Difference between revisions of "Cybersecurity References"
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Dowlin, N., Gilad-Bachrach, R., Laine, K., Lauter, K., Naehrig, M., and Wernsing, J. [http://www.microsoft.com/en-us/research/wp-content/uploads/2016/04/CryptonetsTechReport.pdf CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy], 24 Feb 2016 | Dowlin, N., Gilad-Bachrach, R., Laine, K., Lauter, K., Naehrig, M., and Wernsing, J. [http://www.microsoft.com/en-us/research/wp-content/uploads/2016/04/CryptonetsTechReport.pdf CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy], 24 Feb 2016 | ||
| − | Elsayed, G, Shankar, S., Cheung, B., Papernot, N., Kurakin, A. Goodfellow, I., Sohl-Dickstein, J. [http://arxiv.org/pdf/1802.08195.pdf Adversarial Examples that Fool both Human and Computer Vision], 22 May 2018 | + | Elsayed, G, Shankar, S., Cheung, B., Papernot, N., Kurakin, A. Goodfellow, I., and Sohl-Dickstein, J. [http://arxiv.org/pdf/1802.08195.pdf Adversarial Examples that Fool both Human and Computer Vision], 22 May 2018 |
Everitt, T., Krakovna, V., Orseau, L., Hutter, M., and Legg, S [http://static.ijcai.org/proceedings-2017/0656.pdf Reinforcement Learning with a Corrupted Reward Channel], 19 Aug 2017 | Everitt, T., Krakovna, V., Orseau, L., Hutter, M., and Legg, S [http://static.ijcai.org/proceedings-2017/0656.pdf Reinforcement Learning with a Corrupted Reward Channel], 19 Aug 2017 | ||
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Evtimov, I., Eykholt, K., Fernandes, E., Kohno, T., Li, B., Prakash, A., Rahmati, A., and Song, D. [http://arxiv.org/pdf/1707.08945.pdf Robust Physical-World Attacks on Deep Learning Visual Classification], 27 Jul 2017 | Evtimov, I., Eykholt, K., Fernandes, E., Kohno, T., Li, B., Prakash, A., Rahmati, A., and Song, D. [http://arxiv.org/pdf/1707.08945.pdf Robust Physical-World Attacks on Deep Learning Visual Classification], 27 Jul 2017 | ||
| − | Fredrikson, M., Jha, S., Ristenpart, T. [http://www.cs.cmu.edu/~mfredrik/papers/fjr2015ccs.pdf Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures], 12 Oct 2015 | + | Fredrikson, M., Jha, S., and Ristenpart, T. [http://www.cs.cmu.edu/~mfredrik/papers/fjr2015ccs.pdf Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures], 12 Oct 2015 |
| − | Goodfellow, I., Papernot, N., Huang, S.,Duan, Y., Abbeel, P., Clark, J. [http://blog.openai.com/adversarial-example-research/ Attacking Machine Learning with Adversarial Examples], 24 Feb 2017 | + | Goodfellow, I., Papernot, N., Huang, S.,Duan, Y., Abbeel, P., and Clark, J. [http://blog.openai.com/adversarial-example-research/ Attacking Machine Learning with Adversarial Examples], 24 Feb 2017 |
| − | Goodfellow, I., Shlens, J., Szegedy C. [http://arxiv.org/pdf/1412.6572.pdf Explaining and Harnessing Adversarial Examples], 20 Mar 2015 | + | Goodfellow, I., Shlens, J., and Szegedy C. [http://arxiv.org/pdf/1412.6572.pdf Explaining and Harnessing Adversarial Examples], 20 Mar 2015 |
| − | Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y. [http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf Generative Adversarial Nets], 10 Jun 2014 | + | Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y. [http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf Generative Adversarial Nets], 10 Jun 2014 |
Grosse, K., Papernot, N., Manoharan, P., Backes, M., and McDaniel, P [http://www.patrickmcdaniel.org/pubs/esorics17.pdf Adversarial Examples for Malware Detection], 12 Aug 2017 | Grosse, K., Papernot, N., Manoharan, P., Backes, M., and McDaniel, P [http://www.patrickmcdaniel.org/pubs/esorics17.pdf Adversarial Examples for Malware Detection], 12 Aug 2017 | ||
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Grosse, K., Papernot, N., Manoharan, P., Backes, M., and McDaniel, P [http://arxiv.org/pdf/1606.04435.pdf Adversarial Perturbations Against Deep Neural Networks for Malware Classification], 16 Jun 2016 | Grosse, K., Papernot, N., Manoharan, P., Backes, M., and McDaniel, P [http://arxiv.org/pdf/1606.04435.pdf Adversarial Perturbations Against Deep Neural Networks for Malware Classification], 16 Jun 2016 | ||
| − | Grosse, K., Manoharan, P., Papernot, N., Backes, M., McDaniel, P. [http://arxiv.org/pdf/1702.06280.pdf On the (Statistical) Detection of Adversarial Examples], 21 Feb 2017 | + | Grosse, K., Manoharan, P., Papernot, N., Backes, M., and McDaniel, P. [http://arxiv.org/pdf/1702.06280.pdf On the (Statistical) Detection of Adversarial Examples], 21 Feb 2017 |
Gu, T., Dolan-Gavitt, B., and Garg, S. [https://machine-learning-and-security.github.io/papers/mlsec17_paper_51.pdf BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain], 22 Aug 2017 | Gu, T., Dolan-Gavitt, B., and Garg, S. [https://machine-learning-and-security.github.io/papers/mlsec17_paper_51.pdf BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain], 22 Aug 2017 | ||
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Hitawala, S. [http://arxiv.org/pdf/1801.04271.pdf Comparative Study on Generative Adversarial Networks], 12 Jan 2018 | Hitawala, S. [http://arxiv.org/pdf/1801.04271.pdf Comparative Study on Generative Adversarial Networks], 12 Jan 2018 | ||
| − | Hosseini, H., Chen, Y., Kannan, S., Zhang, B., Poovendran, R. [http://arxiv.org/pdf/1703.04318.pdf Blocking Transferability of Adversarial Examples in Black-Box Learning Systems], 13 Mar 2017 | + | Hosseini, H., Chen, Y., Kannan, S., Zhang, B., and Poovendran, R. [http://arxiv.org/pdf/1703.04318.pdf Blocking Transferability of Adversarial Examples in Black-Box Learning Systems], 13 Mar 2017 |
Hosseini, H., Xiao, B. and Poovendran, R., [http://arxiv.org/pdf/1704.05051.pdf Google’s Cloud Vision API Is Not Robust To Noise], 20 Jul 2017 | Hosseini, H., Xiao, B. and Poovendran, R., [http://arxiv.org/pdf/1704.05051.pdf Google’s Cloud Vision API Is Not Robust To Noise], 20 Jul 2017 | ||
| − | Hu, W. | + | Hu, W. and Tan, Y. [http://arxiv.org/pdf/1702.05983.pdf Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN], ..MalGAN 20 Feb 2017 |
| − | Huang, L., Joseph, A., Neson, B., Rubinstein, B., Tygar, J.D. [http://people.eecs.berkeley.edu/~tygar/papers/SML2/Adversarial_AISEC.pdf Adversarial Machine Learning], Oct 2011 | + | Huang, L., Joseph, A., Neson, B., Rubinstein, B., and Tygar, J.D. [http://people.eecs.berkeley.edu/~tygar/papers/SML2/Adversarial_AISEC.pdf Adversarial Machine Learning], Oct 2011 |
| − | Jin J., Dundar, A., Culurciello, E. [http://arxiv.org/pdf/1511.06306.pdf Robust Convolutional Neural Networks under Adversarial Noise], 25 Feb 2016 | + | Jin J., Dundar, A., and Culurciello, E. [http://arxiv.org/pdf/1511.06306.pdf Robust Convolutional Neural Networks under Adversarial Noise], 25 Feb 2016 |
| − | Kantarcioglu, M. | + | Kantarcioglu, M. and Xi, B. [http://www.utdallas.edu/~muratk/CCS-tutorial.pdf Adversarial Data Mining for Cyber Security], 28 Oct 2016 |
| − | Kantchelian, A., Tygar, J.D., Joseph, A. [https://arxiv.org/pdf/1509.07892.pdf Evasion and Hardening of Tree Ensemble Classifiers], 27 May 2016 | + | Kantchelian, A., Tygar, J.D., and Joseph, A. [https://arxiv.org/pdf/1509.07892.pdf Evasion and Hardening of Tree Ensemble Classifiers], 27 May 2016 |
Kantchelian, A. [http://pdfs.semanticscholar.org/4a8d/97172382144b9906e2cec69d3decb4188fb7.pdf Taming Evasions in Machine Learning Based Detection], 12 Aug 2016 | Kantchelian, A. [http://pdfs.semanticscholar.org/4a8d/97172382144b9906e2cec69d3decb4188fb7.pdf Taming Evasions in Machine Learning Based Detection], 12 Aug 2016 | ||
| − | Kashyap, A., Parmar, R., Agarwal, M., Gupta, H. [http://arxiv.org/pdf/1703.09968.pdf An Evaluation of Digital Image Forgery Detection Approaches], 30 Mar 2017 | + | Kashyap, A., Parmar, R., Agarwal, M., and Gupta, H. [http://arxiv.org/pdf/1703.09968.pdf An Evaluation of Digital Image Forgery Detection Approaches], 30 Mar 2017 |
| − | Kolosnjaji, B., Demontiz, A., Biggio, B., Maiorca, D., Giacinto, G., Eckert, C., Roli, F. [http://arxiv.org/pdf/1803.04173.pdf Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables], 12 Mar 2018 | + | Kolosnjaji, B., Demontiz, A., Biggio, B., Maiorca, D., Giacinto, G., Eckert, C., and Roli, F. [http://arxiv.org/pdf/1803.04173.pdf Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables], 12 Mar 2018 |
| − | Kreuk, F., Barak, A., Aviv-Reuven, S., Baruch, M., Pinkas, B., Keshet, J. [http://www.groundai.com/project/adversarial-examples-on-discrete-sequences-for-beating-whole-binary-malware-detection/ Adversarial Examples on Discrete Sequences for Beating Whole-Binary Malware Detection], 13 Feb 2018 | + | Kreuk, F., Barak, A., Aviv-Reuven, S., Baruch, M., Pinkas, B., and Keshet, J. [http://www.groundai.com/project/adversarial-examples-on-discrete-sequences-for-beating-whole-binary-malware-detection/ Adversarial Examples on Discrete Sequences for Beating Whole-Binary Malware Detection], 13 Feb 2018 |
| − | Kreuk, F., Barak, A., Aviv-Reuven, S., Baruch, M., Pinkas, B., Keshet, J. [http://arxiv.org/pdf/1802.04528.pdf Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples], 13 May 2018 | + | Kreuk, F., Barak, A., Aviv-Reuven, S., Baruch, M., Pinkas, B., and Keshet, J. [http://arxiv.org/pdf/1802.04528.pdf Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples], 13 May 2018 |
| − | Kurakin, A., Goodfellow, I., Bengio, S. [http://arxiv.org/pdf/1607.02533.pdf Adversarial examples in the physical world], 11 Feb 2017 | + | Kurakin, A., Goodfellow, I., and Bengio, S. [http://arxiv.org/pdf/1607.02533.pdf Adversarial examples in the physical world], 11 Feb 2017 |
| − | Laskov, P. | + | Laskov, P. and Lippmann, R. [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.375.4564&rep=rep1&type=pdf Machine Learning in Adversarial Environments], 28 Jun 2010 |
Lewis, L. [http://www.cna.org/cna_files/pdf/DRM-2017-U-016281-Final.pdf Insights for the Third Offset: Addressing Challenges of Autonomy and Artificial Intelligence in Military Operations], Sep 2017 | Lewis, L. [http://www.cna.org/cna_files/pdf/DRM-2017-U-016281-Final.pdf Insights for the Third Offset: Addressing Challenges of Autonomy and Artificial Intelligence in Military Operations], Sep 2017 | ||
| − | Lu, P., Chen, P., Chen, K., Yu, C. [http://arxiv.org/pdf/1805.00310.pdf On the Limitation of MagNet Defense against L1-based Adversarial Examples], 9 May 2018 | + | Lu, P., Chen, P., Chen, K., and Yu, C. [http://arxiv.org/pdf/1805.00310.pdf On the Limitation of MagNet Defense against L1-based Adversarial Examples], 9 May 2018 |
| − | Luo, B., Liu, Y. Wei, L., Xu, Q. [http://arxiv.org/pdf/1801.04693.pdf Towards Imperceptible and Robust Adversarial Example Attacks against Neural], 15 Jan 2018 | + | Luo, B., Liu, Y. Wei, L., and Xu, Q. [http://arxiv.org/pdf/1801.04693.pdf Towards Imperceptible and Robust Adversarial Example Attacks against Neural], 15 Jan 2018 |
| − | Madry, A., Makelov, A., Schmidt, L., Tsipras, D., Vladu, A. [http://arxiv.org/pdf/1706.06083.pdf Towards Deep Learning Models Resistant to Adversarial Attacks], 19 Jun 2017 | + | Madry, A., Makelov, A., Schmidt, L., Tsipras, D., and Vladu, A. [http://arxiv.org/pdf/1706.06083.pdf Towards Deep Learning Models Resistant to Adversarial Attacks], 19 Jun 2017 |
Mayer, M. Norwegian Institute for Defence Studies, Oslo [http://brage.bibsys.no/xmlui/bitstream/handle/11250/2497514/IFS%20Insights_4_2018_Mayer.pdf IFS Insights], Apr 2018 | Mayer, M. Norwegian Institute for Defence Studies, Oslo [http://brage.bibsys.no/xmlui/bitstream/handle/11250/2497514/IFS%20Insights_4_2018_Mayer.pdf IFS Insights], Apr 2018 | ||
| − | Meng, D. | + | Meng, D. and Chen, H. [http://arxiv.org/pdf/1705.09064.pdf MagNet: a Two-Pronged Defense against Adversarial Examples], 11 Sep 2017 |
| − | Miller, D., Hu, X., Qiu, Z., Kesidis, G. [http://arxiv.org/pdf/1705.09823.pdf Adversarial Learning. A Critical Review and Active Learning Study], 27 May 2017 | + | Miller, D., Hu, X., Qiu, Z., and Kesidis, G. [http://arxiv.org/pdf/1705.09823.pdf Adversarial Learning. A Critical Review and Active Learning Study], 27 May 2017 |
| − | Muñoz-González, L, Bissio, B., Demontis, A., Paudice, A., Wongreassamee, V., Lupu, E., Roli, F. [http://arxiv.org/pdf/1708.08689.pdf Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization], 29 Aug 2017 | + | Muñoz-González, L, Bissio, B., Demontis, A., Paudice, A., Wongreassamee, V., Lupu, E., and Roli, F. [http://arxiv.org/pdf/1708.08689.pdf Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization], 29 Aug 2017 |
Nataraj, L [https://vision.ece.ucsb.edu/sites/vision.ece.ucsb.edu/files/publications/lakshman_thesis_final_1.pdf A Signal Processing Approach To Malware Analysis], Dec 2015 | Nataraj, L [https://vision.ece.ucsb.edu/sites/vision.ece.ucsb.edu/files/publications/lakshman_thesis_final_1.pdf A Signal Processing Approach To Malware Analysis], Dec 2015 | ||
| − | + | Naveiro, R., Redondo, A., Insua, D., and Ruggeri, F. [http://arxiv.org/pdf/1802.07513.pdf Adversarial classification: An adversarial risk analysis approach], 21 Feb 2018 | |
| − | + | Nguyen A, Yosinski J, and Clune J. [http://arxiv.org/pdf/1412.1897.pdf Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images], 2 Apr 2015 [http://techtalks.tv/talks/deep-neural-networks-are-easily-fooled-high-confidence-predictions-for-unrecognizable-images/61573/ Video] | |
| − | + | North Atlantic Treaty Organization (NATO): Cooperative Cyber Defence Centre of Excellence; Minárik, T., Jakschis, R., and Lindström, L. [http://ccdcoe.org/sites/default/files/multimedia/pdf/CyCon_2018_Full_Book.pdf 10th International Conference on Cyber Conflict CyCon X: Maximising Effects], 30 May 2018 | |
| − | North Atlantic Treaty Organization: Joint Air Power Competence Centre [https://www.japcc.org/wp-content/uploads/JAPCC_OCO_screen.pdf NATO Joint Air Power and Offensive Cyber Operations], Nov 2017 | + | North Atlantic Treaty Organization (NATO): Joint Air Power Competence Centre [https://www.japcc.org/wp-content/uploads/JAPCC_OCO_screen.pdf NATO Joint Air Power and Offensive Cyber Operations], Nov 2017 |
| − | Norton, A | + | Norton, A. and Qi, Y. [http://arxiv.org/pdf/1708.00807.pdf Adversarial-Playground: A Visualization Suite Showing How Adversarial Examples Fool Deep Learning], 1 Aug 2017 |
| − | Ororbia II, A., Giles, C., Kifer, D. [http://arxiv.org/pdf/1601.07213.pdf Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization], 29 Jul 2016 | + | Ororbia II, A., Giles, C., and Kifer, D. [http://arxiv.org/pdf/1601.07213.pdf Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization], 29 Jul 2016 |
| − | Papernot N., Goodfellow, I., Erlingsson, U., McDaniel, P. [http://www.usenix.org/sites/default/files/conference/protected-files/enigma17_slides_papernot.pdf Adversarial Examples in Machine Learning], 1 Feb 2017 | + | Papernot N., Goodfellow, I., Erlingsson, U., and McDaniel, P. [http://www.usenix.org/sites/default/files/conference/protected-files/enigma17_slides_papernot.pdf Adversarial Examples in Machine Learning], 1 Feb 2017 |
| − | Papernot N., Goodfellow, I., Sheatsley, R., Feinman, R., McDaniel, P. [http://pdfs.semanticscholar.org/308b/72045130d02b849b4a8f914eae6d0d684add.pdf Cleverhans v.1.0.0: an adversarial machine learning library], 14 Dec 2016 | + | Papernot N., Goodfellow, I., Sheatsley, R., Feinman, R., and McDaniel, P. [http://pdfs.semanticscholar.org/308b/72045130d02b849b4a8f914eae6d0d684add.pdf Cleverhans v.1.0.0: an adversarial machine learning library], 14 Dec 2016 |
| − | Papernot, N., McDaniel, P., Wu, X., Jha, S., Swami, A. [http://arxiv.org/pdf/1511.04508.pdf Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks], 14 Nov 2015 | + | Papernot, N., McDaniel, P., Wu, X., Jha, S., and Swami, A. [http://arxiv.org/pdf/1511.04508.pdf Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks], 14 Nov 2015 |
| − | Papernot, N., McDaniel, P, Jha, S., Fredrikson, M., Celik, Z.B., Swami, A. [http://arxiv.org/abs/1511.07528 The Limitations of Deep Learning in Adversarial Settings], 24 Nov 2015 | + | Papernot, N., McDaniel, P, Jha, S., Fredrikson, M., Celik, Z.B., and Swami, A. [http://arxiv.org/abs/1511.07528 The Limitations of Deep Learning in Adversarial Settings], 24 Nov 2015 |
| − | Papernot, N., McDaniel, P., Goodfellow, I., Jha, S., Celik, Z.B. and Swami, A [http://arxiv.org/pdf/1602.02697v2.pdf Practical Black-Box Attacks against Deep Learning Systems using Adversarial Examples], 19 Feb 2016 | + | Papernot, N., McDaniel, P., Goodfellow, I., Jha, S., Celik, Z.B. and Swami, A. [http://arxiv.org/pdf/1602.02697v2.pdf Practical Black-Box Attacks against Deep Learning Systems using Adversarial Examples], 19 Feb 2016 |
| − | Papernot | + | Papernot, N., McDaniel, P., Goodfellow, I., Jha, S., Celik, Z.B. and Swami, A. [http://arxiv.org/pdf/1602.02697.pdf Practical Black-Box Attacks against Machine Learning], 8 Feb 2016 |
| − | Papernot, N., McDaniel, P., Sinha, A., and Wellman | + | Papernot, N., McDaniel, P., Sinha, A., and Wellman M. [http://pdfs.semanticscholar.org/ebab/687cd1be7d25392c11f89fce6a63bef7219d.pdf Towards the Science of Security and Privacy in Machine Learning], 11 Nov 2016 |
| − | Papernot, N., McDaniel, P., Goodfellow I. [http://arxiv.org/pdf/1605.07277.pdf Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples], 24 May 2016 | + | Papernot, N., McDaniel, P., and Goodfellow I. [http://arxiv.org/pdf/1605.07277.pdf Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples], 24 May 2016 |
| − | Paudice | + | Paudice A., Muñoz-González, L., Gyorgy, A., and Lupu, E. [http://arxiv.org/pdf/1802.03041.pdf Detection of Adversarial Training Examples in Poisoning Attacks through Anomaly Detection], 8 Feb 2018 |
Radford, A., Metz, L. and Chintala, S. [http://arxiv.org/pdf/1511.06434.pdf Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks], 7 Jan 2016 | Radford, A., Metz, L. and Chintala, S. [http://arxiv.org/pdf/1511.06434.pdf Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks], 7 Jan 2016 | ||
| − | Raghunathan, A., Steinhardt, J., Liang, P. [http://arxiv.org/pdf/1801.09344.pdf Certified Defenses against Adversarial Examples], 29 Jan 2018 | + | Raghunathan, A., Steinhardt, J., and Liang, P. [http://arxiv.org/pdf/1801.09344.pdf Certified Defenses against Adversarial Examples], 29 Jan 2018 |
| − | Rahman, M., Azimpourkivi, M., Topkara, U., Carbunar, B. [http://users.cs.fiu.edu/~carbunar/vamos.pdf Video Liveness for Citizen Journalism: Attacks and Defenses], Apr 2017 | + | Rahman, M., Azimpourkivi, M., Topkara, U., and Carbunar, B. [http://users.cs.fiu.edu/~carbunar/vamos.pdf Video Liveness for Citizen Journalism: Attacks and Defenses], Apr 2017 |
Rouhani, B., Riazi, M., and Koushanfar, F. [http://arxiv.org/pdf/1709.02538.pdf CuRTAIL: ChaRacterizing and Thwarting AdversarIal deep Learning], 1 Apr 2018 | Rouhani, B., Riazi, M., and Koushanfar, F. [http://arxiv.org/pdf/1709.02538.pdf CuRTAIL: ChaRacterizing and Thwarting AdversarIal deep Learning], 1 Apr 2018 | ||
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Schneier, B. [http://www.schneier.com/blog/archives/2017/02/security_and_th.html Security and the Internet of Things], 2017 | Schneier, B. [http://www.schneier.com/blog/archives/2017/02/security_and_th.html Security and the Internet of Things], 2017 | ||
| − | Shen, S., Tople, S., Saxena, P. [http://www.comp.nus.edu.sg/~shruti90/papers/auror.pdf AUROR: Defending Against Poisoning Attacks in Collaborative Deep Learning Systems], 5 Dec 2016 | + | Shen, S., Tople, S., and Saxena, P. [http://www.comp.nus.edu.sg/~shruti90/papers/auror.pdf AUROR: Defending Against Poisoning Attacks in Collaborative Deep Learning Systems], 5 Dec 2016 |
Shokri, R., Stronati, M., and Shmatikov, V. [http://arxiv.org/pdf/1610.05820.pdf Membership Inference Attacks Against Machine Learning Models], 31 Mar 2017 | Shokri, R., Stronati, M., and Shmatikov, V. [http://arxiv.org/pdf/1610.05820.pdf Membership Inference Attacks Against Machine Learning Models], 31 Mar 2017 | ||
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Šrndic, N. and Laskov, P. [http://www.utdallas.edu/~muratk/courses/dmsec_files/srndic-laskov-sp2014.pdf Practical Evasion of a Learning-Based Classifier: A Case Study], 2014 | Šrndic, N. and Laskov, P. [http://www.utdallas.edu/~muratk/courses/dmsec_files/srndic-laskov-sp2014.pdf Practical Evasion of a Learning-Based Classifier: A Case Study], 2014 | ||
| − | Stevens, R., Suciu, O., Ruef, A., Hong, S., Hicks, M., Dumitras, T. [http://arxiv.org/pdf/1701.04739.pdf Summoning Demons: The Pursuit of Exploitable Bugs in Machine Learning], 17 Jan 2017 | + | Stevens, R., Suciu, O., Ruef, A., Hong, S., Hicks, M., and Dumitras, T. [http://arxiv.org/pdf/1701.04739.pdf Summoning Demons: The Pursuit of Exploitable Bugs in Machine Learning], 17 Jan 2017 |
| − | Stokes, J., Wang, D., Marinescu, M., Mariono, M., Bussone, B. [http://arxiv.org/pdf/1712.05919.pdf Attack and Defense of Dynamic Analysis-Based, Adversarial Neural Malware Classification Models] 16 Dec 2017 | + | Stokes, J., Wang, D., Marinescu, M., Mariono, M., and Bussone, B. [http://arxiv.org/pdf/1712.05919.pdf Attack and Defense of Dynamic Analysis-Based, Adversarial Neural Malware Classification Models] 16 Dec 2017 |
Stoica, I., Song, D., Popa, R., Patterson, D., Mahoney, M., Katz, R., Joseph, A., Jordan, M., Hellerstein, J., Gonzalez, J., Goldberg, K., Ghodsi, A., Culler, D., and Abbeel, P. [http://arxiv.org/pdf/1712.05855.pdf A Berkeley View of Systems Challenges for AI], 15 Dec 2017 | Stoica, I., Song, D., Popa, R., Patterson, D., Mahoney, M., Katz, R., Joseph, A., Jordan, M., Hellerstein, J., Gonzalez, J., Goldberg, K., Ghodsi, A., Culler, D., and Abbeel, P. [http://arxiv.org/pdf/1712.05855.pdf A Berkeley View of Systems Challenges for AI], 15 Dec 2017 | ||
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Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I. and Fergus, R. [http://arxiv.org/pdf/1312.6199.pdf Intriguing properties of neural networks], 19 Feb 2014 | Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I. and Fergus, R. [http://arxiv.org/pdf/1312.6199.pdf Intriguing properties of neural networks], 19 Feb 2014 | ||
| − | Tramèr, F., Papernot, N., Goodfellow, I., Boneh, D., McDaniel, P. [http://arxiv.org/pdf/1704.03453.pdf The Space of Transferable Adversarial Examples], 23 May 2017 | + | Tramèr, F., Papernot, N., Goodfellow, I., Boneh, D., and McDaniel, P. [http://arxiv.org/pdf/1704.03453.pdf The Space of Transferable Adversarial Examples], 23 May 2017 |
| − | Uesato, J., O'Donoghue, B., Oord, A., Kohli, P. [http://arxiv.org/pdf/1802.05666.pdf Adversarial Risk and the Dangers of Evaluating Against Weak Attacks], 12 Jun 2018 | + | Uesato, J., O'Donoghue, B., Oord, A., and Kohli, P. [http://arxiv.org/pdf/1802.05666.pdf Adversarial Risk and the Dangers of Evaluating Against Weak Attacks], 12 Jun 2018 |
U.S. Department of Defense [http://www.defense.gov/Portals/1/Documents/law_war_manual15.pdf Law of War Manual, Chapter XVI | Cyber Operations], 2015 | U.S. Department of Defense [http://www.defense.gov/Portals/1/Documents/law_war_manual15.pdf Law of War Manual, Chapter XVI | Cyber Operations], 2015 | ||
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Revision as of 16:52, 7 July 2018
- Cybersecurity
- Government Services for other related papers
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