Huaiguang Wu, Yibo Peng, Yaqiong He^*, Jinlin Fan

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 77-108, 2024, DOI:10.32604/cmes.2024.046758

Abstract In recent years, the number of smart contracts deployed on blockchain has exploded. However, the issue of vulnerability has caused incalculable losses. Due to the irreversible and immutability of smart contracts, vulnerability detection has become particularly important. With the popular use of neural network model, there has been a growing utilization of deep learning-based methods and tools for the identification of vulnerabilities within smart contracts. This paper commences by providing a succinct overview of prevalent categories of vulnerabilities found in smart contracts. Subsequently, it categorizes and presents an overview of contemporary deep learning-based tools developed for smart contract detection. These… More > Graphic Abstract

Peng Gong^1,2,3, Wenzhong Yang^2,3,*, Liejun Wang^2,3, Fuyuan Wei^2,3, KeZiErBieKe HaiLaTi^2,3, Yuanyuan Liao^2,3

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1439-1462, 2023, DOI:10.32604/cmc.2023.038878

Abstract Smart contracts have led to more efficient development in finance and healthcare, but vulnerabilities in contracts pose high risks to their future applications. The current vulnerability detection methods for contracts are either based on fixed expert rules, which are inefficient, or rely on simplistic deep learning techniques that do not fully leverage contract semantic information. Therefore, there is ample room for improvement in terms of detection precision. To solve these problems, this paper proposes a vulnerability detector based on deep learning techniques, graph representation, and Transformer, called GRATDet. The method first performs swapping, insertion, and symbolization operations for contract functions,… More >

So-Eun Jeon, Sun-Jin Lee, Il-Gu Lee^*

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2407-2419, 2023, DOI:10.32604/iasc.2023.039937

Abstract With the development of the 5th generation of mobile communication (5G) networks and artificial intelligence (AI) technologies, the use of the Internet of Things (IoT) has expanded throughout industry. Although IoT networks have improved industrial productivity and convenience, they are highly dependent on nonstandard protocol stacks and open-source-based, poorly validated software, resulting in several security vulnerabilities. However, conventional AI-based software vulnerability discovery technologies cannot be applied to IoT because they require excessive memory and computing power. This study developed a technique for optimizing training data size to detect software vulnerabilities rapidly while maintaining learning accuracy. Experimental results using a software… More >

Guangxia Xu^1,*, Lei Liu², Jingnan Dong³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 903-922, 2023, DOI:10.32604/cmes.2023.026627

Abstract In recent years, with the great success of pre-trained language models, the pre-trained BERT model has been gradually applied to the field of source code understanding. However, the time cost of training a language model from zero is very high, and how to transfer the pre-trained language model to the field of smart contract vulnerability detection is a hot research direction at present. In this paper, we propose a hybrid model to detect common vulnerabilities in smart contracts based on a lightweight pre-trained language model BERT and connected to a bidirectional gate recurrent unit model. The downstream neural network adopts… More >

LiangJun Deng¹, Hang Lei¹, Zheng Yang¹, WeiZhong Qian^1,*, XiaoYu Li¹, Hao Wu², Sihao Deng³, RuChao Sha¹, WeiDong Deng⁴

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2155-2170, 2023, DOI:10.32604/csse.2023.027680

Abstract In order to realize a general-purpose automatic formal verification platform based on WebAssembly technology as a web service (FVPS), which aims to provide an automated report of vulnerability detections, this work builds a Hyperledger Fabric blockchain runtime model. It proposes an optimized methodology of the functional equivalent translation from source program languages to formal languages. This methodology utilizes an external application programming interface (API) table to replace the source codes in compilation, thereby pruning the part of housekeeping codes to ease code inflation. Code inflation is a significant metric in formal language translation. Namely, minor code inflation enhances verification scale… More >

Abdulaziz Alhumam^*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1463-1482, 2022, DOI:10.32604/cmc.2022.029473

Abstract The most resource-intensive and laborious part of debugging is finding the exact location of the fault from the more significant number of code snippets. Plenty of machine intelligence models has offered the effective localization of defects. Some models can precisely locate the faulty with more than 95% accuracy, resulting in demand for trustworthy models in fault localization. Confidence and trustworthiness within machine intelligence-based software models can only be achieved via explainable artificial intelligence in Fault Localization (XFL). The current study presents a model for generating counterfactual interpretations for the fault localization model's decisions. Neural system approximations and disseminated presentation of… More >

Wenjing Wang¹, Tengteng Zhao¹, Xiaolong Li^1,*, Lei Huang¹, Wei Zhang¹, Hui Guo²

Journal of Cyber Security, Vol.4, No.1, pp. 1-15, 2022, DOI:10.32604/jcs.2022.026816

Abstract At present, the network security situation is becoming more and more serious. Malicious network attacks such as computer viruses, Trojans and hacker attacks are becoming more and more rampant. National and group network attacks such as network information war and network terrorism have a serious damage to the production and life of the whole society. At the same time, with the rapid development of Internet of Things and the arrival of 5G era, IoT devices as an important part of industrial Internet system, have become an important target of infiltration attacks by hostile forces. This paper describes the challenges facing… More >

Adnan Alam Khan^1,2,*, Qamar-ul-Arfeen¹

Journal of Cyber Security, Vol.3, No.4, pp. 201-205, 2021, DOI:10.32604/jcs.2021.024614

Abstract Technology is expanding like a mushroom, there are various benefits of technology, in contrary users are facing serious losses by this technology. Furthermore, people lost their lives, their loved ones, brain-related diseases, etc. The industry is eager to get one technology that can secure their finance-related matters, personal videos or pictures, precious contact numbers, and their current location. Things are going worst because every software has some sort of legacy, deficiency, and shortcomings through which exploiters gain access to any software. There are various ways to get illegitimate access but on the top is Linux Kali with QRLjacker by user… More >