Borja Bordel^1,*, Ramón Alcarria¹, Joaquin Chung², Rajkumar Kettimuthu², Tomás Robles¹, Iván Armuelles³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 855-880, 2023, DOI:10.32604/cmc.2023.026787

Abstract Future components to enhance the basic, native security of 5G networks are either complex mechanisms whose impact in the requiring 5G communications are not considered, or lightweight solutions adapted to ultra-reliable low-latency communications (URLLC) but whose security properties remain under discussion. Although different 5G network slices may have different requirements, in general, both visions seem to fall short at provisioning secure URLLC in the future. In this work we address this challenge, by introducing cost-security functions as a method to evaluate the performance and adequacy of most developed and employed non-native enhanced security mechanisms in 5G networks. We categorize those… More >

Tsu-Yang Wu¹, Qian Meng¹, Lei Yang¹, Saru Kumari², Matin Pirouz^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 317-341, 2023, DOI:10.32604/cmes.2022.019595

Abstract The development of the Internet of Things has facilitated the rapid development of various industries. With the improvement in people’s living standards, people’s health requirements are steadily improving. However, owing to the scarcity of medical and health care resources in some areas, the demand for remote surgery has gradually increased. In this paper, we investigate remote surgery in the healthcare environment. Surgeons can operate robotic arms to perform remote surgery for patients, which substantially facilitates successful surgeries and saves lives. Recently, Kamil et al. proposed a secure protocol for surgery in the healthcare environment. However, after cryptanalyzing their protocol, we… More >

Maria Sameen¹, Seong Oun Hwang^2,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4559-4576, 2022, DOI:10.32604/cmc.2022.031091

Abstract Machine Learning (ML) systems often involve a re-training process to make better predictions and classifications. This re-training process creates a loophole and poses a security threat for ML systems. Adversaries leverage this loophole and design data poisoning attacks against ML systems. Data poisoning attacks are a type of attack in which an adversary manipulates the training dataset to degrade the ML system’s performance. Data poisoning attacks are challenging to detect, and even more difficult to respond to, particularly in the Internet of Things (IoT) environment. To address this problem, we proposed DISTINÏCT, the first proactive data poisoning attack detection framework… More >

Bo Yang¹, Zhengxun Guo¹, Jingbo Wang^1,*, Chao Duan², Yaxing Ren³, Yixuan Chen⁴

Energy Engineering, Vol.119, No.5, pp. 1789-1795, 2022, DOI:10.32604/ee.2022.022217

Abstract This article has no abstract. More >

Sumit Kumar^1,*, S. Indu², Gurjit Singh Walia¹

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1035-1051, 2023, DOI:10.32604/iasc.2023.024469

Abstract Android Smartphones are proliferating extensively in the digital world due to their widespread applications in a myriad of fields. The increased popularity of the android platform entices malware developers to design malicious apps to achieve their malevolent intents. Also, static analysis approaches fail to detect run-time behaviors of malicious apps. To address these issues, an optimal unification of static and dynamic features for smartphone security analysis is proposed. The proposed solution exploits both static and dynamic features for generating a highly distinct unified feature vector using graph based cross-diffusion strategy. Further, a unified feature is subjected to the fuzzy-based classification… More >

Yuzhen Liu^1,2, Xiaoliang Wang^1,2,*, Zhoulei Cao^1,2, Frank Jiang³

Journal of Cyber Security, Vol.4, No.1, pp. 57-64, 2022, DOI:10.32604/jcs.2022.028792

Abstract Vehicular ad hoc network (VANET) is a self-organizing wireless sensor network model, which is extensively used in the existing traffic. Due to the openness of wireless channel and the sensitivity of traffic information, data transmission process in VANET is vulnerable to leakage and attack. Authentication of vehicle identity while protecting vehicle privacy information is an advantageous way to improve the security of VANET. We propose a scheme based on fair blind signature and secret sharing algorithm. In this paper, we prove that the scheme is feasible through security analysis. More >

Gang Xu^1,2, Fan Yun¹, Xiu-Bo Chen^3,*, Shiyuan Xu¹, Jingzhong Wang¹, Tao Shang⁴, Yan Chang⁵, Mianxiong Dong⁶

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 531-541, 2022, DOI:10.32604/iasc.2022.028264

Abstract Secure multi-party computation has been playing a fundamental role in terms of classical cryptography. Quantum homomorphic encryption (QHE) could compute the encrypted data without decryption. At present, most protocols use a semi-honest third party (TP) to protect participants’ secrets. We use a quantum homomorphic encryption scheme instead of TP to protect the privacy of parties. Based on quantum homomorphic encryption, a secure multi-party quantum summation scheme is proposed in which N participants can delegate a server with strong quantum computing power to assist computation. By delegating the computation and key update processes to a server and a semi-honest key center,… More >

Yoosef B. Abushark¹, Asif Irshad Khan^1,*, Fawaz Alsolami¹, Abdulmohsen Almalawi¹, Md Mottahir Alam², Alka Agrawal³, Rajeev Kumar⁴, Raees Ahmad Khan³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1765-1783, 2022, DOI:10.32604/cmc.2022.025604

Abstract Machine learning is a technique that is widely employed in both the academic and industrial sectors all over the world. Machine learning algorithms that are intuitive can analyse risks and respond swiftly to breaches and security issues. It is crucial in offering a proactive security system in the field of cybersecurity. In real time, cybersecurity protects information, information systems, and networks from intruders. In the recent decade, several assessments on security and privacy estimates have noted a rapid growth in both the incidence and quantity of cybersecurity breaches. At an increasing rate, intruders are breaching information security. Anomaly detection, software… More >

Ahmed M. Ayoup^1,*, Ashraf A. M. Khalaf¹, Fahad Alraddady², Fathi E. Abd El-Samie³, Walid El-Shafai^3,5, Salwa M. Serag Eldin^2,4

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1289-1304, 2022, DOI:10.32604/iasc.2022.024381

Abstract In this article, we introduce a new cancelable biometric template generation layout depending on selective encryption technology and Dual-Tree Complex Wavelet Transform (DT-CWT) fusion. The input face biometric is entered into the automatic face-segmentation (Viola-Jones) algorithm to detect the object in a short time. Viola-Jones algorithm can detect the left eye, right eye, nose, and mouth of the input biometric image. The encoder can choose the left or right eye to generate a cancelable biometric template. The selected eye image of size M × N is XORed with the created pseudo-random number (PRN) matrix C_{M × N} to provide an… More >

Syeda Warda Asher¹, Sadeeq Jan^1,*, George Tsaramirsis², Fazal Qudus Khan³, Abdullah Khalil¹, Muhammad Obaidullah⁴

Computer Systems Science and Engineering, Vol.38, No.3, pp. 265-278, 2021, DOI:10.32604/csse.2021.016787

Abstract Software reverse engineering is the process of analyzing a software system to extract the design and implementation details. Reverse engineering provides the source code of an application, the insight view of the architecture and the third-party dependencies. From a security perspective, it is mostly used for finding vulnerabilities and attacking or cracking an application. The process is carried out either by obtaining the code in plaintext or reading it through the binaries or mnemonics. Nowadays, reverse engineering is widely used for mobile applications and is considered a security risk. The Open Web Application Security Project (OWASP), a leading security research… More >