Detecting Spam Zombies by Monitoring Outgoing Messages

Detecting Spam Zombies by Monitoring Outgoing Messages Abstract: Compromised machines are one of the key security threats on the Internet. They are often used to launch various security attacks such as spamming and spreading malware [15]. Given that spamming provides a key economic incentive for attackers to recruit a large number of compromised machines, we focus on the detection of the compromised machines in a network that are involved in the spamming activities, commonly known as spam zombies [12]. Introduction: As the use of internet increased in the era of science and technology the problem of spam has also been increased. There are multiple ways in which spam takes place we would like to discuss the spam that is passed through messages specifically through emails. When these spam mails are passed into the system these makes the system compromised and the data in the network can be stolen or lost these kind of spamming is more concern to the industry or any kind of organization where privacy is the key aspect in this competitive world. Spam: Spam can be defined as Simple Pointless Annoying Messages. According to US Federal Trade Commission (FTC) spam is defined as, any commercial electronic mail message sent, often in bulk, to a consumer without the consumers prior request or consent [1]. A recent study conducted by SMX an email security provider the percentage of spam is about 80% approx. And the average size of these spam messages in 16 Kb [2]. The results above indicate the seriousness of the problem. There are several techniques proposed and employed in filtering these spam messages such as Machine learning techniques like Neural networks(NN), Support Vector Machines(SVM), Naive Bayes Classifier. Some techniques are based on probability and others on architectural. According to Anil Kumar Gupta along with two others in his research paper stated that training SVM is easy compared to NN because NN takes more time to train than SVM and NN will not offer binary classification mechanism where has SVM does that technique t o verify the legitimate of the email [2]. Rafiqul Islam in his research proposed an architecture for spam filtering based on support vector machine [3].   T. Hamsapriya along with three others in 2014 proposed Filtered Bayesian Learning technique to increase the performance of the naÃÆ' ¯ve Bayes classifier. These all techniques have contributed in controlling spam to very much extent [4]. Spam Zombies: A machine is said to be compromised if it is successfully exploited by the attacker. These machines are used to launch various attacks in the network. These compromised machines are called zombies. The machine is made compromised when an attacker sends a spam mail to the targeted system and made a zombie [5]. Spam in Messages: Todays communication mostly happening through messages that are sent electronically through email or text messages in mobile. Our main concentration is confined to messages that are going out through a network and coming into the network that are emails. Body message based spam detection is employed in larger servers but in a research conducted by Shukor Bin Abdul Razak in 2013 showed that the feature can be manipulated and has several issues such as Manipulation of lexical patterns, efficiency, future trends. So he proposed an email header technique that has a potential in filtering spam efficiently [6]. In 2015 Wazir Zada Khan along with three others stated that the detection criterion for web spam is substantially different, so, the email spam coming from botnets cannot be handled by the web spam detection techniques. Then they proposed architecture for email spam botnet detection [7]. Algorithm:  ­Ã‚ ­SPOT detection algorithm is used to detect spammers. Before proposing SPOT detection techniques there are few works which happened in detecting spam zombies. S. Yuvaraj in 2013 came up with a four module system which consists of compose mail process, Filter spam detect, IP capture, Extraction of payloads and payload disassembly and this algorithm is called has semantic aware statistical algorithm (SAS) [8]. But this algorithm fails to catch spammers but detects spam zombies. The research also proposed algorithms in the field of botnet which is usually called a group of computers affected with malware and controlled without the notice of administrator. To control these botnets issues Guofei Gu from Georgia institute of technology came up with bot hunter based on correlation between inbound and outbound communication. This system also uses intrusion detection system(IDS) to find out the compromised machines in the network [9]. Later in 2008 again Guofei Gu along with Wank Lee p roposed another technique called botsniffer in which he extended his research in detecting compromised servers depending on the behavioral similarity in a single group of connected computers [10]. After all these works with different techniques people came up with standard algorithm called SPOT applied in detecting spam zombies which functions by monitoring outgoing messages in the network. Z. Duzan in 2009 proposed an algorithm using Sequential Probability Ratio Test(SPRT) depending on the mathematical value of the SPRT the email is as spam or not spam [11]. But he ignored the impact of dynamic IP address on the data which is considered for analysis. His research is as limitations since the algorithm is based on probability analysis and the messages arrived assumed to independent of each other but this may not be the practical scenario. Spam filters are used to detect the spam emails but these filters are not 100 percent efficient. Later in 2012 Pen cheng along with Z.Duzan modifie d his algorithm they introduced two more terms   called count threshold   and percentage threshold to calculate the impact of dynamic IP address[12]. In continuation to the work of Z. Duzan, Ar. Arunachalam along with his two students in 2013 added two more modules and applied Z. Durzan techniques in calculating the impact of dynamic IP address to entire system by adding user interface module and spam zombie detection module where he has reset the values of the captured spam emails continuously [13]. Similar work has been done by R.Vasanth Kumar and K. Ravi Kumar in 2013 they modified the existing algorithm using the IP address of the sending machine and introducing a new term called message index[14].   Parvathi Bhadre and Deepthi Gothawal in 2014 proposed a new method using SPOT detection algorithm consisting of four modules namely virus checks, Spam Checks and Spam filter, blocking of spammers using SPOT and Recovery [15]. But their research does not talk any thing about the impact spam mails generated using dynamic IP address. In 2015 Anupsingh Thakur and Prof.Praful Sambhare conducted a survey on spamming and detection control through various methods like SVM, Domain key integrated mail system(DKIMS) and SPOT detection system defined how SPOT is accurate in detecting Spams [16]. Conclusion: Brief review on spam, spam zombies, spam in messages, algorithm used and the previous works done are explained. We in our project intending to come up with improved algorithm that could effectively tackle the limitations of the previous works. References: D. C. Washington, Unsolicited commercial e-mail before the SUBCOMMITTEE ON TELECOMMUNICATIONS, TRADE AND CONSUMER PROTECTION of the COMMITTEE ON COMMERCE UNITED STATES HOUSE OF REPRESENTATIVES, 2013. [Online]. Available: https://www.ftc.gov/sites/default/files/documents/public_statements/prepared-statement-federal-trade-commission-spamming/spamtestimony1103.pdf. Accessed: Mar. 3, 2017. A. G. Kakade, P. K. Kharat, and Anil Kumar Gupta, Spam filtering techniques and MapReduce with SVM: A study, 2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE), vol. 14666087, pp. 59-64, Feb. 2014. R. I. M, W. Zhou, and M. U. Choudhury, Dynamic Feature Selection for Spam Filtering Using Support Vector Machine, 6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007), vol. 9864217, Jul. 2007. H. T, L. S. P, K. R. D, and R. C. M, SPAM CLASSIFICATION BASED ON SUPERVISED LEARNING USING MACHINE LEARNING TECHNIQUES, ICTACT Journal on Communication Technology, vol. 02, no. 04, pp. 457-462, Dec. 2011. A. Rajagopal and A. P. P, SPOT- e-mail Spam zombie detection system, International Journal of Innovative Research in Computer and Communication Engineering, vol. 2, no. 1, pp. 664-669, Jan. 2012. [Online]. Available: https://www.rroij.com/open-access/spot-email-spam-zombie-detection-system.php?aid=48276. Accessed: Mar. 3, 2017. S. Bin Abd Razak and A. F. Bin Mohamad, Identification of spam email based on information from email header, 2013 13th International Conference on Intellient Systems Design and Applications, pp. 347-353, Oct. 2014. W. Z. Khan, M. K. Khan, F. T. Bin Muhaya, M. Y. Aalsalem, and H.-C. Chao, A comprehensive study of Email Spam Botnet detection, IEEE Communications Surveys Tutorials, vol. 17, no. 4, pp. 2271-2295, Jul. 2015. Y. M. S. S., An effective defense against compromised machines by sas worm detection, International Journal of Computer Science and Management Research, pp. 33-37, 2013. G. Gu, P. Porras, V. Yegneswaran, M. Fong, and W. Lee, BotHunter: Detecting Malware Infection Through IDS-Driven Dialog Correlation, 16th USENIX Security Symposium, pp. 167-182, 2007. G. Gu, W. Lee, and J. Zhang, Botsniffer: Detecting botnet command and control channels in network traffic, Proceedings of The 15th Annual Network and Distributed System Security Symposium (NDSS 2008), Feb. 2008. Z. Duan, P. Chen, F. Sanchez, Y. Dong, M. Stephenson, and J. Barker, Detecting Spam Zombies by Monitoring Outgoing Messages, IEEE INFOCOM 2009, 2009. Z. Duan, P. Chen, F. Sanchez, Y. Dong, M. Stephenson, and J. M. Barker, Detecting Spam zombies by monitoring outgoing messages, IEEE Transactions on Dependable and Secure Computing, vol. 9, no. 2, pp. 198-210, Mar. 2012. A. Ar, V. V, and Y. V, Detecting Spam Zombies Using Spot Tool by Monitoring Outgoing Messages, International Journal of Advanced Research in Computer Science and Software Engineering, vol. 3, no. 4, pp. 400-402, Apr. 2013. V. kumar R and R. K. K, Recognizing Spam Zombies by Monitoring leaving Messages, International Journal of Engineering and Computer Science, vol. 2, no. 11, pp. 3213-3216, Nov. 2013. P. Bhadre and D. Gothawal, Detection and blocking of spammers using SPOT detection algorithm, 2014 First International Conference on Networks Soft Computing (ICNSC2014), pp. 97-101, Aug. 2014. A. Thakur and P. Sambhare, Spamming and Detection Control: A Survey, INTERNATIONAL JOURNAL FOR RESEARCH IN EMERGING SCIENCE AND TECHNOLOGY, vol. 2, no. 5, pp. 155-157, May 2015.

The Return: Shadow Souls Chapter 26

â€Å"We have to keep our minds on saving Stefan,† Elena was saying in the room Damon had taken over for his own, the old library in Lady Ulma's mansion. â€Å"Where else would my mind be?† Damon said, never taking his eyes off her neck with its ornaments of mother-of-pearl and diamonds. Somehow the milk-white dress served to emphasize the slim soft column of Elena's throat, and Elena knew it. She sighed. â€Å"If we thought you really meant it, then we could all just relax.† â€Å"You mean be as relaxed as you are?† Elena gave herself an inner shake. Damon might seem to be completely absorbed with one thing and one thing only, but his sense of self-preservation made sure that he was constantly on guard, and seeing not just what he wanted to see but everything that was around him. And it was true that Elena was almost unbearably excited. Let the others think it was about her marvelous dress – and it was a marvelous dress, and Elena was profoundly grateful to Lady Ulma and her helpers for getting it done in time. What Elena was really excited about, though, was the chance – no, the certainty, she told herself firmly – that tonight she was going to find half of the key that would allow them to free Stefan. The thought of his face, of seeing him in the flesh was†¦ Was terrifying. Thinking about what Bonnie had said when she was asleep, Elena reached out for comfort and understanding, and somehow found that instead of holding Damon's hand, she was in Damon's arms. The real question is: what will Stefan say about that night at the motel with Damon? What would Stefan say? What was there to say? â€Å"I'm frightened,† she heard, and a minute too late, recognized her own voice. â€Å"Well, don't think about it,† Damon said. â€Å"It'll only make things worse.† But I've lied, Elena thought. You don't even remember it, or you'd be lying, too. â€Å"Whatever happened, I promise I'll still be around for you,† Damon said softly. â€Å"You've got my word on that, anyway.† Elena could feel his breath against her hair. â€Å"And on keeping your mind on the key?† Yes, yes, but I haven't fed properly today. Elena started, then clasped Damon closer. For just an instant she'd felt, not merely a ravaging hunger, but a sharp pain that puzzled her. But now, before she could quite locate it in space, it was gone, and her connection to Damon had been abruptly cut off. Damon. â€Å"What?† Don't shut me out. â€Å"I'm not. I've just said all there is to say, that's all. You know I'll be looking for the key.† Thank you. Elena tried again. But you can't just starve – Who said I was starving? Now Damon's telepathic connection was back, but something was missing. He was deliberately holding something back, and concentrating on assaulting her senses with something else – hunger. Elena could feel it rampaging in him, as if he were a tiger or wolf that had gone for days – for weeks – without making a kill. The room did a slow spin around her. â€Å"It's†¦all right,† she whispered, amazed that Damon was able to stand and hold her at all, with his insides tearing at him that way. â€Å"Whatever†¦you need†¦take†¦Ã¢â‚¬  And then she felt the most gentle probing at her throat of razor-sharp teeth. She gave herself up to it, surrendering to the sensations. In preparation for the Silver Nightingale's gala, where they would be searching for the first half of the double fox key to release Stefan, Meredith had been reading some of the hard copy she'd stuffed into her bag, from the huge amount of information she had downloaded from the Internet. She had done her best to describe everything that she'd learned to Elena and the others. But how could she be sure that she hadn't missed some vital clue, some vastly important thread of information that would make all the difference tonight between success and failure? Between finding a way to save Stefan and coming home defeated, while he languished in prison. No, she thought, standing by a silvered mirror, almost afraid to look at the exotic beauty she had become. No, we can't even think of the word failure. For the sake of Stefan's life, we have to succeed. And we have to do it without getting caught.

Product Proposal Template

Product Proposal Template †¢ [Bulleted lists and bracketed text are descriptive, and should not appear in final documents. ] †¢ Assume your proposal will be one of many reviewed by potential investors. It should be accurate, concise, and self-contained. Don't assume the reader is familiar with you or your product. †¢ The proposal should be well organized, clearly written, and flow smoothly from one item to the next. The style and information should be consistent, even if different people write different parts. †¢ Use graphics (charts, diagrams, etc) where they can be more effective than text (â€Å"a picture is worth a thousand words†).Do not use cutesy or unnecessary pictures. †¢ Include or attach tables or spreadsheets for lists and comparisons. Product Proposal for [Concept] Executive Summary †¢ Write the summary last, not first. †¢ Summarize all key ideas from the proposal in less than one page. †¢ Describe the product in the first p aragraph. †¢ Do not use graphics, tables, etc. Overview 1 Introduction †¢ Describe the product, its key features and functionality. 2 Abbreviations and Definitions †¢ List and define all abbreviations and non-standard terms used. 3 Background Describe any background required to understand the product or its importance, including market or technology trends.Market Analysis 1 Needs Analysis †¢ Describe who needs the product, and why. †¢ For each market of interest, describe key characteristics, including size. †¢ Summarize the customer’s total cost. Include hardware unless you are assuming that your customers already own the necessary hardware. 2 Competitive Analysis †¢ Describe competing products, and their relative strengths ; weaknesses. †¢ Include or attach a table to summarize key characteristics. †¢ Use text (or subsections) for details not easily captured in the table. Feature or Characteristic |[Proposed Product] |Competitor( s) | | | |[#1] |[#2] |[#3] |[#4] | | | | | | | | Requirements 1 Actors ; Use Cases †¢ Describe the general categories of people who will use the product. †¢ Describe any external systems that will interact with the product. For each actor, describe why and how they interact with the product. †¢ For each actor, describe any special characteristics or background.†¢ Include or attach a table to summarize which actors perform which use cases, especially if there is overlap. |Use Case |Actor(s) | | |[#1] |[#2] |[#3] |[#4] |[#5] | | | | | | | | Requirements †¢ Include or attach a table (or a full spreadsheet) to list and describe key requirements, such as: o hardware or software (platform dependencies) o performance o networking o concurrency o data storage o internationalization (multiple languages, currencies, time zones) o error handling ; security o testing ; documentation o installation Category |Requirement |Priorit|Phase |Cost | | | |y | | | | | | | | | | | | | | | 3 Deliverables List and describe items that must be completed in order to complete this product, such as: o hardware components o software components o packaging ; documentation o licenses, user names, passwords Design 1 User Interfaces †¢ Describe the user interface(s). †¢ Include or attach sketches or mockups of GUI screens where applicable. 2 UML Design Diagrams†¢ Describe the key data objects and relationships (data diagrams). †¢ Describe any complex interactions among actors and product components (interaction diagrams). †¢ Describe the logical and physical architecture (deployment diagrams). Include or attach diagrams where applicable. 3 Other †¢ Describe any other design issues, such as: o novel algorithms or data structures o significant challenges or risks o 3rd party components you will use (commercial, open source, etc) o potential patents Project Plan 1 Team and Organization †¢ Describe each member of your team and their roles and responsibilities. †¢ Describe any missing skills you will need to make this product successful. †¢ Describe how your team is organized. 2 Estimates ; Schedule †¢ Describe the expected project schedule. Include or attach applicable tables or planning diagrams, such as: o work breakdown schedules (WBS) o PERT/CPM networks, Gantt charts, etc. (if applicable) |Date |Owner |Action or Deliverable | | | | | | | | |Resource ; Budget Requirements †¢ List and describe any needed resources (equipment, facilities, services, etc). †¢ List all costs required to build and deploy the product, including: o Supporting hardware and software that must be purchased o Effort by developers, testers, writers, etc o Sales and marketing †¢ List expected revenue sources and projected revenue. †¢ Describe your expected profit margin. †¢ Include or attach applicable tables or spreadsheets. Category |Item |Count |Unit Cost |Total Cost | | | | | | | | | | | | | 4 Risks †¢ List and describe risks that could affect features, schedule, or cost. For each, estimate probability and impact, and describe possible responses. †¢ Include or attach applicable tables or spreadsheets. |Category |Risk |Prob |Impact |Response | | | | | | | | | | | | |References †¢ List citations for any published material (including books, articles, product documentation, and web pages) used when preparing the proposal, whether or not they are quoted or cited elsewhere in the proposal.

The Bug in Black Hole - 1691 Words

The teens who occupy Charles Burnss graphic novel Black Hole are ill with what seem to be a sexually-transmitted disease that the teens identify as the bug, an increasing number of teens become infected and reside with a group of teenagers that live in separate from their families and individuals uninfected remain students at their high school in uptown Seattle. The ill teens dwell in a tent village concealed in the outskirts of their community, in the forest and they manage to survive largely on the trash and infrequent aid of the well teens. The sickness marks each teen in varying degrees; many seem grotesque while others physical manifestations are subtle, as a result the ill are alienated and rejected by the community because of†¦show more content†¦Teens typically, feel rejected by their peers and intern isolates himself or herself from the rest of the world in order to cope and deal with stigmatism. Since Chris’s mother was going to take her to the doctor and Chris knew she had the bug she didn’t want her mother to know so she runaway. This communicates to the reader the incidence of runaway teens and the fear of talking to their parents about issues they are going through. The bug The characters infected with the â€Å"bug† felt rejected their former peers because of their unconscious transition from adolescence to young adulthood: â€Å"‘I don’t know what it was†¦but suddenly we were the target of every asshole joke in town. They’d drive around searching for us at night, ganging up on us when we were out trying to find food. They did everything they could to make our lives as miserable as possible’† (no. 9). â€Å"‘Sometimes we made jokes about it†¦but it was no joke - we were scared shitless’† (no. 5). The â€Å"bug†, instead of inflicting typical disease related attribute, like pain or death, the illness causes unstable levels of freakish malformations. Unlike AIDS, however, the teen plague in Black Hole results in physical mutations, though these are not always easily observable by other people; For example, Eliza develops a miniature tail, Rob a mouth on his chest, and other characters bud grotesque mutations on the face and body. They are likeShow MoreRelatedBlack Holes Paper : Black Hole Paper1378 Words   |  6 PagesBlack Hole Paper Many philosophers have said that the ‘Eyes are the windows to the soul.’ The eyes can show a person’s true personality. Not their clothes, facial expressions, or how they hold themselves, but looking into another’s eyes will show one’s soul. But what if their personality was not found in their eyes, but on their body in the form of a mutation? 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In 1965 he applied for and received a research fellowship at Caisus College, Cambridge and married Jane Wilde. They have 3 children: Robert, Lucy, and Timothy . Meeting Jane lifted Hawking out of his terminal-illness depression, and he startedRead MoreEssay On Love Science1173 Words   |  5 Pagesthem so he could bring in a sample. Someone was doing something on bugs, and the other projects i don t remember. But i was the only one without a subject. The teacher looked over at me, she said: â€Å"Jack, what s the subject of your presentation gonna be on?† I still had no idea what to do my project on. I started thinking of things that sounded science related. I got to something, and without thinking i blurted out: â€Å"Black holes, because i couldn t think of anything else.† The teacher lookedRead MoreEssay on Ethical Computer Hacking972 Words   |  4 Pagesno morals, or ethical value behind what they do, but to compromise, and cause havoc upon the end user computing world. 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