• International Journal of Computer Science & Network Security
• /
• v.23 no.6
• /
• pp.169-175
• /
• 2023

Ethical hackers are using different tools and techniques to encounter malicious cyber-attacks generated by bad hackers. During the software development process, development teams typically bypass or ignore the security parameters of the software. Whereas, with the advent of online web-based software, security is an essential part of the software development process for implementing secure software. Security features cannot be added as additional at the end of the software deployment process, but they need to be paid attention throughout the SDLC. In that view, this paper presents a new, Ethical Hacking - Software Development Life Cycle (EH-SDLC) introducing ethical hacking processes and phases to be followed during the SDLC. Adopting these techniques in SDLC ensures that consumers find the end-product safe, secure and stable. Having a team of penetration testers as part of the SDLC process will help you avoid incurring unnecessary costs that come up after the data breach. This research work aims to discuss different operating systems and tools in order to facilitate the secure execution of the penetration tests during SDLC. Thus, it helps to improve the confidentiality, integrity, and availability of the software products.

• Journal of the Korea Convergence Society
• /
• v.8 no.8
• /
• pp.51-57
• /
• 2017

A wireless sensor network is composed of many resource constrained sensor nodes. These networks are attacked by malicious attacks like DDoS and routing attacks. In this paper, we propose the intrusion detection and prevention system using convergence of software-defined networking and security technology in wireless sensor networks. Our proposed scheme detects various intrusions in a central server by accumulating log messages of OpenFlow switch through SDN controller and prevents the intrusions by configuring OpenFlow switch. In order to validate our proposed scheme, we show it can detect and prevent some malicious attacks in wireless sensor networks.

• International Journal of Computer Science & Network Security
• /
• v.23 no.7
• /
• pp.186-192
• /
• 2023

Malwares are becoming a major problem nowadays all around the world in android operating systems. The malware is a piece of software developed for harming or exploiting certain other hardware as well as software. The term Malware is also known as malicious software which is utilized to define Trojans, viruses, as well as other kinds of spyware. There have been developed many kinds of techniques for protecting the android operating systems from malware during the last decade. However, the existing techniques have numerous drawbacks such as accuracy to detect the type of malware in real-time in a quick manner for protecting the android operating systems. In this article, the authors developed a hybrid model for android malware detection using a decision tree and KNN (k-nearest neighbours) technique. First, Dalvik opcode, as well as real opcode, was pulled out by using the reverse procedure of the android software. Secondly, eigenvectors of sampling were produced by utilizing the n-gram model. Our suggested hybrid model efficiently combines KNN along with the decision tree for effective detection of the android malware in real-time. The outcome of the proposed scheme illustrates that the proposed hybrid model is better in terms of the accurate detection of any kind of malware from the Android operating system in a fast and accurate manner. In this experiment, 815 sample size was selected for the normal samples and the 3268-sample size was selected for the malicious samples. Our proposed hybrid model provides pragmatic values of the parameters namely precision, ACC along with the Recall, and F1 such as 0.93, 0.98, 0.96, and 0.99 along with 0.94, 0.99, 0.93, and 0.99 respectively. In the future, there are vital possibilities to carry out more research in this field to develop new methods for Android malware detection.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.24 no.6
• /
• pp.1215-1224
• /
• 2014

Various research was done to protect user's private data from malicious application which expose user's private data and abuse exposed data. However, a new type of malicious application were appeared. And these malicious applications use a smart phone as a new tools to perform secondary attack. Therefore, in this paper, we propose a method to detect the DDoS attack application installed inside the mobile device using the Android logging system.

• International Journal of Computer Science & Network Security
• /
• v.21 no.12
• /
• pp.213-218
• /
• 2021

This paper proposes a technique for detecting a significant threat that attempts to get sensitive and confidential information such as usernames, passwords, credit card information, and more to target an individual or organization. By definition, a phishing attack happens when malicious people pose as trusted entities to fraudulently obtain user data. Phishing is classified as a type of social engineering attack. For a phishing attack to happen, a victim must be convinced to open an email or a direct message [1]. The email or direct message will contain a link that the victim will be required to click on. The aim of the attack is usually to install malicious software or to freeze a system. In other instances, the attackers will threaten to reveal sensitive information obtained from the victim. Phishing attacks can have devastating effects on the victim. Sensitive and confidential information can find its way into the hands of malicious people. Another devastating effect of phishing attacks is identity theft [1]. Attackers may impersonate the victim to make unauthorized purchases. Victims also complain of loss of funds when attackers access their credit card information. The proposed method has two major subsystems: (1) Data collection: different websites have been collected as a big data corresponding to normal and phishing dataset, and (2) distributed detection system: different artificial algorithms are used: a neural network algorithm and machine learning. The Amazon cloud was used for running the cluster with different cores of machines. The experiment results of the proposed system achieved very good accuracy and detection rate as well.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.10
• /
• pp.3793-3814
• /
• 2021

Most secure solutions like cryptography are software based and they are designed to mainly deal with the outside attacks for traditional networks, but such soft security is hard to be implemented in wireless sensor networks to counter the inside attacks from internal malicious nodes. To address this issue, reputation has been introduced to tackle the inside malicious nodes. Reputation is essentially a stimulating mechanism for nodes' cooperation and is employed to detect node misbehaviors and improve the trust-worthiness between individual nodes. Among the reputation models, binomial distribution based reputation has many advantages such as light weight and ease of implementation in resource-constraint sensor nodes, and accordingly researchers have proposed many insightful related methods. However, some of them either directly use the modelling results, apply the models through simple modifications, or only use the required components while ignoring the others as an integral part of the whole model, this topic still lacks a comprehensive and systematical review. Thus the motivation of this study is to provide a thorough survey concerning each detailed functional components of binomial distribution based reputation for wireless sensor networks. In addition, based on the survey results, we also argue some open research problems and suggest the directions that are worth future efforts. We believe that this study is helpful to better understanding the reputation modeling mechanism and its components for wireless sensor networks, and can further attract more related future studies.

• The KIPS Transactions:PartD
• /
• v.11D no.2
• /
• pp.423-434
• /
• 2004

This paper presents the software system that protects illegal installation and use of the commercial software. The server computer in this system stores the compressed versions for all software, while client computers install all software by downloading them from the server. Also the client computers periodically report to the server whether they have illegally installed software. This system introduces authentication and encryption/decryption using the session key under Windows Operating System to prevent interception of the software package from outside world and malicious modification of the transfer message between the server and the client. The proposed system in this Paper has several advantages such as providing real-time control of license and easy maintenance of the software as well as protecting illegal use of the software.

• Journal of Korea Society of Industrial Information Systems
• /
• v.20 no.5
• /
• pp.37-44
• /
• 2015

An antivirus is a widely used solution for detecting malicious softwares in client devices. The performance of antivirus solutions in the mobile client environment is critical due to its resource constrains. Many solutions light-weighting client's overhead in the mobile client environment have been developed. However, most solutions require platform modifications or software installations and it decreases their realizations in practice. In this paper, we propose a solution detecting malwares on networks using the Software Defined Network (SDN). Our main goal is designing a solution detecting malwares of mobile client without involving the client into the work. We contribute to provide a solution that does not require client-side installations or modifications and so is easily applicable in practice.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.3 s.35
• /
• pp.75-88
• /
• 2005

This paper proposes a method to ensure security attacks caused by insertion of malicious codes in a real-time control system that can be accessed through networks. The proposed technique is for dynamically upgradable real-time software through networks and based on a static program analysis technique to detect the malicious uses of memory access statements. Validation results are shown using a remotely upgradable real-time control system equipped with a modified compiler where the proposed security technique is applied.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.04a
• /
• pp.501-503
• /
• 2015

Malicious(악의적인) + Code 즉, 악의적인코드를 포함한 소프트웨어라는 의미로 줄여 Malware(Malicious + Software) 라고 불리는 악성코드는 최근 네트워크와 컴퓨터의 급속한 발전에 따라 기하급수적으로 증가하고 있는 추세이다. 폭발적인 증가율 추세를 보이고 있는 악성코드의 위협을 대비하기 위해 악성코드에 대한 분석이 필요한데 그 분석의 종류로는 초기분석, 동적 분석, 정적분석으로 나누고 장, 단점을 정리하였다. 또한 악성코드 대량화에 따른 효율적인 분석과 빠른 의사결정을 위한 악성코드 유사도에 대한 연구를 소개하고 API Call Sequence와 분류된 API를 이용한 악성행위 유사도 판별법을 제시하고 실험하였다.