Unlike CCTV, security video surveillance devices, which we have generally known about, IP cameras which are connected to a network either with or without wire, provide monitoring services through a built-in web-server. Due to the fact that IP cameras can use a network such as the Internet, multiple IP cameras can be installed at a long distance and each IP camera can utilize the function of a web server individually. Even though IP cameras have this kind of advantage, it has difficulties in access control management and weakness in user certification, too. Particularly, because the market of IP cameras did not begin to be realized a long while ago, systems which are systematized from the perspective of security have not been built up yet. Additionally, it contains severe weaknesses in terms of access authority to the IP camera web server, certification of users, and certification of IP cameras which are newly installed within a network, etc. This research grouped IP cameras hierarchically to manage them systematically, and provided access control and data confidentiality between groups by utilizing group keys. In addition, IP cameras and users are certified by using PKI-based certification, and weak points of security such as confidentiality and integrity, etc., are improved by encrypting passwords. Thus, this research presents specific protocols of the entire process and proved through experiments that this method can be actually applied. OPEN ACCESSSymmetry 2015, 7 1568
Abstract:The darknet (i.e., a set of unused IP addresses) is a very useful solution for observing the global trends of cyber threats and analyzing attack activities on the Internet. Since the darknet is not connected with real systems, in most cases, the incoming packets on the darknet ('the darknet traffic') do not contain a payload. This means that we are unable to get real malware from the darknet traffic. This situation makes it difficult for security experts (e.g., academic researchers, engineers, operators, etc.) to identify whether the source hosts of the darknet traffic are infected by real malware or not. In this paper, we present the overall procedure of the in-depth analysis between the darknet traffic and IDS alerts using real data collected at the Science and Technology Cyber Security Center (S&T CSC) in Korea and provide the detailed in-depth analysis results. The ultimate goal of this paper is to provide practical experience, insight and know-how to security experts so that they are able to identify and trace the root cause of the darknet traffic. The experimental results show that correlation analysis between the darknet traffic and IDS alerts is very useful to discover potential attack hosts, especially internal hosts, and to find out what kinds of malware infected them.
Infrastructure as a service with desktops (DIaaS) based on the extensible mark-up language (XML) is herein proposed to utilize surplus resources. DIaaS is a traditional surplus-resource integrated management technology. It is designed to provide fast work distribution and computing services based on user service requests as well as storage services through desktop-based distributed computing and storage resource integration. DIaaS includes a nondisruptive resource service and an auto-scalable scheme to enhance the availability and scalability of intra-cloud computing resources. A performance evaluation of the proposed scheme measured the clustering performance time for surplus resource utilization. The results showed improvement in computing and storage services in a connection of at least two computers compared to the traditional method for high-availability measurement of nondisruptive services. Furthermore, an artificial server error environment was used to create a clustering delay for computing and storage services and for nondisruptive services. It was compared to the Hadoop distributed file system (HDFS).
The rapid development of Internet technology and the spread of various smart devices have enabled the creation of a convenient environment used by people all around the world. It has become increasingly popular, with the technology known as the Internet of Things (IoT). However, both the development and proliferation of IoT technology have caused various problems such as personal information leakage and privacy violations due to attacks by hackers. Furthermore, countless devices are connected to the network in the sense that all things are connected to the Internet, and network attacks that have thus far been exploited in the existing PC environment are now also occurring frequently in the IoT environment. In fact, there have been many security incidents such as DDoS attacks involving the hacking of IP cameras, which are typical IoT devices, leakages of personal information and the monitoring of numerous persons without their consent. While attacks in the existing Internet environment were PC-based, we have confirmed that various smart devices used in the IoT environment—such as IP cameras and tablets—can be utilized and exploited for attacks on the network. Even though it is necessary to apply security solutions to IoT devices in order to prevent potential problems in the IoT environment, it is difficult to install and execute security solutions due to the inherent features of small devices with limited memory space and computational power in this aforementioned IoT environment, and it is also difficult to protect certificates and encryption keys due to easy physical access. Accordingly, this paper examines potential security threats in the IoT environment and proposes a security design and the development of an intelligent security framework designed to prevent them. The results of the performance evaluation of this study confirm that the proposed protocol is able to cope with various security threats in the network. Furthermore, from the perspective of energy efficiency, it was also possible to confirm that the proposed protocol is superior to other cryptographic protocols. Thus, it is expected to be effective if applied to the IoT environment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.