Jae-Ik Cho

Toward Advanced Mobile Cloud Computing for the Internet of Things: Current Issues and Future Direction

Cloud computing is the coming new era of information processing and has proved its benefits in high scalability and functional diversity. However, almost all cloud-computing architectures including SaaS, PaaS, and IaaS are vulnerable to serious security issues. Similarly, Mobile Cloud Computing (MCC) is vital to overcoming mobile limited storage and computing capabilities. MCC authentication and authorization issues must be provided on two levels: login password control and the environment from where the cloud is accessed. MCC has overcome the barrier of limited storage by providing remote storage but requires a strict security system that is responsible for retrievability, integrity, and seamless storage access. Elasticity and connectivity are also of major concern in MCC because delays and jitters cause degradation in the user experience. Cloud-computing architecture creates more challenges in maintaining security because of the liberty of users to choose any MCC architecture. Thus in this paper we discuss current cloud computing issues and future directions.

Waveform analysis of tremor may help to differentiate Parkinson's disease from drug-induced parkinsonism

In this study, we analyzed the waveform characteristics of resting tremor by accelerometer recordings in patients with drug-induced parkinsonism (DIP) and Parkinsons disease (PD). We prospectively recruited 12 patients with tremulous PD and 12 patients with DIP presenting with resting tremor. Tremor was recorded from the more affected side and was recorded twice for a 60 s period in each patient. Peak frequency, amplitude and all harmonic peaks were obtained, and the asymmetry of the decay of the autocorrelation function, third momentum and time-reversal invariance were also computed using a mathematical algorithm. Among the parameters used in the waveform analysis, the harmonic ratio, time-reversal invariance and asymmetric decay of the autocorrelation function were different between PD and DIP at a statistically significant level (all p < 0.01). The total harmonic peak power and third momentum in the time series were not significantly different. The clinical characteristics of DIP patients may be similar to those of PD patients in some cases, which makes the clinical differentiation between DIP and PD challenging. Our study shows that the identification of parameters reflecting waveform asymmetry might be helpful in differentiating between DIP and PD.

A Novel Approach to Analyzing for Detecting Malicious Network Activity Using a Cloud Computing Testbed

Recent developments have caused the expansion of various cloud computing environments and services. Cloud computing environments have led to research in the areas of data processing, virtual environments, and access control. Information security is the most important research area for these environments security. In this study, we analyzed typical example of network testbeds, which have been used for malicious activity data collection and its subsequent analysis. Further, we propose an effective malicious network application testbed, which is based on a cloud system. We also verified the performance of our new testbed by comparing real malicious activity with the cloud-based testbed results.

Dynamic learning model update of hybrid-classifiers for intrusion detection

Machine Learning as network attack detection is one of the popular methods researched. Signature based network attack detection is no longer convinced the efficiency in the diversified intrusions (Limmer and Dressler in 17th ACM Conference on Computer and Communication Security, 2010). Moreover, as the various Zero-day attacks, non notified attacks cannot be detected (Wu and Banzhaf in Appl Soft Comput 10(1):1–35, 2010). This paper suggests an effective update method of data set on Machine Learning to detect non notified attacks. In addition, this paper compares and verifies the effects of Machine Learning Detection with updated data set to the former methods.

A statistical model for network data analysis: KDD CUP 99’ data evaluation and its comparing with MIT Lincoln Laboratory network data☆

Abstract In network data analysis, research about how accurate the estimation model represents the universe is inevitable. As the speed of the network increases, so will the attacking methods on future generation communication network. To correspond to these wide variety of attacks, intrusion detection systems and intrusion prevention systems also need a wide variety of counter measures. As a result, an effective method to compare and analyze network data is needed. These methods are needed because when a method to compare and analyze network data is effective, the verification of intrusion detection systems and intrusion prevention systems can be trusted. In this paper, we use extractable standard protocol information of network data to compare and analyze the data of MIT Lincoln Lab with the data of KDD CUP 99 (modeled from Lincoln Lab). Correspondence Analysis and statistical analyzing method is used for comparing data.

Enhanced Security Protocols for EPC Global Gen2 on Smart Grid Network

Recent developments in the field of network communications have prompted the rise of smart grid research in the United States, China, and South Korea. RFID has become a standard technology within that domain, however many weaknesses in the security of smart grid communication still remain. In this paper we present a lightweight security protocol based on the current standard EPCGlobal Gen2. We also propose an enhanced security scheme for smart grid networks using a protocol based on the One Time Password (OPT) algorithm.

Effective Feature Selection Model for Network Data Modeling

Network data modeling is a essential research for the evaluation for intrusion detection systems performance, network modeling and methods for analyzing network data. In network data modeling, real data from the network must be analyzed and the modeled data must be efficiently composed to reflect a sufficient amount of the original data. In this parer the useful elements of real network data were quantified from packets captured from a huge network. Futhermore, a statistical analysis method was used to find the most effective element for efficiently classifying the modeled data.

A Network Data Abstraction Method for Data Set Verification

Network data sets are often used for evaluating the performance of intrusion detection systems and intrusion prevention systems[1]. The KDD CUP 99’ data set, which was modeled after MIT Lincoln laboratory network data has been a popular network data set used for evaluation network intrusion detection algorithm and system. However, many points at issues have been discovered concerning the modeling method of the KDD CUP 99’ data. This paper proposed both a measure to compare the similarities between two data groups and an optimization method to efficiently modeled data sets with the proposed measure. Then, both similarities between KDD CUP 99’ and MIT Lincoln laboratory data that between our composed data set from the MIT Lincoln laboratory data and MIT Lincoln laboratory are compared quantitatively.

A Study on the Malicious Web Page Detection Systems using Real-Time Behavior Analysis

The recent trends in malwares show the most widely used for the distribution of malwares that the targeted computer is infected while the user is accessing to the website, without being aware of the fact that, in which the harmful codes are concealed. In this thesis, we propose a new malicious web page detection system based on a real time analysis of normal/abnormal behaviors in client-side. By means of this new approach, it is not only the limitation of conventional methods can be overcome, but also the risk of infection from malwares is mitigated.

A Suggestion for Cloud Environments New Layer Contemplating and Its Security Factors

The cloud computing environments, according to recent developments have caused the expansion of various services. Therefore the cloud computing environments led research on data processing, virtual environment, and access control. Also study on information security area is most important particular of this environment. In this paper we analyze several typical examples of cloud services and cloud systems of the existing problems were identified. In addition, the architecture of a typical component of cloud services was compared and proposed generalized form secure cloud services architecture.