.Google ScholarGoogle Scholar
  8. CVE-2013--6023 -- Directory traversal in the TVT TD-2308SS-B DVR.Google ScholarGoogle Scholar
  9. CVE details -- CCTV systems. http://goo.gl/IB1Hk7.Google ScholarGoogle Scholar
  10. CVE details -- DVR systems. http://goo.gl/Xmv1jN.Google ScholarGoogle Scholar
  11. CVE details -- IP cameras. http://goo.gl/ObpWCg.Google ScholarGoogle Scholar
  12. FTC settles with Trendnet after 'thousands' of home security cameras were hacked. http://goo.gl/94Ibmv.Google ScholarGoogle Scholar
  13. Full disclosure -- CCTV systems. http://insecure.org/search.html?q=cctv.Google ScholarGoogle Scholar
  14. Full disclosure -- DVR systems. http://insecure.org/search.html?q=dvr.Google ScholarGoogle Scholar
  15. Full disclosure -- IP cameras. http://insecure.org/search.html?q=IP%20camera.Google ScholarGoogle Scholar
  16. Google Glass hacked by the image of a malicious QR code. http://goo.gl/Qqh72x.Google ScholarGoogle Scholar
  17. How A Creep Hacked A Baby Monitor To Say Lewd Things To A 2-Year-Old. http://goo.gl/92yg9G.Google ScholarGoogle Scholar
  18. How to ZAP a Camera: Using Lasers to Temporarily Neutralize Camera Sensors. http://www.naimark.net/projects/zap/howto.html.Google ScholarGoogle Scholar
  19. Internet Census 2012 -- Port scanning /0 using insecure embedded devices. http://internetcensus2012.bitbucket.org.Google ScholarGoogle Scholar
  20. Israeli Road Control System hacked -- malware to hit the security camera apparatus in the Carmel Tunnel toll. http://goo.gl/F5I0ou.Google ScholarGoogle Scholar
  21. Mal au Pixel# Festival -- CCTV Sniffing Workshop. http://vimeo.com/57881594.Google ScholarGoogle Scholar
  22. Oakland Domain Awareness Center (DAC). http://oaklandwiki.org/Domain_Awareness_Center.Google ScholarGoogle Scholar
  23. Ray Sharp CCTV DVRs Password Retrieval. http://goo.gl/Hnp3TO.Google ScholarGoogle Scholar
  24. SHODAN -- Computer Search Engine. http://www.shodan.io.Google ScholarGoogle Scholar
  25. Swann Song DVRs Insecurity. http://goo.gl/oY3z3w.Google ScholarGoogle Scholar
  26. Anonymous. Insecam Project -- The world biggest directory of online (insecure) surveillance security cameras. http://insecam.org.Google ScholarGoogle Scholar
  27. Anonymous. TRENDnet Exposed. https://twitter.com/trendnetexposed.Google ScholarGoogle Scholar
  28. J. Aron. Want to rob a bank? Hack your way in. New Scientist, 220(2937):22, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  29. J. Bau, E. Bursztein, D. Gupta, and J. C. Mitchell. State of the Art: Automated Black-Box Web Application Vulnerability Testing. In IEEE Symposium on Security and Privacy, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. J. Bellardo and S. Savage. 802.11 denial-of-service attacks: Real vulnerabilities and practical solutions. In Proceedings of the USENIX Security Symposium, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. G. Berg, I. Davidson, M.-Y. Duan, and G. Paul. Searching for hidden messages: Automatic detection of steganography. In IAAI, pages 51--56, 2003.Google ScholarGoogle Scholar
  32. H. Bojinov, E. Bursztein, and D. Boneh. Xcs: Cross channel scripting and its impact on web applications. In Proceedings of the 16th ACM Conference on Computer and Communications Security, CCS '09, pages 420--431, New York, NY, USA, 2009. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. H. Bojinov, E. Bursztein, E. Lovett, and D. Boneh. Embedded management interfaces: Emerging massive insecurity. Blackhat USA, July 2009.Google ScholarGoogle Scholar
  34. M. Brocker and S. Checkoway. iSeeYou: Disabling the MacBook webcam indicator LED. In 23rd USENIX Security Symposium (USENIX Security 14), pages 337--352, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. N. Carlini, P. Mishra, T. Vaidya, Y. Zhang, M. Sherr, C. Shields, D. Wagner, and W. Zhou. Hidden Voice Commands. In 25th USENIX Security Symposium (USENIX Security 16), Austin, TX, 2016.Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. A. Castiglione, M. Cepparulo, A. De Santis, and F. Palmieri. Towards a lawfully secure and privacy preserving video surveillance system. In International Conference on Electronic Commerce and Web Technologies, pages 73--84. Springer, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  37. J. Clark, S. Leblanc, and S. Knight. Hardware trojan horse device based on unintended usb channels. In Network and System Security, 2009. NSS'09. Third International Conference on, pages 1--8. IEEE, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. M. Coole, A. Woodward, and C. Valli. Understanding the vulnerabilities in wi-fi and the impact on its use in cctv systems. 2012.Google ScholarGoogle Scholar
  39. A. Costin. Poor Man's Panopticon: Mass CCTV Surveillance for the masses. In PowerOfCommunity, November 2013.Google ScholarGoogle Scholar
  40. A. Costin, J. Zaddach, A. Francillon, and D. Balzarotti. A Large-Scale Analysis of the Security of Embedded Firmwares. In USENIX Security Symposium, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. A. Costin, A. Zarras, and A. Francillon. Automated Dynamic Firmware Analysis at Scale: A Case Study on Embedded Web Interfaces. In ACM Symposium on Information, Computer and Communications Security (ASIACCS), 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. A. Cui, M. Costello, and S. J. Stolfo. When firmware modifications attack: A case study of embedded exploitation. In Proceedings of the Symposium on Network and Distributed System Security (NDSS), 2013.Google ScholarGoogle Scholar
  43. A. Cui and S. J. Stolfo. A quantitative analysis of the insecurity of embedded network devices: Results of a wide-area scan. In Proceedings of the 26th Annual Computer Security Applications Conference, ACSAC '10, pages 97--106, New York, NY, USA, 2010. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. A. Dabrowski and M. Slunsky. Hacking CCTV -- Watching the watchers, having fun with cctv cameras, making yourself invisible. In 22nd Chaos Communication Congress, 2005.Google ScholarGoogle Scholar
  45. J. Demme, M. Maycock, J. Schmitz, A. Tang, A. Waksman, S. Sethumadhavan, and S. Stolfo. On the feasibility of online malware detection with performance counters. In ACM SIGARCH Computer Architecture News, volume 41, pages 559--570. ACM, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. A. Dessiatnikoff, Y. Deswarte, E. Alata, and V. Nicomette. Potential attacks on onboard aerospace systems. IEEE Security & Privacy, (4):71--74, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. DigitalMunition. Owning a Police Car and It's DVR. http://www.digitalmunition.com/OwningCopCar.pdf.Google ScholarGoogle Scholar
  48. K. El Defrawy, A. Francillon, D. Perito, and G. Tsudik. Smart: Secure and minimal architecture for (establishing a dynamic) root of trust. In Proceedings of the Network & Distributed System Security Symposium (NDSS), San Diego, CA, 2012.Google ScholarGoogle Scholar
  49. J. Fridrich, M. Goljan, and R. Du. Reliable detection of lsb steganography in color and grayscale images. In Proceedings of the 2001 workshop on Multimedia and security: new challenges, pages 27--30. ACM, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. M. Gasser. Building a secure computer system. 1988. Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. O. Gayer, O. Wilder, and I. Zeifman. CCTV Botnet In Our Own Back Yard. https://www.incapsula.com/blog/cctv-ddos-botnet-back-yard.html.Google ScholarGoogle Scholar
  52. I. J. Goodfellow, J. Shlens, and C. Szegedy. Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572, 2014.Google ScholarGoogle Scholar
  53. M. Guri, O. Hasson, G. Kedma, and Y. Elovici. Visisploit: An optical covert-channel. arXiv preprint arXiv:1607.03946, 2016.Google ScholarGoogle Scholar
  54. M. Guri, A. Kachlon, O. Hasson, G. Kedma, Y. Mirsky, and Y. Elovici. Gsmem: data exfiltration from air-gapped computers over gsm frequencies. In 24th USENIX Security Symposium (USENIX Security 15), pages 849--864, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. M. Guri, G. Kedma, A. Kachlon, and Y. Elovici. Airhopper: Bridging the air-gap between isolated networks and mobile phones using radio frequencies. In Malicious and Unwanted Software: The Americas (MALWARE), 2014 9th International Conference on, pages 58--67. IEEE, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  56. M. Guri, M. Monitz, Y. Mirski, and Y. Elovici. Bitwhisper: Covert signaling channel between air-gapped computers using thermal manipulations. In 2015 IEEE 28th Computer Security Foundations Symposium, pages 276--289. IEEE, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  57. M. Guri, Y. Solewicz, A. Daidakulov, and Y. Elovici. Fansmitter: Acoustic data exfiltration from (speakerless) air-gapped computers. arXiv preprint arXiv:1606.05915, 2016.Google ScholarGoogle Scholar
  58. M. Hanspach and M. Goetz. On covert acoustical mesh networks in air. arXiv preprint arXiv:1406.1213, 2014.Google ScholarGoogle Scholar
  59. C. Heffner. Exploiting Surveillance Cameras. Like a Hollywood Hacker. In BlackHat US, 2013.Google ScholarGoogle Scholar
  60. D. Hely, F. Bancel, M.-L. Flottes, and B. Rouzeyre. Secure scan techniques: a comparison. In IEEE International On-Line Testing Symposium (IOLTS), 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  61. iPower Technologies. Hidden Virus Discovered in Martel Police Body Camera. http://www.goipower.com/?pageId=40, November 2015. Accessed: July 25, 2016.Google ScholarGoogle Scholar
  62. iSpy. iSpyConnect -- the world?s most popular open source video surveillance application. https://www.ispyconnect.com/sources.aspx, 2007. Accessed: July 26, 2016.Google ScholarGoogle Scholar
  63. N. Jenkins. 245 million video surveillance cameras installed globally in 2014. June 2015.Google ScholarGoogle Scholar
  64. U. Johannes. This is why your DVR attacked my Synology Disk Station (and now with Bitcoin Miner!), April 2014.Google ScholarGoogle Scholar
  65. A. Kharraz, E. Kirda, W. Robertson, D. Balzarotti, and A. Francillon. Optical delusions: A study of malicious QR codes in the wild. In 2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, pages 192--203. IEEE, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  66. A. Kidman. How A Prison Had Its CCTV Hacked. http://goo.gl/sKombD, September 2012.Google ScholarGoogle Scholar
  67. G.-W. Kim and J.-W. Han. Security model for video surveillance system. In International Conference on ICT Convergence (ICTC). IEEE, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  68. D. Kriesel. Xerox scanners/photocopiers randomly alter numbers in scanned documents, 2014.Google ScholarGoogle Scholar
  69. J. Kuboviak. Legal admissibility of digital video recordings. LAW AND ORDER-WILMETTE THEN DEERFIELD-, 52(4):92--99, 2004.Google ScholarGoogle Scholar
  70. M. G. Kuhn and R. J. Anderson. Soft tempest: Hidden data transmission using electromagnetic emanations. In International Workshop on Information Hiding, pages 124--142. Springer, 1998.Google ScholarGoogle ScholarCross RefCross Ref
  71. I.-S. Lee and S. Y. Wan. Security Requirements for Network CCTV. World Academy of Science, 70, 2010.Google ScholarGoogle Scholar
  72. Y. Liu, P. Ning, H. Dai, and A. Liu. Randomized differential dsss: Jamming-resistant wireless broadcast communication. In INFOCOM. IEEE, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  73. J. Loughry and D. A. Umphress. Information leakage from optical emanations. ACM Transactions on Information and System Security (TISSEC), 5(3):262--289, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  74. D. Maass, C. Quintin, and EFF. License Plate Readers Exposed!, October 2015.Google ScholarGoogle Scholar
  75. A. Mahendran and A. Vedaldi. Understanding deep image representations by inverting them. In 2015 IEEE conference on computer vision and pattern recognition (CVPR), pages 5188--5196. IEEE, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  76. MajorMalfuntion. Old Skewl Hacking -- InfraRed updated. In 22nd Chaos Communication Congress, 2005.Google ScholarGoogle Scholar
  77. J. Marpet. Physical Security in a Networked World: Video Analytics, Video Surveillance, and You. In DefCon, 2010.Google ScholarGoogle Scholar
  78. Y. Mirsky, M. Guri, and Y. Elovici. Hvacker: Bridging the air-gap by manipulating the environment temperature.Google ScholarGoogle Scholar
  79. T. Morkel, J. H. Eloff, and M. S. Olivier. An overview of image steganography. In ISSA, pages 1--11, 2005.Google ScholarGoogle Scholar
  80. K. Mowery, E. Wustrow, T. Wypych, C. Singleton, C. Comfort, E. Rescorla, J. A. Halderman, H. Shacham, and S. Checkoway. Security analysis of a full-body scanner. In 23rd USENIX Security Symposium (USENIX Security 14), pages 369--384, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  81. C. Mulliner and B. Michéle. Read it twice! a mass-storage-based TOCTTOU attack. In Proceedings of the 6th USENIX conference on Offensive Technologies, pages 11--11. USENIX Association, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  82. J. Newsome and D. Song. Dynamic taint analysis for automatic detection, analysis, and signature generation of exploits on commodity software. 2005.Google ScholarGoogle Scholar
  83. A. Nguyen, J. Yosinski, and J. Clune. Deep neural networks are easily fooled: High confidence predictions for unrecognizable images. In 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 427--436. IEEE, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  84. R. K. Nichols and P. C. Lekkas. Wireless security. McGraw-Hill New York.Google ScholarGoogle Scholar
  85. J. Obermaier and M. Hutle. Analyzing the Security and Privacy of Cloud-based Video Surveillance Systems. In Proceedings of the 2nd ACM International Workshop on IoT Privacy, Trust, and Security, pages 22--28. ACM, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  86. M. Olson. Beware, even things on Amazon come with embedded malware?. http://artfulhacker.com/post/142519805054/beware-even-things-on-amazon-come, April 2016. Accessed: July 25, 2016.Google ScholarGoogle Scholar
  87. OWASP. Buffer Overflow. owasp.org/index.php/Buffer_overflow_attack.Google ScholarGoogle Scholar
  88. OWASP. Command Injection. owasp.org/index.php/Command_Injection.Google ScholarGoogle Scholar
  89. OWASP. Information Leakage. owasp.org/index.php/Information_Leakage.Google ScholarGoogle Scholar
  90. OWASP. Path Traversal. owasp.org/index.php/Path_Traversal.Google ScholarGoogle Scholar
  91. OWASP. Top 10 Vulnerabilities 2013. owasp.org/index.php/Top_10_2013-Top_10.Google ScholarGoogle Scholar
  92. S. J. O?Malley and K.-K. R. Choo. Bridging the air gap: Inaudible data exfiltration by insiders. In 20th Americas Conference on Information Systems (AMCIS 2014), pages 7--10, 2014.Google ScholarGoogle Scholar
  93. D. Papp, Z. Ma, and L. Buttyan. Embedded systems security: Threats, vulnerabilities, and attack taxonomy. In Annual Conference on Privacy, Security and Trust (PST). IEEE, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  94. T.-S. Park and M.-S. Jun. User authentication protocol for blocking malicious user in Network CCTV environment. In Computer Sciences and Convergence Information Technology (ICCIT), 2011 6th International Conference on, pages 18--24. IEEE, 2011.Google ScholarGoogle Scholar
  95. C. Pöpper, M. Strasser, and S. Capkun. Jamming-resistant broadcast communication without shared keys. In USENIX security Symposium, pages 231--248, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  96. ProCheckup. Owning Big Brother: Multiple vulnerabilities on Axis 2100.Google ScholarGoogle Scholar
  97. N. Provos and P. Honeyman. Hide and seek: An introduction to steganography. IEEE Security & Privacy, 1(3):32--44, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  98. C. Pu and J. Wei. A methodical defense against tocttou attacks: The edgi approach. In International Symposium on Secure Software Engineering (ISSSE), 2006.Google ScholarGoogle Scholar
  99. G. Ritt and B. Eberle. Sensor protection against laser dazzling. In SecurityGoogle ScholarGoogle Scholar
  100. Defence, pages 783404--783404. International Society for Optics and Photonics, 2010.Google ScholarGoogle Scholar
  101. E. Ronen and A. Shamir. Extended Functionality Attacks on IoT Devices: The Case of Smart Lights. In 2016 IEEE European Symposium on Security and Privacy (EuroS&P), pages 3--12. IEEE, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  102. E. J. Schwartz, T. Avgerinos, and D. Brumley. All you ever wanted to know about dynamic taint analysis and forward symbolic execution (but might have been afraid to ask). In IEEE Symposium on Security and Privacy. IEEE, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  103. V. Sepetnitsky, M. Guri, and Y. Elovici. Exfiltration of information from air-gapped machines using monitor's led indicator. In Intelligence and Security Informatics Conference (JISIC), 2014 IEEE Joint, pages 264--267. IEEE, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  104. S. Shekyan and A. Harutyunyan. To Watch Or To Be Watched. Turning your surveillance camera against you. In HITB Amsterdam, 2013.Google ScholarGoogle Scholar
  105. Shodan. Shodan Images -- an easier way to browse the screenshots that Shodan collects. https://images.shodan.io/.Google ScholarGoogle Scholar
  106. S. Skorobogatov and C. Woods. Breakthrough silicon scanning discovers backdoor in military chip. In E. Prouff and P. Schaumont, editors, Cryptographic Hardware and Embedded Systems -- CHES 2012, volume 7428 of Lecture Notes in Computer Science, pages 23--40. Springer Berlin Heidelberg, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  107. C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus. Intriguing properties of neural networks. arXiv preprint arXiv:1312.6199, 2013.Google ScholarGoogle Scholar
  108. D. H. Titterton. A review of the development of optical countermeasures. In European Symposium on Optics and Photonics for Defence and Security, pages 1--15. International Society for Optics and Photonics, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  109. D. Tsafrir, T. Hertz, D. Wagner, and D. Da Silva. Portably Solving File TOCTTOU Races with Hardness Amplification. In FAST, volume 8, pages 1--18. Google ScholarGoogle ScholarDigital LibraryDigital Library
  110. M. Vuagnoux and S. Pasini. Compromising electromagnetic emanations of wired and wireless keyboards. In USENIX security symposium, pages 1--16, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  111. G. Wei. Evaluation method for jamming effectiveness on electro-optical imaging systems {j}. Opto-Electronic Engineering, 33(2):5--8, 2006.Google ScholarGoogle Scholar
  112. J. Wei and C. Pu. TOCTTOU Vulnerabilities in UNIX-Style File Systems: An Anatomical Study. In FAST, volume 5, pages 12--12, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  113. Y. Xia, Y. Liu, H. Chen, and B. Zang. Cfimon: Detecting violation of control flow integrity using performance counters. In IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2012), pages 1--12. IEEE, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  114. YouTube. The fastest robbery -- 1 min in bank. http://youtu.be/LFArxqcP4MI.Google ScholarGoogle Scholar
  115. J. Zaddach and A. Costin. Embedded devices security and firmware reverse engineering. BlackHat USA, 2013.Google ScholarGoogle Scholar
  116. K. Zetter. CCTV Hack Results In 33M USD Casino Theft. http://goo.gl/zmxVXe.Google ScholarGoogle Scholar
  117. B. Zhu, A. Joseph, and S. Sastry. A taxonomy of cyber attacks on SCADA systems. In International conference on cyber, physical and social computing Internet of things (iThings/CPSCom). IEEE, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Security of CCTV and Video Surveillance Systems: Threats, Vulnerabilities, Attacks, and Mitigations

                Recommendations

                Comments

                Login options

                Check if you have access through your login credentials or your institution to get full access on this article.

                Sign in

                PDF Format

                View or Download as a PDF file.

                PDF

                eReader

                View online with eReader.

                eReader