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Detecting Hardware Trojans Inserted by Untrusted Foundry Using Physical Inspection and Advanced Image Processing

Journal of Hardware and Systems security 2018年第4期2卷 333-344页

作者： Nidish Vashistha M. Tanjidur Rahman Haoting Shen Damon L. Woodard Navid Asadizanjani Mark Tehranipoor Florida Institute for Cyber Security (FICS) Research Electrical and Computer Engineering Department University of Florida Gainesville USA

Hardware Trojans are malicious changes to the design of integrated circuits (ICs) at different stages of the design and fabrication process. Different approaches have been developed to detect Trojans namely non-destructive and destructive testing. However, none of the previously developed methods can be used to detect all types of Trojans as they suffer from a number of disadvantages such as low speed of detection, low accuracy, low confidence level, and poor coverage of Trojan types. Majority of the hardware Trojans implemented in an IC will leave a footprint at the active layer. In this paper, we propose a new technique based on rapid backside SEM imaging and advanced computer vision algorithms to detect any subtle changes at the active region of transistors that can show the existence of a hardware Trojan. Here, we are only concerned with untrusted foundry problem, where it is assumed the attacker has access to a golden layout/image of the IC. This is a common threat model for those organizations that fully design their IC but need access to untrusted foundry for fabrication. SEM image from a backside thinned golden IC is compared with a low-quality SEM image of an IC under authentication (IUA). We perform image processing to both golden IC and IUA images to remove noise. We have developed a computer vision-based framework to detect hardware Trojans based on their structural similarity. The results demonstrate that our technique is quite effective at detecting Trojans and significantly faster than full chip reverse engineering. One of the major advantages of our technique is that it does not rely on the functionality of the circuit, rather the real physical structure to detect malicious changes performed by the untrusted foundry.

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Improved impossible differential cryptanalysis of large-block Rijndael

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Science China(Information Sciences) 2019年第3期62卷 5-18页

作者： Ya LIU Yifan SHI Dawu GU Bo DAI Fengyu ZHAO Wei LI Zhiqiang LIU Zhiqiang ZENG Engineering Research Center of Optical Instrument and System Ministry of Education Shanghai Key Lab of Modern Optical System University of Shanghai for Science and Technology State Key Laboratory of Cryptology Department of Computer Science and Engineering Shanghai Jiao Tong University School of Computer Science and Technology Donghua University Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Science and Technology on Information Assurance Laboratory

Rijndael is a substitution-permutation network（SPN） block cipher for the AES development process. Its block and key sizes range from 128 to 256 bits in steps of 32 bits, which can be denoted by Rijndael-b-k, where b and k are the block and key sizes, respectively. Among them, Rijndael-128-128/192/256,that is, AES, has been studied by many researchers, and the security of other large-block versions of Rijndael has been exploited less frequently. However, more attention has been paid to large-block versions of block ciphers with the fast development of quantum computers. In this paper, we propose improved impossible differential attacks on 10-round Rijndael-256-256, 10-round Rijndael-224-256, and 9-round Rijndael-224-224 using precomputation tables, redundancies of key schedules, and multiple impossible differentials. For 10-round Rijndael-256-256, the data, time, and memory complexities of our attack were approximately 2244.4chosen plaintexts, 2240.1encryptions, and 2181.4blocks, respectively. For 10-round Rijndael-224-256, the data, time, and memory complexities of our attack were approximately 2214.4chosen plaintexts, 2241.3encryptions, and 2183.4blocks, respectively. For 9-round Rijndael-224-224, the data, time, and memory complexities of our attack are approximately 2214.4chosen plaintexts, 2113.4encryptions, and 287.4blocks,respectively, or 2206.6chosen plaintexts, 2153.6encryptions, and 2111.6blocks, respectively. To the best of our knowledge, our results are currently the best on Rijndael-256-256 and Rijndael-224-224/256.

关键词： block cipher Rijndael precomputation tables impossible di?erentials multiple impossible differential attacks

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Smart Phone as Toolbox for Height Measurement

Smart Phone as Toolbox for Height Measurement

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IEEE National Conference on Aerospace and Electronics (NAECON)

作者： Abdul Razaque Fathi Amsaad Cai Mengjie Cherry Lin Jiahui Linda Ahmed Oun Computer Engineering and Telecommunication International IT University Almaty Kazakhstan School of Information Security Eastern Michigan University USA Computer Science Department New York Institute of Technology (NYIT) Nanjing Campus China Electrical Engineering and Computer Science Department University of Toledo USA

ISBN: (数字)9781728114163

ISBN: (纸本)9781728114170

Many researchers focus on using smart phone as toolbox, such as measuring height via barometer on smart phone. However, none of them compared the error rate that exists in different brands of mobile phones (e.g., Samsung, HUAWEI and iPhone). This paper carries out sets of control experiments to acquire plenty of data to analyze and contrast the error rate in those mobile systems. This paper uses elementary effects (EE) method to recognize variables that are non-influential. EE method is also used to sort affecting factors such as temperature and humidity, according to factors' significance. Furthermore, this paper minimizes the burst affecting variable random error by using a method called Filtering Burst Error and Random Error Process (FBEREP) to ensure the error rate. The validation is conducted using real smart phones. Based on the result, it can be observed that error rate is controlled within 2%.

关键词： Error analysis Smart phones Temperature Lead

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Multilevel Data Encryption Using AES and RSA For Image and Textual information Data

Multilevel Data Encryption Using AES and RSA For Image and T...

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Innovations in Power and Advanced Computing Technologies (i-PACT)

作者： Urvi Patel Pradish Dadhania Computer Eng. (System and Network Security) Department Sardar Vallabhbhai Patel Institute of Technology Vasad Gujarat India Information Technology Engineering Department Sardar Vallabhbhai Patel Institute of Technology Vasad Gujarat India

In our day by day life day's style we moving starting with one spot then onto the next spot with writings, records over the web are the undertakings in like manner identified with puzzle PC key arrangement of PC guidelines assumes an a major job in a cryptosystem, which secures those touchy and private information. With the extended cryptanalysis, verifying intuitive media data sight and sound information against variations of assaults against different sorts of ambushes might be a testing work. This paper presents a nascent picture mapping method for doing thing for encoding the message into relative concentration by scramble plain content believer into HEXADECIMAL. The changed over Hex qualities are assembled together to type of framework. Pseudo Random Number Engenderer (PRNG) circuits are basic central of cryptographic structure. These days, the aim of information security has wound up more prevalent than the back, due to the particularly that especially in open system frameworks, there's a potential risk of making fragile information, for example, military requests, wellbeing records and individual data to interceptor. The enhancement of overwhelming cryptographic plans to arrangement of information security. In the correspondence medium, secured information utilizes identified with ways and working or delivering something of we tried our method for getting things done with various info content sizes. The substance Cover to use to stow away the fragile information was vigorously effectively and did not reveal the closeness of any puzzle code data. It tends to be combination these two cryptographic systems gives a viable answer for information concealing and data transmission through unbound channels. The outcome demonstrates that the proposed sizably voluminous arrangement/format/duplicitous arrangement is inducing a ton with next to no waste and equipped for accomplishing something great/great when contrasted with famous subsisting methods for getting things d

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Efficient SVM Based Packer Identification with Binary Diffing Measures

Efficient SVM Based Packer Identification with Binary Diffin...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Yeongcheol Kim Joon-Young Paik Seokwoo Choi Eun-Sun Cho Department of Computer Science and Engineering Chungnam National University Daejeon South Korea Department of Computer Science and Technology Tianjin Polytechnic University Tianjin China National Security Research Institute Daejeon South Korea

Packer identification is an essential process followed by further investigation on malware. For efficient packer identification, we introduce an SVM based automatized method, which uses kernel lifting with binary diffing measures for RBF kernels. According to the experimental results, we found that LCS, n-gram and other binary diffing measure serve kernels with better performance in packer identification than previous works, which has used traditional kernels or no kernel-lifting at all. In addition, Edit distance-based RBF kernels in previous works (e.g., [6]) do not show satisfying results compared to other binary diffing measure-based kernels.

关键词： Support vector machines Kernel Malware Binary codes Feature extraction Tools Machine learning

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Exploring the back alleys: Analysing the robustness of alternative neural network architectures against adversarial attacks

arXiv

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arXiv 2019年

作者： Tan, Yi Xiang Marcus Elovici, Yuval Binder, Alexander ST Engineering Electronics-SUTD Cyber Security Laboratory Pillar Singapore University of Technology and Design Department of Software and Information Systems Engineering Ben-Gurion University of the Negev Deutsche Telekom Innovation Laboratories Ben-Gurion University of the Negev

Recent discoveries in the field of adversarial machine learning have shown that Artificial Neural Networks (ANNs) are susceptible to adversarial attacks. These attacks cause misclassification of specially crafted adversarial samples. In light of this phenomenon, it is worth investigating whether other types of neural networks are less susceptible to adversarial attacks. In this work, we applied standard attack methods originally aimed at conventional ANNs, towards stochastic ANNs and also towards Spiking Neural Networks (SNNs), across three different datasets namely MNIST, CIFAR-10 and Patch Camelyon. We analysed their adversarial robustness against attacks performed in the raw image space of the different model variants. We employ a variety of attacks namely Basic Iterative Method (BIM), Carlini & Wagner L2 attack (CWL2) and Boundary attack. Our results suggests that SNNs and stochastic ANNs exhibit some degree of adversarial robustness as compared to their ANN counterparts under certain attack methods. Namely, we found that the Boundary and the state-of-the-art CWL2 attacks are largely ineffective against stochastic ANNs. Following this observation, we proposed a modified version of the CWL2 attack and analysed the impact of this attack on the models’ adversarial robustness. Our results suggest that with this modified CWL2 attack, many models are more easily fooled as compared to the vanilla CWL2 attack, albeit observing an increase in L2 norms of adversarial perturbations. Lastly, we also investigate the resilience of alternative neural networks against adversarial samples transferred from ResNet18. We show that the modified CWL2 attack provides an improved cross-architecture transferability compared to other attacks. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

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Deep Active Learning for Anchor User Prediction

arXiv

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arXiv 2019年

作者： Cheng, Anfeng Zhou, Chuan Yang, Hong Wu, Jia Li, Lei Tan, Jianlong Guo, Li Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Centre for Artificial Intelligence School of Software FEIT University of Technology Sydney Australia Department of Computing Macquarie University Sydney Australia School of Computer Science and Information Engineering Hefei University of Technology China

Predicting pairs of anchor users plays an important role in the cross-network analysis. Due to the expensive costs of labeling anchor users for training prediction models, we consider in this paper the problem of minimizing the number of user pairs across multiple networks for labeling as to improve the accuracy of the prediction. To this end, we present a deep active learning model for anchor user prediction (DALAUP for short). However, active learning for anchor user sampling meets the challenges of non-i.i.d. user pair data caused by network structures and the correlation among anchor or non-anchor user pairs. To solve the challenges, DALAUP uses a couple of neural networks with shared-parameter to obtain the vector representations of user pairs, and ensembles three query strategies to select the most informative user pairs for labeling and model training. Experiments on real-world social network data demonstrate that DALAUP outperforms the state-of-the-art approaches. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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A novel aircraft and missile accurate positioning and tracking system for military and intelligence using global satellite networks

A novel aircraft and missile accurate positioning and tracki...

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AIAA Information Systems-AIAA Infotech at Aerospace, 2018

作者： Chyad, Hayder Jabbar Al-Saedi, Firas Abdullah Thweny Data and Applications Security Branch Ministry of Science and Technology Baghdad Iraq Computer Engineering Department Al-Nahrain University Baghdad Iraq

ISBN: (数字)9781624105272

ISBN: (纸本)9781624105272

Our novel real time system is based on gathering aircrafts and missiles information from various Radar stations all over the world to a single or multi operation centers. Also, the data gathered by each Radar station can be sent to all other Radar stations, and this will result in extending the range from where information of targets can be obtained even that they are not detected by that specific Radar station itself. These data are tracked by the military and intelligence parties to make the analysis and take the proper decisions on this information. Then all/some of these data are retransmitted to a large and far areas all over the world that does not have a nearby Radar systems, so that the special forces troops on these areas, and by using any commercial Direct Broadcast Satellite TV receiver, can have all the important targets information in their areas shown on their anti-aircraft/anti-missile system’s display, so that they can track or even destroy these targets without being vulnerable till they react on that target. These data are transmitted using commercial satellites using their audio channel of the TV broadcasted channel. The transmitted data will contain all the targets information like speed, range, altitude, geolocation and type after being encrypted. The system was tested in reality and its performance was excellent. © 2018 American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Real time systems

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Holistic digital forensic readiness framework for IoT-enabled organizations

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Forensic Science International: Reports 2020年 2卷 100117-100117页

作者： Kebande, Victor R. Mudau, Phathutshedzo P. Ikuesan, Richard A. Venter, H.S. Choo, Kim-Kwang Raymond Internet of Things and People (IoTaP) Research Center Department of Computer Science and Media Technology Malmö Universitet Malmö Sweden DigiForS Research Group Department of Computer Science University of Pretoria South Africa Cyber and Network Security Department Science and Technology Division Community College of Qatar Qatar Department of Information Systems and Cyber Security University of Texas at San Antonio San Antonio TX 78249-0631 USA

AbstractInternet of Things (IoT) are becoming commonplace in homes, buildings, cities, and nations, and IoT networks are also getting more complex and interconnected. The complexity, interconnectivity, and heterogeneity of IoT systems, however, complicate digital (forensic) investigations. The challenge is compounded due to the lack of holistic and standardized approaches. Hence, building on the ISO/IEC 27043 international standard, we present a holistic digital forensic readiness (DFR) framework. We also qualitatively evaluate the utility of the proposed DFR framework.

关键词： Holistic IoT Digital forensics Forensic readiness ISO/IEC 27043

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Real-time reversible data hiding with shifting block histogram of pixel differences in encrypted image

Real-time reversible data hiding with shifting block histogr...

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Journal of Real-Time Image Processing

作者： Tang, Zhenjun Xu, Shijie Ye, Dengpan Wang, Jinyan Zhang, Xianquan Yu, Chuanqiang Guangxi Key Lab of Multi-source Information Mining & Security Guangxi Normal University Guilin541004 China Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing Guangxi Normal University Guilin541004 China School of Cyber Science and Engineering Wuhan University Wuhan430072 China School of Computer Science and Information Technology Guangxi Normal University No. 15 YuCai Road Guilin541004 China

Reversible data hiding in encrypted image (RDH-EI) is a hot topic of data hiding in recent years. Most RDH-EI algorithms do not reach desirable embedding rate and their computational costs are not suitable for real-time applications. Aiming at these problems, we propose an efficient RDH-EI algorithm with shifting block histogram of pixel differences in homomorphic encrypted domain. A key step of our RDH-EI algorithm is the block-based encryption scheme with additive homomorphism, which can preserve spatial correlation of plaintext image in homomorphic encrypted domain. In addition, our proposed technique of shifting block histogram can achieve efficient data embedding with high payload and correctly recover image. Extensive experiments are conducted to validate performance of our RDH-EI algorithm. Comparison results illustrate that our RDH-EI algorithm outperforms some state-of-the-art algorithms in terms of embedding rate, visual quality and computational time. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Cryptography Graphic methods Image processing Pixels Steganography Computational costs Computational time Histogram shifting Homomorphic cryptosystem Real time application Reversible data hiding Spatial correlations State of the art algorithms

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