Provenance is derivative journal information about the origin and activities of system data and processes. For a highly dynamic system like the cloud, provenance can be accurately detected and securely used in cloud digital forensic investigation activities. This paper proposes watchword oriented provenance cognition algorithm for the cloud environment. Additionally time-stamp based buffer verifying algorithm is proposed for securing the access to the detected cloud provenance. Performance analysis of the novel algorithms proposed here yields a desirable detection rate of 89.33 and miss rate of 8.66 . The securing algorithm successfully rejects 64 of malicious requests, yielding a cumulative frequency of 21.43 for MR.
A process aware approach to worm attacks and contamination have been designed, implemented and evaluated in @cite_7 . The authors identified the important issue that provenance un-awareness leads to problems in quick and accurate identification of worm attack point @cite_7 . Process coloring can be assigned to uniquely identify processes, it is inherited by the child processes and diffused through process actions.
@cite_7
2159357881 2033368661 2146697465 2056451850
To investigate the exploitation and contamination by self-propagating Internet worms, a provenance-aware tracing mechanism is highly desirable. Provenance unawareness causes difficulties in fast, accurate identification of a worms break-in point, and incurs significant log inspection overhead. This paper presents the design, implementation, and evaluation of process coloring, an efficient provenance-aware approach to worm break-in and contamination tracing. More specifically, process coloring assigns a "color", a unique system-wide identifier, to each remotely-accessible server or process. The color will then be either inherited by spawned child processes or diffused indirectly through process actions (e.g., read write operations). Process coloring brings two major advantages: (1) It enables fast color-based identification of a worms break-in point even before detailed log analysis; (2) It naturally partitions log data based on their colors, effectively reducing the volume of log data that need to be examined for worm investigation. A tamper-resistant log collection method is developed based on the virtual machine introspection technique. Our experiments with a number of real-world worms demonstrate the advantages of processing coloring. Several syntactic-based automatic worm signature generators, e.g., Polygraph, have recently been proposed. These systems typically assume that a set of suspicious flows are provided by a flow classifier, e.g., a honeynet or an intrusion detection system, that often introduces "noise" due to difficulties and imprecision inflow classification. The algorithms for extracting the worm signatures from the flow data are designed to cope with the noise. It has been reported that these systems can handle a fairly high noise level, e.g., 80 for Polygraph. In this paper, we show that if noise is introduced deliberately to mislead a worm signature generator, a much lower noise level, e.g., 50 , can already prevent the system from reliably generating useful worm signatures. Using Polygraph as a case study, we describe a new and general class of attacks whereby a worm can combine polymorphism and misleading behavior to intentionally pollute the dataset of suspicious flows during its propagation and successfully mislead the automatic signature generation process. This study suggests that unless an accurate and robust flow classification process is in place, automatic syntactic-based signature generators are vulnerable to such noise injection attacks. The increasing incidence of worm attacks in the Internet and the resulting instabilities in the global routing properties of the border gateway protocol (BGP) routers pose a serious threat to the connectivity and the ability of the Internet to deliver data correctly. In this paper we propose a mechanism to detect predict the onset of such instabilities which can then enable the timely execution of preventive strategies in order to minimize the damage caused by the worm. Our technique is based on online statistical methods relying on sequential change-point and persistence filter based detection algorithms. Our technique is validated using a year's worth of real traces collected from BGP routers in the Internet that we use to detect predict the global routing instabilities corresponding to the Code Red II, Nimda and SQL Slammer worms. In the last years there has been an increasing interest in the security of process control and SCADA systems. Furthermore, recent computer attacks such as the Stuxnet worm, have shown there are parties with the motivation and resources to effectively attack control systems. While previous work has proposed new security mechanisms for control systems, few of them have explored new and fundamentally different research problems for securing control systems when compared to securing traditional information technology (IT) systems. In particular, the sophistication of new malware attacking control systems--malware including zero-days attacks, rootkits created for control systems, and software signed by trusted certificate authorities--has shown that it is very difficult to prevent and detect these attacks based solely on IT system information. In this paper we show how, by incorporating knowledge of the physical system under control, we are able to detect computer attacks that change the behavior of the targeted control system. By using knowledge of the physical system we are able to focus on the final objective of the attack, and not on the particular mechanisms of how vulnerabilities are exploited, and how the attack is hidden. We analyze the security and safety of our mechanisms by exploring the effects of stealthy attacks, and by ensuring that automatic attack-response mechanisms will not drive the system to an unsafe state. A secondary goal of this paper is to initiate the discussion between control and security practitioners--two areas that have had little interaction in the past. We believe that control engineers can leverage security engineering to design--based on a combination of their best practices--control algorithms that go beyond safety and fault tolerance, and include considerations to survive targeted attacks.