Dentitic Cell and Immune Networks Algorithm Comparison

Dentitic Cell and Immune Networks Algorithm Comparison A Comparative study of Dentitic cell and immune networks algorithm for Artificial immune networks. Jaspreet kaur, Kamal Kumar Abstract – Artificial immune systems are the systems used for advanced computational systems for the need of robust and secure functioning of computer systems. They are the systems inspired by the human immune systems in the human immunity save the body from external threats. We in this paper would be working on the networking branch of the AIS which is called Artificial immune networks which builds up an immunity in the network against the attacks. The accuracy, time analysis and a few other parameters are to be studied using two algorithms of Artificial immune networks. The two algorithms which we are taking in action will be immune networks algorithm and Dentritic cell algorithm. 1 INTRODUCTION An immune system, one of the most intricate biological sys-tems, has been used as a metaphor for intelligent computation in a variety of domains. Artificial Immune System (AIS) has been considered as a family of techniques originated from the community of immunology. As an important constituent of the AIS, the artificial immune networks are based on the principles of the behaviors of both B cells and T cells in the biological immune system. B cell is an integral part of the immune system. Through a process of recognition and stimulation, the B cells can clone and mutate to produce a diverse set of antibodies in an attempt to remove the infection from the body. T cell has two types. One regulates and con-trols the strength of the immune response, and the other di-rectly destroys the cells that have specific antigens. Both the B cells and T cells have been widely employed to solve a wide range of engineering problems, such as anomaly detection and data mining. This paper aims at giving a concise overview on the artificial immune network models including their theory, structures, and applications. Functions, principles and models, which can be applied to real world problems. According to the mechanis of DCs, the Dendritic cell Algorithm (DCA) has been put forward by Greensmith and successfully applied to a range of problems, particularly in the area of anomaly detection Compared with the classical AIS algorithms , the DCA has advantages of small calculations, strong recognition ability and few training samples, but it also hasthe defect that it will have promising detection accuracy onlyin ordered data sets, with the increasing of the disorder degree in data sets, the accuracy will reduce and the false positives and the false negatives will increase obviously. Experiments show that except some noise data most of the mistakes occur during the transition phases, this is because during a transition phase there is a small degree of confusion regarding temporally and spatially clustered antigens and DC may sample multiple antigens in different types of context. The Dendritic Cell Algorithm (DCA) is a second generation Artificial Immune System (AIS) algorithm. It is based on an abstract model of the function of dendritic cells and their ability to discriminate between healthy and infected tissue . As a context-aware anomaly detection algorithm, the DCA performs well in malware detection. Current research with this algorithm have suggested that the DCA shows not only excellent performance on detection rate, but also promise in assisting in reducing the number of false positive errors shown with similar systems. However, as the defenses evolve, so does the malware. The DCA distinguishes between normal and potentially malicious antigens on the basis of the concentration of danger signals they cause and neighboring antigens. This feature cabe exploited by crafty malware via mimicry attacks (such as blending with normal activities or mimicking normal behavior) to evade detection by the DCA . For example, some stealthy malware communicate with remote servers only when they detect user activities (such as requesting web pages). This reduces both the frequency and significance of malicious behavior, making the malware less active and more likely to avoid detection by the DCA. In , Gu et al. proposed an improvement for the DCA namely antigen multiplier to overcome the problem of ‘antigen deficiency’. As an additional function of the DCA, antigen multiplier can make several copies of each individual antigen which can be fed to multiple dendritic cells (DCs). Then the classification deci sion is averaged over the replicated population. The experimental results showed that antigen multiplier helped in improving the classification accuracy. But, as antigen multiplier copies every antigen it meets indifferently, it may show less resistance to mimicry attacks since the concentration of potentially malicious antigens is not increased. Similar to the inefficient detection to hidden and inactive malware by the DCA, biological immune system (BIS) also shows inefficiency when responds to some antigens. 2 LITERATURE REVIEW In this research paper [1] the author has analysed the immune theory and hopfied neural network (HNN), them proposing a new algorithm for multidimensional functionality. A group of solutions are collected for analyses using k means algorithm. Then later on the cluster is taken which is cluster centurions by k means algorithm. In this paper, by making use of the advantages of clustering analysis algorithm, HNN and ia, a new algorithm is proposed to solve the optimal problems of multimodal function with high dimensions. Simulation experiment proves that the new algorithm has much higher accuracy and shorter running time, compared with ia. Especially, at high dimensional function, the new algorithm has clearly advantage. In this paper[2], a novel multi-modal optimization algorithm, namely Dcopt-aiNet is proposed, which is based on biological immune network mechanism for global numerical optimization. Different from de Castro’s opt-aiNet algorithm, Dcopt-aiNet models cloning operation using dynamic cloning operation which is adopted from biological immune network mechanism. Based on the multi-modal benchmarks, experiments were carried out to compare the performance of Dcopt-aiNet with that of opt-aiNet. Experiment results show that when compared with the opt-aiNet method, the new algorithm is capable of improving search performance significantly in successful rate and convergence speed. In this paper [3] the author has proposed the the use of DCA for malwre detection. Artificial adjuvants increase immunogenicity of stealthy malware which speeds up the immunigenicity of them. This is how they improve the malware detection with help of DCA. Future work proposed in this paper is that the experiments need to evaluate their effects on enhancing the detection performance of dca. Further we need to better understand the mechanisms of immunological adjuvants can be beneficial to design more biologically. Lastly to make more diverse and more general algorithms. In this research paper[4] the algorithm is posed to only good in ordered data set but the results in the other cases are not considered to be great. In instances of different antigens, each instance is accesed and finally all the asessments made are taken into account. Proposed algorithm i.e. Mmdca brings up the nature of each multiplier and also it can be inferred that the false positives is higher, this is because the dca weights matrix used to calculate the semi and mat tends to mat. With the intrinsic properties of multimodal optimization problems, a multi-population artificial immune network algorithm (mopt-aiNet) is proposed to improve the performance of static and time-varing multimodal optimization problems by making use of biologic immune mechanism in this paper[5]. Compared with other immune network search methods, several novel operations such as multi-population dynamic hypermutation, asynchronous colony evolution, dynamic memory solutions management and a hill-valley exploring are designed which can speed up  searching the environment in an optimal way. Two other immune network algorithms are compared against mopt-aiNet by using static and dynamic benchmarks. Comparative analysis illustrates mopt-aiNet’s potential value. A bi-objective optimization model of power and power changes generated by a wind turbine is discussed in this paper[6]. The model involves two objectives, power maximization and power ramp rate (PRR) minimization. A new constraint for power maximization based on physics and process control theory is introduced. Data-mining algorithms were used to identify the model of power generation from the industrial data collected at a wind farm. The models and constraints derived from the data were integrated to optimize the power itself and the power variability, expressed as the power ramp rate. Due to the nonlinearity and complexity of the optimization model, an artificial immune network algorithm was used to solve it. The optimization results, such as computed operation strategies and the corresponding outputs, are demonstrated and discussed. In this paper [7] , the problem of finding the optimal collision free path, path planning for the case of a controllable mobile robot moving in a static environment filled with obstacles with known shape and size is studied. A path planner based on a hybrid memetic algorithm, Genetic Artificial Immune Network (GAIN), which provides near optimal collision free path is proposed. Genetic Artificial Immune Network is a hybrid memetic algorithm based on Genetic Algorithm (GA) and Artificial Immune Network (AIN) algorithm. The network cell structures are simple which makes the operators simple and results in a fast calculation with smaller number of cells. The results obtained from GAIN is compared with that of GA and GAIN is found to outperform. GA in terms of convergence speed and result obtained, making it a promising algorithm for solving the mobile robot path planning problem. 3 PROBLEM FORMULATION Adaptive immunity is directed towards specific invaders; either seen before or not previously encountered and gets modified by exposure to invaders. It mainly consists of lymphocytes (white blood cells, more specifically B and T type) that aid the process of recognizing and destroying specific substances, and are antigen-specific. Clonal Selection: Clonal selection theory was proposed by Burnet. The theory is used to explain basic response of adaptive immune system to antigenic stimulus. It establishes the idea that only those cells capable of recognizing an antigen will proliferate while other cells are selected against. Clonal selection operates on both B and T cells. B cells, when their antibodies bind with an antigen, are activated and differentiated into plasma or memory cells. Prior to this process, clones of B cells are produced and undergo somatic hyper mutation. As a result, diversity is introduced into the B cell population. Plasma cells produce antigen-specific antibodies that are work against antigen. Memory cells remain with the host and promote a rapid secondary response. Negative Selection :Negative selection is a mechanism to protect body against self-reactive lymphocytes. It utilizes the immune systems ability to detect unknown antigens while not reacting to the self cells. During the generation of T-cells, receptors are made through a pseudo-random genetic rearrangement process. Then, they undergo a censoring process in the thymus, called the negative selection. In this process, T-cells that react against self-proteins are destroyed and only those that do not bind to self-proteins are allowed to leave the thymus. These matured T-cells then circulate throughout the body performing immunological functions and protecting the body against foreign antigens. 4 OBJECTIVES 1. To study intuitively and understand the working of dentritic cell and immune networks technique in artificial immune systems. 2. To analyse the two above mentioned techniques on the basis of the following parameters:- A. Accuracy B. Response time C. Fittest cell level D. Immune memory strength. 3. Mathematical and graphical comparison between dentritic cell and immune networks. 5 RESEARCH METHODOLOGY ALGORITHM DESIGN ( Dentritic Cell ) Its principle is taken up from the original dentritic cell mechanism in the human body with which our human immune system works. It generally takes advantage of the remembering power of our body in which if our body if exposed to a certain infection remembers it prevents it from harming us in at least near future, it also may cause permanent prevention. ALGORITHM DESIGN ( Immune Networks ) Its principle is taken up from the immune network mechanism which does not have fixed idea for prevention of particular disease in all senses. It undoubted takes up a more robust way of finding the right vaccine or the attack example for actual prevention. 6 RESULTS AND CONCLUSION Bar graph for less no of attacks Bar for all attacks Plot for less no. of attacks. Plot for all attacks. POINTS OF CONCLUSION The accuracy varies with no. of attacks. More the no. of attacks in DCT more is the accuracy. Accuracy in INT is not dependent on no. of attacks. Though the accuracy of the DCT is more but the response time of INT takes lead on DCT. In terms of response time INT is much better than DCT. DCT has time consuming behavior because of all internal processes which take place in it like updating memory cells and informing t cell etc. Memory strength of DCT improves with no. of attacks and it is status quo in INT. Fittest cell level show only local behavior of a part of the system having most immunity. In short term goals INT is preferable because its less time consuming and can act quick. Also its cheaper as no internal processes prevail. In long term goals DCT is preferred because of its stability. We need to have a really fast system to implement DCT because of its time consumption DCT is a central system because t cells keep record of all previous attacks and which is accessible to every part or ip in the network which makes DCT a central system. 7 REFERENCES [1] Ruiying Zhou, Qiuhong Fan, Mingjun Wei, â€Å"Solving for Multimodal Function with High Dimensions Base on Hopfield Neural Network and Immune Algorithm†, IEEE 2011 International Conference on Electronic Mechanical Engineering and Information Technology, Print ISBN- 978-1-61284-008-8, pp.3905-3908, 12-14 August 2011. [2] Shi Xu-hua, Zhu Yu-guang, â€Å"Dynamic Cloning based immune network Algorithm for multi-modal Optimization†, IEEE, Seventh International Conference on Natural Computation, 2011, Print ISBN- 978-1-4244-9953-3, pp.522-525. [3] Jun Fu, Huan Yang, â€Å"Introducing Adjuvants to Dendritic Cell Algorithm for Stealthy Malware Detection†, IEEE, Fifth International Symposium on Computational Intelligence and Design, 2012, Print ISBN- 978-0-7695-4811-1, DOI-10.1109/ISCID.2012.156, pp.18-22 [4] Song Yuan, Qi-juan Chen, â€Å"Dendritic Cell Algorithm for Anomaly Detection in Unordered Data Set†, 4th International Conference on Intelligent Human-Machine Systems and Cybernetics, 2012, Print ISBN- 978-0-7695-4721-3, DOI-10.1109/IHMSC.2012.69, pp.249-252 [5] Shi Xuhua, Qian Fenq, â€Å"An Optimization Algorithm Based on Multi-population Artificial Immune Network†, IEEE, Fifth International Conference on Natural Computation, 2009, Print ISBN- 978-0-7695-3736-8, DOI-10.1109/ICNC.2009.574, pp.379-383 [6] Andrew Kusiak, Zijun Zhang, â€Å"Optimization of Power and its Variability with an Artificial Immune Network Algorithm†, IEEE, Print ISBN- 978-1-61284-788-7 [7] Antariksha Bhaduri, â€Å"A Mobile Robot Path Planning Using Genetic Artificial Immune Network Algorithm†, IEEE, World Congress on Nature and Biologically Inspired Computing, 2009, Print ISBN- 978-1-4244-5612-3, pp.1536-1539 [8] Yong Sun, Weigou Zhang, Meng Zhang, Dan Li, â€Å"Design on Neural Network Gain Scheduling Flight Control Law using a Modified PSO Algorithm based on Immune Clone Principle†, IEEE, Second International Conference on Intelligent Computation Technology and Automation, 2009, Print ISBN- 978-0-7695-3804-4, DOI-10.1109/ICICTA.2009.70, pp.259-263 [9] Chung-Ming Ou, C.R. Ou, â€Å"Immunity Inspired Host-Based Intrusion Detection Systems†, IEEE, Fifth International Conference on Genetic and Evolutionary Computing, 2011, Print ISBN- 978-0-7695-4449-6, DOI-10.1109/ICGEC.2011.70, pp.283-286 [10] Maizura Mokhtar, Ran Bi, Jon Timmis, Andy M. Tyrrell, â€Å"A Modified Dendritic Cell Algorithm for On-line Error Detection in Robotic Systems†, IEEE, Congress on Evolutionary Computation, 2009, Print ISBN- 978-1-4244-2959-2, pp.2055-2062 [11] Yunfeng Zhao, Yixin Yin, Dongmei Fu, Zhun Zhou, Ping Yin, Jia Wang, â€Å"Application of Improved Artificial Immune Network Algorithm to Optimization†, IEEE, 2008, Print ISBN- 978-1-4244-2386-6. [12] Zhonghua Li, Jianming Li, Jieyeing Zhou, â€Å"An improved artificial immune network for multimodal function optimization†, IEEE, The 26th Chinese Control and Decision Conference, 2014, Print ISBN- 978-1-4799-3707-3, DOI-10.1109/CCDC.2014.6852268, pp.766-771, May 31st – June 2nd 2014.

Information Security Essay

Information Security is a fundamental function of any organization expecting to be competitive in the global market. As more and more developing countries make the leap into capitalism, competiveness will only become more essential. With Asian nations like China, Korea and India stepping up to make their presence noticed taking more of the market share than ever before other organizations must remain competitive which means keeping their piece of the pie safe and secure. Organizations’ proprietary information if left unsecure could mean loss of their competitive edge. In the IndustryWeek. com article by, â€Å"Manufacturers Must Think Virtually to Ensure Data is Protected† Chris Benco contends; â€Å"Data is what all manufacturers rely upon, and with the ever-increasing influx of it, companies need to ensure that it is protected in the event of a natural disaster, human error or other problems. With this heavy reliance on data to maintain day-to-day operations, manufacturers cannot afford to overlook data protection as it is the key in maintaining production, optimizing productivity and guaranteeing profit. Information security though takes on another aspect when you consider an often over looked key element of corporate information. We think of information security in terms of protecting what is on paper and in data bases, but knowledge is much harder to nail down. Knowledge, information that is stored in the minds of the organization’s personnel is just as important as any other data or product information and should be gathered and stored just the same. As we could see in the reading material for this case assignment there are many methods for obtaining, sharing, and storing knowledge information. Some such methods were discussed by Ann Field in her article â€Å"Locking Up What Your Employees Know†. The step according to Ms. Fields are to first Create a knowledge profile, then foster mentoring relationships, encourage communities of practice, ensure that passing knowledge on is rewarded, Protect people’s privacy, and decide whether you’re interested in recorded knowledge as well.

Blame in Romeo and Juliet Essay

In the play â€Å"Romeo and Juliet† a series of unfortunate the circumstances and illogical decisions force the protagonists into an impossible position ultimately resulting in their death. As Il-fated as the two â€Å"star-crossed lover’s† may have been the root of all their problems can be traced back to rash decisions by characters and circumstances placed unfairly on characters by warped societal expectations. While the Friar had nothing but the best intentions his illogical and somewhat naive decisions contributed greatly to the tragedy of Romeo and Juliet. Romeo’s impulsive, dangerous and irrational behavior is also to blame. Societal expectations and outside influences can be partly to blame for many of the characters irrational decisions. Although these expectations could be to blame for two lovers parents behavior it does not justify them completely, thus they are also to blame. None of these reasons can be blamed in isolation but all contributed to the ultimate outcome of Romeo and Juliets relationship. The Friar was very mush to blame for the tragic outcome of Romeo and Juliet. He was continuously relied on for advice from Romeo and Juliet and failed to acknowledge his mistakes after their deaths. The Friar is blame because he married the two with their parents consent and thought that Romeo’s love lied â€Å" not truly in [his] heart, but in [his] eyes†. Instead he foolishly chose to marry the two, purely â€Å"to turn [their] households’ rancor to pure love† despite being unknowing of the true nature of their dispute as a priest. Not only this, but he also expressed that things were moving too fast and that â€Å"violent delights (such as Romeo’s and Juliet’s love) have violent ends† but continued with the wedding anyway. He failed to listen to his own wisdom and take things â€Å"wisely and slowly†. Despite prolonging the lives of two suicidal teenagers, they placed their trust in him when he promised to â€Å"blaze [their] marriage†¦beg pardon to the Prince, and call thee back†. Because he made no attempt at doing so, he instilled false hope into the couple, which also contributed to their deaths. Furthermore he failed to personally deliver the letter explaining Juliet’s faked death to Romeo, instead outsourcing it to another Friar without telling him of its urgency. This lack of responsibility repeats itself when he gives an unstable, teenage girl a fake-death poison, a risky idea he should have known better not to do. Furthermore, he leaves Juliet when she is at her most vulnerable,  alone together with her dead husband. Because he was the only adult Romeo could trust, the Friar’s naive, rash and immature decisions that neglected to look after Romeo and Juliet properly were at the epicenter for why their deaths occurred. The melodramatic character of Romeo is also very much to blame for his fate because of his impulsive decisions and his inability to control his emotions. Mature enough to show genuine love for Juliet he is unable to make logical decisions. Although he showed enough common sense to avoid a fight with Tybalt it is clear that when misfortune swallows Romeo he becomes an impulsive and somewhat selfish person, valuing his own pride over a life together with Juliet. His immaturity is illustrated when he describes himself as â€Å"fortunes fool† or saying that Juliet made him weak, as he is merely passing the blame along rather than accepting full responsibility. It is obvious that because of Romeo’s weakness, Juliet suffers too. Whether it is taking a potion or killing herself she continuously risks her neck to help undo her husband’s wrongdoings. In Friar Laurence’s words Romeo â€Å"is set afire by thine own ignorance†¦ like powder in a skill-less soldiers flask.† By climbing the Capulet’s walls, marrying Juliet within days, killing Tybalt and himself, his lack of foresight and awareness of how his actions affected others ultimately lead to Juliet’s and his own death. The pressures and expectations formed and enforced by society, forced the characters, into impossible situations, which forced difficult and risky decisions. The Patriarchal society meant women such as Juliet had no voice in things such as their own marriage. This, coupled with the unjustified conflict in Verona meant that Juliet was unable to Marry in public, which set off a chain of events ultimately leading to her death. These same values forced Romeo into conflict with the malevolent Tybalt. At first he eludes fighting, telling Tybalt that he â€Å"loves thee better than thou cant devise† but despite being loving person at heart the patriarchal society which promoted masculinity acted as a catalyst for Romeos impulsive character. The corrupting influence of this societal value forced Romeo to maintain honor and revenge Tybalt because Juliet â€Å"made him effeminate† or weak like a women. Furthermore the societal values of loyalty to one family meant pride  alone kept the futile conflict a part of everyone’s lives. Because of this and the need to respect ones elders unconditionally it meant that Romeo and Juliet were not able to stand up to their parents and declare the marriage public. When Juliet showed any sort of rebellion toward her parent regarding marriage she was abused and practically disown. Even after this loyalty to her family influenced Juliet to use â€Å" a thing like death† in order to be with Romeo and â€Å"to ‘scape from (the shame)† that would come with running away from her family. The Parents of Romeo and Juliet are also to blame because as adults they should have showed maturity and put away their pride like the youthful Romeo and Juliet and put an end to the unjustified conflict. Firstly Capulet directly influences the outcome by forcing the marriage between Juliet and Paris despite Juliet’s obvious discomfort. But as adults they had the greater responsibility of putting an end to the conflict but quite to the contrary they were seen encouraging and wanting to actively engage in it when the fight broke out between rival servants. The reason for the tragedy cannot be blamed on fate because the environment that the parents created meant that their whole love affair was doomed from the beginning. There was no-way their marriage in secret could last forever because enviably Juliet would be forced to marry somebody else. The hope, which the youthfulness of Romeo and Juliet embodied, was foiled by the reality created by their parents. Without this mutual ha ted the fight between Tybalt and Mercutio would not have occurred, and there would be no issue marrying Romeo thus the outcome of the play can be directly attributed to the conflict instilled in society by the parents of Romeo and Juliet. In the play a series of unfortunate situations and illogical decisions by characters create a downhill spiral, which escalates ultimately to the death of Romeo and Juliet. The Friar can be regarded as the character that should have and did know better but failed to act accordingly. While Romeo blinded by emotions failed to make logical decisions or take into account the impact they had on others. These characters were put under unnecessary pressure by social expectations that existed primly because the parents of Romeo and Juliet failed to stop the unjustified conflict in Verona. None of these  factors can be blamed in isolation they all were pivotal causes of the tragedy of Romeo and Juliet.

How A Bill Becomes A Law - 1125 Words

A president of our United States once claimed that â€Å"Can’t living with a bill means it won’t become law† (AZ Quotes). However, is George W. Bush right? Will a â€Å"bad† law ever get passed. Well, to answer that question, you need to know how a bill becomes a law. It is pretty widely known that there are three branches of the United States Government. It has been this way since the US Constitution created our national government over 200 years ago. With these multiple branches to speak of there must be some way to make sure that none of them has too much power. Thus is the mission of checks and balances. Checks and balances are built into the government and they are designed to keep one branch from becoming too powerful by checking/balancing the power of the branch with one or two of the other branches. There are several ingenious that the legislative, or law writing branch is checked by the executive, main ruling bodied, branch, and the judicial, cour t filled, branch. The monumental process of checks and balances is displayed incredibly in the complex political process of how bills become laws, preventing a single legislature from controlling the whole US, resulting in a likely tyranny. For a proposed idea, in a bill, to become a law, there are many steps, in two branches of government, it is required to take. A bill is a legislation that has been proposed to the legislature and is not yet passed into official rule, or a law. Bills have to follow a process for it to becomeShow MoreRelatedHow a Bill Becomes a Law1118 Words   |  5 PagesThe road a bill takes to becoming a law is a long and tedious process. First, the proposed bill goes through the House of representatives. Once the bill has been approved by the House, it is then begins its journey through the Senate. After the bill has been endorsed by the Senate, the houses of congress then meet in conference committees to prepare the bill to be sent to the White House. To su mmarize, the path the bill takes to become a law is a fairly complex impediment. br brNow to begin,Read MoreHow a Bill Becomes a Law1156 Words   |  5 Pagesmajor role in decision making. They’re primary role is to pass laws. These laws start off as bills. Bills can only be introduced by members of Congress. Although these bills only come from Congressman, there are many people who influence these bills. Such as the president, regular citizens, offices in the executive branch, and many others. The bills right off the bat do not have a very good chance of passage. Only 1 out of every 10 bills even gets any attention at all. This is because they must goRead MoreHow A Bill Becomes A Law1180 Words   |  5 Pagesmajor role in decision making. They’re primary role is to pass laws. These laws start off as bills. Bills can only be introduced by members of Congress. Although these bills only come from Congressman, there are many people who influence these bills. 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First, the proposed bill goes through the House of repr esentatives. Once the bill has been approved by the House, it is then begins its journey through the Senate. After the bill has been endorsed by the Senate, the houses of congress then meet in conference committees to prepare the bill to be sent to the White House. To summarize, the path the bill takes to become a law is a fairly complex impediment. Now to begin, the bill mustRead MoreEssay On How A Bill Becomes A Law743 Words   |  3 Pages How a bill becomes law is not as easy as expected. In my paper it is important for me to explain the basics which are a total of ten steps a bill have to take before it become a law. First, a bill is originated from an idea, then it is proposed and introduced to the house of representatives. The bill is then reviewed and then it gets debated on the floor where if it passes will be received by the senate. 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First, the legislation is introduced, and then you have the committee action, afterwards floor action, conference committee, the president, and then the bill becomes a law. Some bills will never make it through any of these processes but for those who really want their bill to pass, if they fight for it they just might get lucky. This paper will show you that it takes more thanRead MoreEssay On How A Bill Become A Law1000 Words   |  4 Pages How A Bill Become A Law What is a bill? A bill is proposed laws and lawmaking being thought about carefully by a government. A bill does not become law until it is passed by the government and, in most cases, approved by the executive. Once a bill has been put into law it is called an act of the government, or a law. Before a law is made it has to be passed through both House of congresses. Laws begin as ideas. These ideas may come from a Representative--or from a person who lawfullyRead MoreEssay On How A Bill Becomes A Law840 Words   |  4 PagesHow a Bill Becomes a Law Creating laws is the U.S. House of Representatives most important job. All laws in the United States begin as bills. Before a bill can become a law, it must be approved by the U.S. House of Representatives, the U.S. Senate, and the President. The road a bill takes to becoming a law is a long and tedious process. First, the proposed bill goes through the House of Representatives. Laws begin as ideas. These ideas may come from a Representative, or from a citizen. Citizens