CERIAS Weekly Security Seminar - Purdue University

Nowadays more and more data are gathered for detecting and preventing cyber attacks. Unique to the cyber security applications, learning models face active adversaries that try to deceive learning models and avoid being detected. Hence future datasets and the training data no longer follow the same distribution. The existence of such adversarial samples motivates the development of robust and resilient adversarial learning techniques. Game theory offers a suitable framework to model the conflict between adversaries and defender. We develop a game theoretic framework to model the sequential actions of the adversaries and the defender, allowing players to maximize their own utilities. For supervised learning tasks, our adversarial support vector machine has a conservative decision boundary, whereas our robust deep neural network plays a random strategy inspired by the mixed equilibrium strategy. One the other hand, in real practice, labeling the data instances often requires costly and time-consuming human expertise and becomes a significant bottleneck. We develop a novel grid based adversarial clustering algorithm, to understand adversaries' behavior from a large number of unlabeled instances. Our adversarial clustering algorithm is able to identify the normal regions inside mixed clusters, and to draw defensive walls around the center of the normal objects utilizing game theoretic ideas. Our algorithm also identifies sub-clusters of adversarial samples and the overlapping areas within mixed clusters, and identify outliers which may be potential anomalies.

ARM possessors are being widely used on mobile devices and smart IoT devices. Despite the best efforts, an operating system is too hard to be absolutely secured on both x86 and ARM platforms. We addresse the problem of executing an unmodified application in a compromised OS for ARM platforms. Existing protection mechanisms mainly focus on x86 platform, utilizing SGX of Intel Processors or a hypervisor which is running below an operating system. However, SGX is not available for ARM platform, and hypervisor is an overkill for embedded or IoT settings. We descript how to achieve the security goals on ARM Cortex-A processors using ARM specific designs. We also discuss the threats of side-channels and possible mitigations. About the speaker: Dr. Meng Yu is a Robert Miner Endowed Chair Professor of Roosevelt University. He is the Chairperson of the Department of Computer Science, Information Technology, and Data Science. He received his Ph.D. degree in Computer Science from Nanjing University, China. Before he joined Roosevelt University, he was a tenure associate professor of University of Texas at San Antonio and Virginia Commonwealth University. His research interests include systems and network security, cloud computing, virtualization and security. His primary research goal is to build more secure and trustworthy system software. He has been working on security problems such as privacy protection in cloud computing, self-healing problem, protection of applications against untrusted operating systems. His research has been supported by funding agencies such as National Science Foundation, Army Research Office, etc. He has served many conference program committees and also organized several international conferences and workshops.

ARM possessors are being widely used on mobile devices and smart IoT devices. Despite the best efforts, an operating system is too hard to be absolutely secured on both x86 and ARM platforms. We addresse the problem of executing an unmodified application in a compromised OS for ARM platforms. Existing protection mechanisms mainly focus on x86 platform, utilizing SGX of Intel Processors or a hypervisor which is running below an operating system. However, SGX is not available for ARM platform, and hypervisor is an overkill for embedded or IoT settings. We descript how to achieve the security goals on ARM Cortex-A processors using ARM specific designs. We also discuss the threats of side-channels and possible mitigations.

Information, not just data, is key to today's security challenges. To solve these security challenges requires not only advancing computer science and big data analytics but requires new analysis and decision-making environments that enable reliable, decisions from trustable, understandable information. These environments are successful when they effectively couple human decision making with advanced, guided analytics in human-computer collaborative discourse and decision making (HCCD). Our HCCD approach builds upon visual analytics, traceable information, and human-guided analytics and machine learning and focuses on empowering the decision maker through interactive visual analytic environments where non-digital human expertise and experience can be combined with state-of-the-art and transparent analytical techniques. When we combine this approach with real-world application-driven research, not only does the pace of scientific innovation accelerate, but impactful change occurs. I'll describe how we have applied these techniques to homeland and community security, resiliency,public safety and disaster management. About the speaker: David Ebert is the Silicon Valley Professor of Electrical and Computer Engineering at Purdue University, a Fellow of the IEEE, interim director of the Center for Education and Research in Information Assurance and Security, and director of the Visual Analytics for Command Control and Interoperability Center (VACCINE), the Visualization Science team of the Department of Homeland Security's Command Control and Interoperability Center of Excellence. Ebert performs research in visual analytics, volume rendering, illustrative visualization, and procedural abstraction of complex, massive data. He is the recipient of the 2017 IEEE Computer Society vgTC Technical Achievement Award for seminal contributions in visual analytics. He has been very active in the visualization community, serving as Editor in Chief of IEEE Transactions on Visualization and Computer Graphics, serving as IEEE Computer Society Vice President and the IEEE Computer Society's VP of Publications, and successfully managing a large program of external funding to develop more effective methods for visually communicating information.

Information, not just data, is key to today’s security challenges. To solve these security challenges requires not only advancing computer science and big data analytics but requires new analysis and decision-making environments that enable reliable, decisions from trustable, understandable information. These environments are successful when they effectively couple human decision making with advanced, guided analytics in human-computer collaborative discourse and decision making (HCCD). Our HCCD approach builds upon visual analytics, traceable information, and human-guided analytics and machine learning and focuses on empowering the decision maker through interactive visual analytic environments where non-digital human expertise and experience can be combined with state-of-the-art and transparent analytical techniques. When we combine this approach with real-world application-driven research, not only does the pace of scientific innovation accelerate, but impactful change occurs. I’ll describe how we have applied these techniques to homeland and community security, resiliency,public safety and disaster management.

In application environments like international military coalitions or multi-party relief work in a disaster zone, passing secure messages using a Delay Tolerant Network (DTN) is challenging because the existing public-private key cryptographic approaches may not be always accessible across different groups due to the unavailability of Public Key Infrastructure (PKI). In addition, connectivity may be intermittent so finding reliable routes is also difficult. Thus, instead of sending a complete message in a single packet, fragmenting the message, and sending the fragments via multiple nodes can help achieve better security and reliability when multiple groups are involved. Therefore, encrypting messages before fragmentation and then sending both the data fragments and the key fragments (needed for decryption) provide much higher security. Keys are also fragmented as sending the key in a single packet can hamper security if it is forwarded to some corrupt nodes who may try to tamper or drop it. In this talk, I will discuss a scheme to provide improved security by generating multiple key-shares and data fragments, and disseminating them via some intermediate nodes. In this fragmentation process, we also create a few redundant blocks to guarantee higher data arrival rate at the destination when the message drop rate is high like in a DTN environment. The performance evaluation when compared to the closely related scheme like Multiparty Encryption shows the improvement on minimizing the number of compromised messages as well as reduced bandwidth consumption in the network. About the speaker: SanjayKMadriaisaCurators'DistinguishedProfessorintheDepartmentofComputer Science at the Missouri University of Science and Technology (formerly, University of Missouri- Rolla, USA). He received his Ph.D. in Computer Science from Indian Institute of Technology, Delhi, India in 1995. He has published over 250 Journal and conference papers in the areas of mobile and sensor computing, cloud and cyber security. He won five IEEE best papers awards in conferences such as IEEE MDM 2011, IEEE MDM 2012 and IEEE SRDS 2015. He is a co-author of a recent book on Secure Sensor Cloud published by Morgan and Claypool in Dec. 2018. He has served/serving in International conferences as a general co-chair, pc co-chair, and steering committee members, and presented tutorials/talks in the areas of secure sensor cloud, cloud computing, etc. NSF, NIST, ARL, ARO, AFRL, DOE, Boeing, ORNL, Honeywell, etc. have funded his research projects. He has been awarded JSPS (Japanese Society for Promotion of Science) invitational visiting scientist fellowship in 2006 and ASEE (American Society of Engineering Education) fellowship from 2008 to 2018. In 2012 and in 2018, he was awarded NRC Fellowship by National Academies. He has received research faculty excellence awards six times from his university. He is ACM Distinguished Scientist, and served/serving as an ACM and IEEE Distinguished Speaker, and is an IEEE Senior Member as well as IEEE Golden Core Awardee.

In application environments like international military coalitions or multi-party relief work in a disaster zone, passing secure messages using a Delay Tolerant Network (DTN) is challenging because the existing public-private key cryptographic approaches may not be always accessible across different groups due to the unavailability of Public Key Infrastructure (PKI). In addition, connectivity may be intermittent so finding reliable routes is also difficult. Thus, instead of sending a complete message in a single packet, fragmenting the message, and sending the fragments via multiple nodes can help achieve better security and reliability when multiple groups are involved. Therefore, encrypting messages before fragmentation and then sending both the data fragments and the key fragments (needed for decryption) provide much higher security. Keys are also fragmented as sending the key in a single packet can hamper security if it is forwarded to some corrupt nodes who may try to tamper or drop it. In this talk, I will discuss a scheme to provide improved security by generating multiple key-shares and data fragments, and disseminating them via some intermediate nodes. In this fragmentation process, we also create a few redundant blocks to guarantee higher data arrival rate at the destination when the message drop rate is high like in a DTN environment. The performance evaluation when compared to the closely related scheme like Multiparty Encryption shows the improvement on minimizing the number of compromised messages as well as reduced bandwidth consumption in the network.

One of the reasons we care about information security is protectingprivacy, and satisfying requirements of privacy law. But whatexactly is meant by privacy? Is security sufficient to provideprivacy? This talk looks at some background on data privacy,and techniques for privacy protection including anonymity anddifferential privacy.

One of the reasons we care about information security is protecting privacy, and satisfying requirements of privacy law. But what exactly is meant by privacy? Is security sufficient to provide privacy? This talk looks at some background on data privacy, and techniques for privacy protection including anonymity and differential privacy.

Caller ID spoofing forges the authentic caller identity, thus making the call appear to originate from another user. In this paper, we propose CEIVE (Callee-only inference and verification), an effective and practical defense against caller ID spoofing. It is a victim callee only solution without requiring additional infrastructure support or changes on telephony systems. We implement CEIVE on Android phones and test it with all top four US mobile carriers, one landline and two small carriers. It shows 100% accuracy in almost all tested spoofing scenarios except one special, targeted attack case. About the speaker: Haotian Deng is a forth-year PhD student from the department of computer science. His advisor is Prof. Chunyi Peng. His research interests are mainly on mobile networks.

Caller ID spoofing forges the authentic caller identity, thus making the call appear to originate from another user. In this paper, we propose CEIVE (Callee-only inference and verification), an effective and practical defense against caller ID spoofing. It is a victim callee only solution without requiring additional infrastructure support or changes on telephony systems. We implement CEIVE on Android phones and test it with all top four US mobile carriers, one landline and two small carriers. It shows 100% accuracy in almost all tested spoofing scenarios except one special, targeted attack case.

Access control systems are known to be vulnerable to anomalies in security policies, such as inconsistency. Android Security model is no exception. This talk presents a new approach aiming to unveil Android inconsistent access controls enforced across multiple instances of the same resource. ​To address the complex nature of Android security checks (e.g., semantic similarity of syntactically different enforcements), the presented approach detects inconsistencies through modeling and normalizing diverse checks. The talk further presents application results of the approach, including the discovery of actual exploits. About the speaker: Dr. Aafer is a postdoctoral researcher at Purdue University. Her research tackles emerging threats of mobile and smart systems. She earned her Ph.D. degree in computer engineering from Syracuse University while focusing on Android security. Her discoveries directly benefited mobile vendors and led to publications in top security venues. She was elected as a member of the ACM's Future of Computing Academy.

Access control systems are known to be vulnerable to anomalies in security policies, such as inconsistency. Android Security model is no exception. This talk presents a new approach aiming to unveil Android inconsistent access controls enforced across multiple instances of the same resource. ​To address the complex nature of Android security checks (e.g., semantic similarity of syntactically different enforcements), the presented approach detects inconsistencies through modeling and normalizing diverse checks. The talk further presents application results of the approach, including the discovery of actual exploits.

How do you assess the cybersecurity status of public and private organization in a State? The NIST has a comprehensive framework for assessing cybersecurity but for small companies with limited expertise or funding, this process is not possible to reasonably complete. Indiana Governor’s Executive Council on Cybersecurity and Purdue University collaborated in conducting a Cybersecurity Scorecard Pilot to aid the improvements in cybersecurity across their state. The Cybersecurity Scorecard included several targeted objectives: Enable non-cybersecurity experts to confidently learn, self-assess, and initiate cybersecurity improvement. Enable public and private executives to identify systemic cybersecurity issues Provide a means of comparing preparedness across public and private critical infrastructure and key resource sectors within the state. Utilize standards and measurements that support “apples to apples” comparison. Presentation will describe Indiana’s Cybersecurity Scorecard’s development process, pilot launch, and initial findings.

How do you assess the cybersecurity status of public and private organization in a State? The NIST has a comprehensive framework for assessing cybersecurity but for small companies with limited expertise or funding, this process is not possible to reasonably complete. Indiana Governor's Executive Council on Cybersecurity and Purdue University collaborated in conducting a Cybersecurity Scorecard Pilot to aid the improvements in cybersecurity across their state. The Cybersecurity Scorecard included several targeted objectives:Enable non-cybersecurity experts to confidently learn, self-assess, and initiate cybersecurity improvement.Enable public and private executives to identify systemic cybersecurity issuesProvide a means of comparing preparedness across public and private critical infrastructure and key resource sectors within the state.Utilize standards and measurements that support "apples to apples" comparison.Presentation will describe Indiana's Cybersecurity Scorecard's development process, pilot launch, and initial findings. About the speaker: James is currently an Interdisciplinary Information Security Ph.D. Candidate in the Purdue Homeland Security Institute and Department of Computer Information Technology at Purdue University, West Lafayette, Indiana. He has over thirty years of experience of as an engineer, senior manager, and military officer in voice and data communications, industrial automation, business, operations, and strategy.