Intrusion Detection System Using Node-Predictive Attack

Intrusion Detection System Using Node-Predictive Attack Intrusion Detection System Using Node-Predictive Attack Graph Model for Cloud Ambikavathi C Dr.S.K.Srivatsa Abstract- The role of Intrusion Detection System (IDS) in security world is considered as a key requirement for any computing model. This traditional methodology can add its own contribution of security to the distributed Cloud environment. The purpose of this paper is to clarify the steps that are needed to be taken in order to efficiently implement the IDS in cloud environment. The proposed system uses node predictive attack graph to correlate the newly occurred attacks with known attacks. The prediction steps are used to later monitor the environment and control the attacks. Keywords-Attack Graph; Cloud Computing; IDS ,; I. INTRODUCTION A. What is Cloud computing? Cloud computing is â€Å"a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction†[1]. This cloud model is co mposed of three service models, four deploy ment models and five essential characteristics . The three service models are So ftware as a Service (SaaS), Platfo rm as a Se rvice (PaaS) and Infrastructure as a Service (IaaS). The four deployment models are private cloud, public cloud, hybrid cloud and community cloud. The five essential characteristics of cloud are on-demand self-service, broad network access, resource pooling, rapid elasticity and measured service. B. What is IDS? Intrusion detection systems are software or hardware systems that automate the process of monitoring the events occurring in a computer system or network, analyzing them for malicious activities or policy violations and produces reports to a management station. IDSs a rehost-based, network-based and distributed IDSs. Hos t based IDS (HIDS) monitors specific host machines, network-based IDS (NIDS) identifies intrusions on key network points and distributed IDS (DIDS) operates both on host as well as network [7]. IDS can be a valuable addition to the security arsenal. IDS performs the following functionalities : Monitoring and analyzing both user and system activities .Analyzing system configurations and vulnerabilities .Assessing system and file integrity.Ability to recognize patterns typical of attacks.Analysis of abnormal activity patterns.Tracking user policy violations.The extensive use of virtualization in implementing cloud infrastructure brings unique security concerns for customers or tenants of a public cloud service. Virtualization alters the relationship between the OS and underlying hardware. This introduces an additional layer virtualization that itself must be properly configured, managed and secured. Specific concerns include the potential to compromise the virtualization software, or hypervisor. So virtual machine security is essential in cloud environment. C. Attack Graph Attack graphs are used to determine how vulnerable their systems are and to determine what security measures to deploy to defend their systems. In the predictive attack graph, a node represents a host and an edge represents vulnerability. The predictive attack graph representation accurately forecasts the effect of removing vulnerabilities by removing edges from the attack graph. The predictive attack graph is the full attack graph with redundant paths removed. A path is considered redundant if the path contains the same vulnerability-host pair in two or mo replaces along the same attack path. In node predictive attack graph, a node can be host or a group of hosts, and an edge can be vulnerability or a group of vulnerabilities. The node predictive attack graph is a simplified version of the predictive attack graph. The node predictive attack graph’s purpose is to mitigate the effects of â€Å"firewall explosion.† Firewall explosion causes redundancy in the predictive gr aph. Thus, the node predictive attack graph mitigates this issue by merging nodes of the attack graph. Two nodes are merged if the attacker can compromise the two hosts from all hosts the attacker has already compromised. [16] Rest of the paper is organized as follows. Section II discusses about the related work done. Proposed system is described briefly in section III. Section IV, presents the implementation part of EIDS and section V concludes with references at the end. II. RELATED WORK In this section, we present related research to our proposed work: Intrusion detection in cloud and attack graph models. A. Anomaly based IDS Anomaly or behavior based detection [7] refers to techniques that define and characterize normal or acceptable behaviors of the system (e.g., CPU usage, job execution time , system ca lls). Behaviors that deviate fro m the expected normal behavior are considered intrusions. Generation of high false alarms is the major drawback of this type which leads to low detection efficiency. But it is able to detect new attack patterns. Here, Input parameter selection and analysis of ciphered data are tedious processes . It attains low throughput but high cost. Metrics and frame work to evaluate this IDS and compare with alternate IDS techniques is in need. Also it is poor in defending themselves from attacks. To avoid false alarms in anomaly based systems the system must be trained to create the appropriate user profiles. It requires extensive training to characterize normal behavior patterns. B. Signature based I DS Signature or Misuse based detection refers to techniques that characterize known methods to penetrate a system. These penetrations are characterized as a ‘pattern’ or a ‘signature’ that the IDS looks for. The pattern/signature might be a static string or a set sequence of actions[9]. It can only detect known attacks. Frequent updation is needed in the database for signatures of new attacks. The advantages of this IDS are, it generates less number of false alarms. A single signature can detect a group of attacks. It does not require extensive training. C. Fuzzy based IDS Fuzzy logic can be used to deal with inexact description of intrusions. It provides some flexibility to the uncertain problem of intrusion detection. Fuzzy logic techniques[5] are used for classification techniques. The classification algorithm is applied to audit data collected which learns to classify new audit data as normal or abnormal data. It allows greater complexity for IDS while it provides some flexibility to the uncertain problem of IDS. Most fuzzy IDS require human intervention to determine fuzzy sets and set of fuzzy rules . D. Artificial Neural Network based The goal of using ANNs for intrusion detection[5] is to be able to generalize data from incomplete data and to be able to classify data as being normal or intrusive. It is best because of it’s self learning capabilities , quick processing and can find small behaviour deviations. But it’s downside is it requires more tra ining sa mples and time consuming. E. Data Mining based IDS Some intrusion attacks are formed based on known attacks or variant of known attacks. To detect such signatures or attacks, signature apriori algorithm can be used, which finds frequent subset (containing some features of original attack) of given attack set. In Cloud, association rules can be used to generate new signatures. Using newly generated signatures, variations of known attacks can be detected in real time[5]. F. Profile based IDS In VM profile based IDS[12], a profile is created for each virtual machine in cloud that describes network behavior of each clouduser. The behavior gathered is then used for detection of network attacks on cloud. It detects the attacks early with robustness and minimum complexity. G. Entropy based IDS Entropy is, in general, used for measuring the data’s degree of impurity using a Threshold value. Entropy based anomaly detection system[14] is mainly proposed to prevent DDoS attacks. This is done in two steps. First users are allowed to pass through a router in network site. It detects for legitimate user using detection algorithm. Second again it passes through a router in cloud site. In this methodology confirmation algorithm is incorporated to detect the intruder by checking a threshold value. H. Multithreaded IDS Multithreading technique improves IDS performance within Cloud computing environment to handle large number of data packet flows. The proposed multi-threaded NIDS[8][4] is based on three modules named: capture module, analysis module and reporting module. The first one is responsible of capturing data packets and sending them to analysis part which analyzes them efficiently through matching against pre-defined set of rules and distinguishes the bad packets to generate alerts. Finally, the reporting module can read alerts and immediately prepare alert report. The authors conducted simulation experiments to show the effectiveness of their proposed method and compared it with single thread which presented high performance in terms of processing and execution time. However, the problem of detecting new types of attacks still needs many works to be done. I. Integrated model IDS It uses the combination two or more o f above techniques. It is advantageous since each technique has some advantages and drawbacks. Grid and Cloud Computing Intrusion Detection System (GCCIDS)[10] proposed the integration of knowledge and behavior analysis to detect specific intrusions. However, the proposed prototype cannot discover new types of attacks or create an attack database which must be considered during implementing IDS. A new integrated intrusion detection approach, called FCA NN[13] is proposed based on ANN and fuzzy clustering. Through fuzzy clustering technique, the heterogeneous training set is divided to several homogenous subsets. Thus complexity of each sub training set is reduced and consequently the detection performance is increased. J. Graph based IDS A graph is constructed in which nodes represent state of attack and edges represent the correlations between attacks. Queue graph, Dependency graph and Attack graph are the existing works done on IDS. To prevent vulnerable virtual machines from be ing compromised in the cloud, a multiphase distributed vulnerability detection, measurement, and countermeasure selection mechanism called NICE[2] is proposed, which is built on attack graph-based analytical models and reconfigurable virtual network-based countermeasures. III. PROP OSED WORK In this section, we describe how to construct and utilize node predictive attack graph model to handle vulnerabilities in cloud environ ment. Any attack has some set of predefined steps to incorporate it. An attack can only be accomplished when all its pre-conditions are met [11]. So that by keen monitoring the attack can be prevented. An attack graph is an abstraction that represents the ways an attacker can violate a security policy by leveraging interdependencies among discovered vulnerabilities. An attack graph can be generated from network configuration details and known vulnerabilities within the network. An attack path is a sequence of steps that starts from an attacker’s initial state to the attacker’s goal state (security policy violation) in an attack graph. Every virtual machine has it’s own logfile for recording the actions of that virtual machine. Th is logfile along with the knowledge base provides information for constructing attack graph. Fig. 1. Proposed Architecture IV. IMPLEMENTATION EIDS is implemented using Openebula[15] and OSSIM (Open Source – Security Information Management)[3] which comprises of traffic analyzers, vulnerability scanners. OS-SIM is embedded as a virtual mach ine in the c loud environment. The ro le of this virtual machine is to monitor all other virtual machines running in the environment. OSSIM provides a Security Information and Event Management (SIEM) solution. It is a one-stop solution and integrated the open source software’s NTOP, Mrtg, Snort, Open VAS, and Nmap. OSSIM is a cost effective solution in the area of monitoring network health and security of network/hosts compared to other propriety products[6]. A. Attack Analyzer Attack Analyzer is built on the top the traffic Analyzer of OS-SIM. It uses each virtual machine’s logfile to analyze and extract attack trace steps. Whenever an attack occurs it is added to the attack graph as a node along with its state and correlation function is invoked. Attack Graph Attack Graph Generator Alert System Knowledge Base Attack Analyzer B. Correlation function Correlation function correlates this new attack with known attacks and gives the prediction steps for this attack. These prediction steps for each attack are used to monitor the further attacks in future. C. Attack Graph Generator Each node in the graph defines an attack and the edge between nodes represent the correlation between that two attacks. V. CONCLUSION Defending distributed environment is difficult. Always prevention is better than cure. Prediction of Intrusions in prior enhances the security of cloud environment. So that predictive attack graph model is chosen for providing security to the distributed cloud environment. At any point the known attacks are correlated with each other to predict new attacks. REFERENCES: [1] NIST (National Institute of Standards and Technology ) http://csrc.nist.gov/p ublications/nistp ubs/800-145/SP800-145.p df [2] Chun-Jen Chung, Pankaj Khatkar, Tiany i Xing Jeongkeun Lee, Dijian g Huan g, â€Å"NICE: Network Intrusion Detection and Countermeasure Selection in Virtual Network Systems†, IEEE Transactions On Dependable And Secure Computing, Vol. 10, No. 4, pp. 198 – 211, July /August 2013. [3] â€Å"OSSIM †, https://www.alienvault.com/ [4] Ms. Parag K. Shelke, M s. Sneha Sontakke, Dr. A. D. Gawande, â€Å"Intrusion Detection Sy stem for Cloud Comp uting†, International Journal of Scientific Technology Research Volume 1, Issue 4, M ay 2012. [5] M odi, C., Patel, D., Patel, H., Borisaniy a, B., Patel, A. Rajarajan, M ., â€Å"A survey of intrusion detection techniques in Cloud†, Journal of Network and Computer App lications. [6] â€Å"OSSIM †, http ://www.op ensourceforu.com/2014/02 /top -10-op en-source-security -tools/ [7] Amirreza Zarrabi, Alireza Zarrabi, â€Å"Internet Intrusion Detection Sy stem Service in a Cloud† IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 5, No 2, Sep tember 2012. [8] I. Gul and M . Hussain, â€Å"Distributed Cloud Intrusion Detection M odel†, International Journal of Advanced Science and Technology, vol. 34, pp. 71-82, 2011. [9] R. Bhadauria, R. Chaki, N. Chak i, and S. Sany al â€Å"A Survey on Secur ity Issues in Cloud Comp uting†, Available at: http ://arxiv.org/abs/1109.5388 [10] K. Vieira, A. Schulter, C.B. Westp hall, and C.M . Westphall, â€Å"Intrusion Detection for Grid and Cloud comp uting†, IT Professional, Volume: 12 Issue: 4, p p. 38-43, 2010. [11] X. Ou and A. Singhal, â€Å"Quantitative Secur ity Risk Assessment of Enterp rise Networks†, Sp ringerBriefs in Comp uter Scien ce, DOI 10.1007/978-1-4614-1860-3_2,  © The Author(s) 2012 [12] Sanchik a Gupta, Padam Kumar and Ajith Abraham, â€Å"A Profile Based Network Intrusion Detection and Prevention System for Secur in g Cloud Env ironment†, International Journal of Distributed Sensor Networks, Feb 2013 [13] Swati Ramteke, Rajesh Dongare, Ko mal Ramteke, â€Å"Intrusion Detection System for Cloud Network Using FC-ANN Algorithm†, Int. Journal of Advanced R esearch in Comp uter and Communication En gineeringVo l. 2, Issue 4, April 2013. [14] A.S.Sy ed Navaz, V.San geetha, C.Prabhadevi, â€Å"Entropy based Anomaly Detection System to Prevent DDoS Attacks in Cloud†, Int. Journal of Computer Applications (0975 – 8887) Volume 62– No.15, January 2013 [15] â€Å"Op ennebula†, http ://opennebula.org [16] Nwokedi C. Idika, â€Å"Characterizin g and A ggregating Attack Grap h-based Security M etrics†, CERIAS Tech Rep ort 2010

Comparing the Black Album and Rushdies The Satanic Verses Essays

The Black Album and Rushdie's The Satanic Verses      Ã‚  Ã‚   British writer C.C. Colton once claimed, "Men will wrangle for religion; write for it; fight for it; die for it; anything but--live for it" (Copeland 345). Indeed, if nothing else, Hanif Kureishi's The Black Album shows the depths to which people concern themselves with questions of religion, ethnicity, and the identity associated with them. Kureishi's themes and symbolism work within a larger context of the politics of identity, race, and nationality. Salman Rushdie's The Satanic Verses and the larger religious question associated with it, serve to polarize the British community between Muslims and non-Muslims, as well as to polarize people supporting liberation and those supporting containment. Combined with other cultural references, Kureishi uses the literary allusion to create his themes and symbolism.    The question of the racial, religious, and socioeconomic identity of Shahid becomes a central question posed as Shahid undergoes translation from his Pakistani ancestry to his desired identity as a Briton. Shahid's translation parallels the translations of the former Asian colonies of Britain into their new postcolonial identities. Unfortunately for Shahid, the struggle over The Satanic Verses catches him as he is translating himself, presenting him with a series of tough choices.    The quest for identity in Indo-English writing has emerged as a recurrent theme, as it is in much of modern literature (Pathak preface). Indeed, often the individual's identity and his quest for it becomes so bound up in the national quest for identity, that the individual's search for his identity becomes allegorical of the national search (Pathak pr... ...pular Quotations for All Uses. Garden City, New York: Garden City, 1942. Gorra, Michael. After Empire: Scott, Naipul, Rushdie. Chicago: U of Chicago P, 1997. Kureishi, Hanif. The Black Album. New York: Simon, 1995. Lings, Martin. Muhammad: His Life Based on the Earliest Sources. Revised edition. Bartlow, Cambridge, UK: Islamic Texts Society, 1991. Pathak, R.S., ed. Quest for Identity in Indian English Writing. New Delhi: Bahri, 1992. Rusdie, Salman. The Satanic Verses. First Owl Book edition. New York: Henry Holt, 1997. Saynor, James. Rev. of The Black Album, by Hanif Kureishi. The New Statesman & Society, March 3, 1995, p. 40(2). Wilkie, Brian, and James Hurt. Literature of the Western World. 2nd edition. In Galloway, Stan. "The House of Bernarda Alba." http://www.bridgewater.edu/~sgallowa/203/alba-notes.htm, April 26, 1999.    Comparing the Black Album and Rushdie's The Satanic Verses Essays The Black Album and Rushdie's The Satanic Verses      Ã‚  Ã‚   British writer C.C. Colton once claimed, "Men will wrangle for religion; write for it; fight for it; die for it; anything but--live for it" (Copeland 345). Indeed, if nothing else, Hanif Kureishi's The Black Album shows the depths to which people concern themselves with questions of religion, ethnicity, and the identity associated with them. Kureishi's themes and symbolism work within a larger context of the politics of identity, race, and nationality. Salman Rushdie's The Satanic Verses and the larger religious question associated with it, serve to polarize the British community between Muslims and non-Muslims, as well as to polarize people supporting liberation and those supporting containment. Combined with other cultural references, Kureishi uses the literary allusion to create his themes and symbolism.    The question of the racial, religious, and socioeconomic identity of Shahid becomes a central question posed as Shahid undergoes translation from his Pakistani ancestry to his desired identity as a Briton. Shahid's translation parallels the translations of the former Asian colonies of Britain into their new postcolonial identities. Unfortunately for Shahid, the struggle over The Satanic Verses catches him as he is translating himself, presenting him with a series of tough choices.    The quest for identity in Indo-English writing has emerged as a recurrent theme, as it is in much of modern literature (Pathak preface). Indeed, often the individual's identity and his quest for it becomes so bound up in the national quest for identity, that the individual's search for his identity becomes allegorical of the national search (Pathak pr... ...pular Quotations for All Uses. Garden City, New York: Garden City, 1942. Gorra, Michael. After Empire: Scott, Naipul, Rushdie. Chicago: U of Chicago P, 1997. Kureishi, Hanif. The Black Album. New York: Simon, 1995. Lings, Martin. Muhammad: His Life Based on the Earliest Sources. Revised edition. Bartlow, Cambridge, UK: Islamic Texts Society, 1991. Pathak, R.S., ed. Quest for Identity in Indian English Writing. New Delhi: Bahri, 1992. Rusdie, Salman. The Satanic Verses. First Owl Book edition. New York: Henry Holt, 1997. Saynor, James. Rev. of The Black Album, by Hanif Kureishi. The New Statesman & Society, March 3, 1995, p. 40(2). Wilkie, Brian, and James Hurt. Literature of the Western World. 2nd edition. In Galloway, Stan. "The House of Bernarda Alba." http://www.bridgewater.edu/~sgallowa/203/alba-notes.htm, April 26, 1999.   

Cost Information for decision making Essay

Two common costing systems used in business are traditionally cost accounting system (job costing, process costing and operating costing) and activity-based costing system (ABC). There are some similarities and differences between these systems. Regarding the similarities, both accumulate product costs throughout the production process and assign those costs to individual units of production. Additionally, product cost under two costing systems consists of direct materials, direct labor and manufacturing overhead. In terms of differences, they are different in the way how the overhead costs are allocated. For conventional costing, it assigns manufacturing overhead based on a single volume based cost driver such as direct labour hours. In contrast, ABC approaches cost from the perspective that products do not cause costs. It requires activities which are the causes of all costs incurred so it allocates manufacturing overhead according to the activities needed to produce the products. Therefore, it highlights the existence of non value added activity which is not existed under traditional method. ABC also differs from conventional costing in the use of several cost pools when allocating the overhead costs. For instance, traditional costing uses only one cost pool to distribute the overhead whereas there are many cost pools involved under ABC. Furthermore, ABC employs both volume-based and non-volume-based cost drivers while conventional costing utilizes only volume-based cost drivers. Another difference is that conventional approach complies with the GAAP so it can be used to satisfy conventional financial reporting requirements. On the other hand, accounting standard board does not accept ABC to prepare financial statements so it can be useful for internal management decision. Under conventional system, there are similarities between job costing, process costing and operating costing. Firstly, they accumulate product costs throughout the production process and assign those costs to products. Secondly, these costing systems calculate the product costs which comprise direct material, direct labour and manufacturing overhead. Lastly, the cost flows for three systems is from raw material to work in process to finished goods and then to costs of goods sold. These first two systems can be distinguished by the following differences. First, job costing system is used by the company which produces unique products or products based on customer orders. Conversely, process costing is for the firms which produce one or a few homogenous products and often have continuous mass production. Second, each individual product costs are traced easily under job costing while process costing makes no attempt to track individual product costs. Thirdly, under job costing, the transfer from one job to another does not take place whereas the production from one process is transferred to next one till the product is full completed under process costing. Next, process costing accumulates product costs in each production department throughout the period while job order costing accumulates product costs to specific units. Operating costing for company which has a mix production system that produces in large quantities but then is customized the finished product. Therefore, operating costing is a combination of process costing and job costing. However, it differs from job and process costing which includes more than two types of cost pools in overhead allocation process. The cost pools are designed to match the separate processes that may be allocated to batches of products. Comment about the quality of your work: According to the assessment criteria, my answer for the question should be marked 7. This is for the following reasons. Firstly, the answer is well-organized into five paragraphs which consist of differences between conventional costing and ABC costing. For instance, the first and second paragraphs demonstrate the similarities and differences between conventional costing and ABC. Apart from this, the answer also points out the similarities and differences between job costing, process costing and operating costing.

Negative Effects Of Sports - 1669 Words

Youth sports are an incredibly healthy way for kids to grow and release energy. Children in preschool can begin to take part in sports like dance and soccer, and as they grow older, the lists of sports gets longer. However, there are negatives of sports that are often not talked about by parents, coaches, schools, or the media. As a result, stigmatization occurs, leaving children struggling with sports to suffer alone. With youth sports, elevated levels of stress occur, and as a consequence, mental health can decline. Youth sports can have an adverse psychological effect on young athletes and it is an effect that can be damaging for children for their entire lives. There are certainly some psychological benefits of sports and it is one of†¦show more content†¦Competition builds up anxiety when playing other teams, but it’s seen between children on the same team. If a child is not playing up to expectations, coaches can cut and force them off the team. This can happen as early as in middle school sports. In an article all about sports cuts, Dan Rather talked about the time he was cut from a baseball team at the age of 13. He said, â€Å"When you’re that age, and you’re searching for your own identity, all you want is to be told you’re all right† (Greene). Getting cut crushes these kids’ self-esteem. Competition can really be dangerous for children. Practicing a sport can be highly beneficial to children, until it’s taken too far. Often called training now, children as young as six years old are participating in sports that require too much time. At that age, sports should be something fun to do and a favorable source of physical activity. However, whenever an athlete shows a hint of a talent, child exploitation occurs (Bean 10234). Between the ages of 7-12, adolescents should be learning identity, motives, beliefs, and values, but nearly all athletes are practicing 5 days a week with games every Saturday. 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