Hisham A. Kholidy

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By impersonating legitimate users, intruders can use the abundant resources of cloud computing environments. This paper develops a framework for "CIDS" a cloud based intrusion detection system, to solve the deficiencies of current IDSs. CIDS also provides a component to summarize the alerts and inform the cloud administrator. CIDS architecture is scalable(More)
Cloud computing is an attractive model that provides the delivery of on-demand computing resources over the Internet and on a pay-for-use basis. However, while intruders may exploit clouds for their advantage, most IDS solutions are not suitable for cloud environments. This paper presents a hierarchical and autonomous cloud based intrusion detection system,(More)
Masquerade attacks pose a serious threat for cloud system due to the massive amount of resource of these systems. Lack of datasets for cloud computing hinders the building of efficient intrusion detection of these attacks. Current dataset cannot be used due to the heterogeneity of user requirements, the distinct operating systems installed in the VMs, and(More)
Security and availability are critical for cloud environments because their massive amount of resources simplifies several attacks to cloud services. This paper introduces a distributed deployment and a centralized one for our Cloud intrusion detection framework, CIDS-VERT. After describing the architectures and the components of the two deployments it(More)
A masquerade attacker impersonates a legal user to utilize the user services and privileges. The semi-global alignment algorithm (SGA) is one of the most effective and efficient techniques to detect these attacks but it has not reached yet the accuracy and performance required by large scale, multiuser systems. To improve both the effectiveness and the(More)
Cloud computing significantly increased the security threats because intruders can exploit the large amount of cloud resources for their attacks. However, most of the current security technologies do not provide early warnings about such attacks. This paper presents a Finite State Hidden Markov prediction model that uses an adaptive risk approach to predict(More)
Word Alignment is an important supporting task for different NLP applications like training of machine translation systems, translation lexicon induction, word sense discovery, word sense disambiguation, information extraction and the cross-lingual projection of linguistic information. In this paper we study the main rules and guidelines required to build(More)
Security problems arise in software systems are very challenging. Using program analysis techniques and some language based security rules can help in enforcing application-level security through control access to program resources and verification of control flow of the information inside the program based on some security properties. This paper presents a(More)