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Intelligence business: Trump must keep privacy protections for US firms

February 13, 2017


Zachary K. Goldman poses questions for the Director of National Intelligence on information privacy, cybersecurity, and American businesses in The Hill.

Automotive Electrical/Electronic Architecture Security via Distributed In-Vehicle Traffic Monitoring

February 9, 2017

Peter Waszecki, Philipp Mundhenk, Sebastian Steinhorst, Martin Lukasiewycz, Ramesh Karri, and Samarjit Chakraborty

Due to the growing interconnectedness and complexity of in-vehicle networks, in addition to safety, security is becoming an increasingly important topic in the automotive domain. In this paper we study techniques for detecting security infringements in automotive Electrical and Electronic (E/E) architectures. Towards this we propose in-vehicle network traffic monitoring to detect increased transmission rates of manipulated message streams.

Mining Anonymity: Identifying Sensitive Accounts on Twitter

February 1, 2017

Sai Teja Peddinti, Keith W. Ross, and Justin Cappos

We explore the feasibility of automatically finding accounts that publish sensitive content on Twitter. One natural approach to this problem is to first create a list of sensitive keywords, and then identify Twitter accounts that use these words in their tweets. But such an approach may overlook sensitive accounts that are not covered by the subjective choice of keywords. In this paper, we instead explore finding sensitive accounts by examining the percentage of anonymous and identifiable followers the accounts have. This approach is motivated by an earlier study showing that sensitive accounts typically have a large percentage of anonymous followers and a small percentage of identifiable followers.

Third-Party Cyber Risk & Corporate Responsibility

February 1, 2017

Judith H. Germano

Third parties are a significant source of cybersecurity vulnerabilities, yet there remains much work to be done in terms of how third-party risk is assessed and  controlled. This paper explains how properly understanding and addressing third-party cyber risk requires a proactive and comprehensive approach to enable parties on all sides to prevent harms and to prepare for and respond to incidents in a faster, better coordinated, less expensive and more effective manner.

Microfluidic encryption of on-chip biochemical assays

January 26, 2017

Sk Subidh Ali- , Mohamed Ibrahim, Ozgur Sinanoglu, Krishnendu Chakrabarty, and Ramesh Karri

Recent security analysis of digital micro-fluidic biochips (DMFBs) has revealed that the DMFB design flow is vulnerable to IP piracy, Trojan attacks, overproduction, and counterfeiting. An attacker can launch assay manipulation attacks against DMFBs that are used for clinical diagnostics in healthcare.

Physical Unclonable Functions and Intellectual Property Protection Techniques

January 25, 2017

Ramesh Karri, Ozgur Sinanoglu and Jeyavijayan Rajendran

On one hand, traditionally, secure systems rely on hardware to store the keys for cryptographic protocols. Such an approach is becoming increasingly insecure, due to hardware-intrinsic vulnerabilities. A physical unclonable function (PUF) is a security primitive that exploits inherent hardware properties to generate keys on the fly, instead of storing them. On the other hand, the integrated circuit (IC) design flow is globalized due to increase in design, fabrication, testing, and verification costs.

Source camera attribution using stabilized video

January 19, 2017

Samet Taspinar, Manoranjan Mohanty, and Nasir Memon

Although PRNU (Photo Response Non-Uniformity)-based methods have been proposed to verify the source camera of a non-stabilized video, these methods may not be adequate for stabilized videos. The use of video stabilization has been increasing in recent years with the development of novel stabilization software and the availability of stabilization in smart-phone cameras. This paper presents a PRNU-based source camera attribution method for out-of-camera stabilized video (i.e., stabilization applied after the video is captured).

Scan Design: Basics, Advancements, and Vulnerabilities

January 14, 2017

Samah Mohamed Saeed, Sk Subidh Ali, and Ozgur Sinanoglu

The increasing design complexity of modern Integrated Chips (IC) has reflected into exacerbated challenges in manufacturing testing. In this respect, scan is the most widely used design for testability (DfT) technique that overcomes the manufacturing test challenges by enhancing the access and thus, testability. However, scan can also open a back door to an attacker when implemented in security critical chips.

Repeatable Reverse Engineering with the Platform for Architecture-Neutral Dynamic Analysis

January 6, 2017

Ryan J. Whelan, Timothy R. Leek, Joshua E. Hodosh, Patrick A. Hulin, and Brendan Dolan-Gavitt

Many problems brought on by faulty or malicious software code can be diagnosed through a reverse engineering technique known as dynamic analysis, in which analysts study software as it executes. Researchers at Lincoln Laboratory developed the Platform for Architecture-Neutral Dynamic Analysis to facilitate analyses that lead to profound insight into how software behaves.

Diplomat: Using delegations to protect community repositories

December 21, 2016

Trishank Karthik Kuppusamy, Santiago Torres-Arias, Vladimir Diaz, and Justin Cappos

Community repositories, such as Docker Hub, PyPI, and RubyGems, are bustling marketplaces that distribute software. Even though these repositories use common software signing techniques (e.g., GPG and TLS), attackers can still publish malicious packages after a server compromise.

Stressing Out: Bitcoin “Stress Testing”

December 19, 2016

Khaled Baqer, Danny Yuxing Huang, Damon McCoy, and Nicholas Weaver

In this paper, we present an empirical study of a recent spam campaign (a “stress test”) that resulted in a DoS attack on Bitcoin. The goal of our investigation being to understand the methods spammers used and impact on Bitcoin users.

Secure and resilient distributed machine learning under adversarial environments

December 19, 2016

Rui Zhang and  Quanyan Zhu

Machine learning algorithms, such as support vector machines (SVMs), neutral networks, and decision trees (DTs) have been widely used in data processing for estimation and detection. They can be used to classify samples based on a model built from training data. However, under the assumption that training and testing samples come from the same natural distribution, an attacker who can generate or modify training data will lead to misclassification or misestimation.

FACID: A trust-based collaborative decision framework for intrusion detection networks

December 15, 2016

Carol J. Fung and Quanyan Zhu

Computer systems evolve to be more complex and vulnerable. Cyber attacks have also grown to be more sophisticated and harder to detect. Intrusion detection is the process of monitoring and identifying unauthorized system access or manipulation. It becomes increasingly difficult for a single intrusion detection system (IDS) to detect all attacks due to limited knowledge about attacks. Collaboration among intrusion detection devices can be used to gain higher detection accuracy and cost efficiency as compared to its traditional single host-based counterpart.

Proposed NY Cybersecurity Regulation: A Giant Leap Backward?

December 2, 2016


Judith Germano

Mid-November marked the end of the comment period for New York’s “first in nation” proposed cybersecurity legislation for financial institutions. As the hot topic of the day, many regulators and government officials have felt compelled to take a stand on cybersecurity. It seems counterintuitive to set out to protect constituents by inaction. But the wrong type of action, including through inflexible and far-reaching state required mandates, only adds to the growing clamor of distractions about how companies should best secure their systems.

Guest Editorial: Special Issue on Secure and Trustworthy Computing

December 1, 2016

Ozgur Sinanoglu and Ramesh Karri

There is a growing concern regarding the trustworthiness and reliability of the hardware underlying all information systems on which modern society is reliant. Trustworthy and reliable semiconductor supply chain, hardware components, and platforms are essential to all critical infrastructures including financial, healthcare, transportation, and energy.

FPGA Trust Zone: Incorporating trust and reliability into FPGA designs

November 24, 2016

Vinayaka Jyothi, Manasa Thoonoli, Richard Stern and Ramesh Karri

This paper proposes a novel methodology FPGA Trust Zone (FTZ) to incorporate security into the design cycle to detect and isolate anomalies such as Hardware Trojans in the FPGA fabric. Anomalies are identified using violation to spatial correlation of process variation in FPGA fabric.

Hardware Trojans: Lessons Learned after One Decade of Research

November 23, 2016

Kan Xiao, Domenic Forte, Yier Jin, Ramesh Karri, Swarup Bhunia, and Mark Mohammad Tehranipoor 

Given the increasing complexity of modern electronics and the cost of fabrication, entities from around the globe have become more heavily involved in all phases of the electronics supply chain. In this environment, hardware Trojans (i.e., malicious modifications or inclusions made by untrusted third parties) pose major security concerns, especially for those integrated circuits (ICs) and systems used in critical applications and cyber infrastructure.

Securing digital microfluidic biochips by randomizing checkpoints

November 17, 2016

Jack Tang, Ramesh Karri, Mohamed Ibrahim, and Krishnendu Chakrabarty

Much progress has been made in digital microfluidic biochips (DMFB), with a great body of literature addressing low-cost, high-performance, and reliable operation. Despite this progress, security of DMFBs has not been adequately addressed. We present an analysis of a DMFB system prone to malicious modification of routes and propose a DMFB defense based on spatio-temporal randomized checkpoints using CCD cameras.