Visible to the public Biblio

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2023-02-17
Shi, Jiameng, Guan, Le, Li, Wenqiang, Zhang, Dayou, Chen, Ping, Zhang, Ning.  2022.  HARM: Hardware-Assisted Continuous Re-randomization for Microcontrollers. 2022 IEEE 7th European Symposium on Security and Privacy (EuroS&P). :520–536.
Microcontroller-based embedded systems have become ubiquitous with the emergence of IoT technology. Given its critical roles in many applications, its security is becoming increasingly important. Unfortunately, MCU devices are especially vulnerable. Code reuse attacks are particularly noteworthy since the memory address of firmware code is static. This work seeks to combat code reuse attacks, including ROP and more advanced JIT-ROP via continuous randomization. Previous proposals are geared towards full-fledged OSs with rich runtime environments, and therefore cannot be applied to MCUs. We propose the first solution for ARM-based MCUs. Our system, named HARM, comprises a secure runtime and a binary analysis tool with rewriting module. The secure runtime, protected inside the secure world, proactively triggers and performs non-bypassable randomization to the firmware running in a sandbox in the normal world. Our system does not rely on any firmware feature, and therefore is generally applicable to both bare-metal and RTOS-powered firmware. We have implemented a prototype on a development board. Our evaluation results indicate that HARM can effectively thaw code reuse attacks while keeping the performance and energy overhead low.
2022-04-26
Gadepally, Krishna Chaitanya, Mangalampalli, Sameer.  2021.  Effects of Noise on Machine Learning Algorithms Using Local Differential Privacy Techniques. 2021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS). :1–4.

Noise has been used as a way of protecting privacy of users in public datasets for many decades now. Differential privacy is a new standard to add noise, so that user privacy is protected. When this technique is applied for a single end user data, it's called local differential privacy. In this study, we evaluate the effects of adding noise to generate randomized responses on machine learning models. We generate randomized responses using Gaussian, Laplacian noise on singular end user data as well as correlated end user data. Finally, we provide results that we have observed on a few data sets for various machine learning use cases.

2022-02-25
Bolbol, Noor, Barhoom, Tawfiq.  2021.  Mitigating Web Scrapers using Markup Randomization. 2021 Palestinian International Conference on Information and Communication Technology (PICICT). :157—162.

Web Scraping is the technique of extracting desired data in an automated way by scanning the internal links and content of a website, this activity usually performed by systematically programmed bots. This paper explains our proposed solution to protect the blog content from theft and from being copied to other destinations by mitigating the scraping bots. To achieve our purpose we applied two steps in two levels, the first one, on the main blog page level, mitigated the work of crawler bots by adding extra empty articles anchors among real articles, and the next step, on the article page level, we add a random number of empty and hidden spans with randomly generated text among the article's body. To assess this solution we apply it to a local project developed using PHP language in Laravel framework, and put four criteria that measure the effectiveness. The results show that the changes in the file size before and after the application do not affect it, also, the processing time increased by few milliseconds which still in the acceptable range. And by using the HTML-similarity tool we get very good results that show the symmetric over style, with a few bit changes over the structure. Finally, to assess the effects on the bots, scraper bot reused and get the expected results from the programmed middleware. These results show that the solution is feasible to be adopted and use to protect blogs content.

2019-11-04
Wang, Jingyuan, Xie, Peidai, Wang, Yongjun, Rong, Zelin.  2018.  A Survey of Return-Oriented Programming Attack, Defense and Its Benign Use. 2018 13th Asia Joint Conference on Information Security (AsiaJCIS). :83-88.

The return-oriented programming(ROP) attack has been a common access to exploit software vulnerabilities in the modern operating system(OS). An attacker can execute arbitrary code with the aid of ROP despite security mechanisms are involved in OS. In order to mitigate ROP attack, defense mechanisms are also drawn researchers' attention. Besides, research on the benign use of ROP become a hot spot in recent years, since ROP has a perfect resistance to static analysis, which can be adapted to hide some important code. The results in benign use also benefit from a low overhead on program size. The paper discusses the concepts of ROP attack as well as extended ROP attack in recent years. Corresponding defense mechanisms based on randomization, frequency, and control flow integrity are analyzed as well, besides, we also analyzed limitations in this defense mechanisms. Later, we discussed the benign use of ROP in steganography, code integrity verification, and software watermarking, which showed the significant promotion by adopting ROP. At the end of this paper, we looked into the development of ROP attack, the future of possible mitigation strategies and the potential for benign use.

2019-10-08
Fan, Xinxin, Chai, Qi.  2018.  Roll-DPoS: A Randomized Delegated Proof of Stake Scheme for Scalable Blockchain-Based Internet of Things Systems. Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. :482–484.

Delegated Proof-of-Stake (DPoS) is an efficient, decentralized, and flexible consensus framework available in the blockchain industry. However, applying DPoS to the decentralized Internet of Things (IoT) applications is quite challenging due to the nature of IoT systems such as large-scale deployments and huge amount of data. To address the unique challenge for IoT based blockchain applications, we present Roll-DPoS, a randomized delegated proof of stake algorithm. Roll-DPoS inherits all the advantages of the original DPoS consensus framework and further enhances its capability in terms of decentralization as well as extensibility to complex blockchain architectures. A number of modern cryptographic techniques have been utilized to optimize the consensus process with respect to the computational and communication overhead.