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Sweatshops
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Sweatshops
Globalization has opened up new opportunities for trade, and many companies have taken advantage of this to reduce production costs. American companies such as Nike, Apple, and many others have shifted their factories to developing countries, widely referred to as sweatshops. The debate around these sweatshops is a polarizing one, with supporters arguing that the factories offer poor people employment opportunities as a way out of poverty. On the other hand, opponents of the idea explain that sweatshops are exploitative mainly due to the low wages paid to workers, and therefore companies should raise wages or close shop in such developing countries. The main reason why companies choose to outsource production is because of lower costs. Developed countries such as the United States have high minimum wages, while developed countries do not have such laws. This means that companies can pay workers very little money in developing countries, which cuts the cost of production.
Outsourcing may be profitable for companies, but they have a negative impact on American workers. Low skill laborers stand to lose the most with outsourcing. Many of the outsourced jobs require very little training and skill, therefore having such factories in the country would offer employment opportunities for low-skilled workers. Because the majority of companies choose to outsource for economic reasons, such workers lose out on job opportunities. Outsourcing serves to lower the domestic prices of goods. The main reason for this is that lower costs of production allow companies to set prices lower. Other factors, such as lower taxes with outsourcing, further reduces the domestic prices of outsourced goods.
For the US government to reduce outsourcing, some policy changes required would be tax breaks and lowering the minimum wage (Sollars & Englander 19). Wages are the most significant impediment when it comes to setting up factories in the United States. Domestic law requires companies to pay employees a minimum wage that is comparatively much higher than those paid in developing countries. Most developing countries have no minimum wage laws, which allows companies to set their own wages for workers. Tax breaks would also be an incentive to reduce outsourcing, as companies would not have to pay as much taxes that further eat into their profit margins. Tax breaks involve lowering taxes that a company has to pay to reduce production costs.
From the two videos, the idea of sweatshops is quite different for different people. For example, the John Stossel video includes interviews from students protesting against sweatshops in developing countries. These students explain that sweatshops are exploitative, and take advantage of poor populations by paying them very low wages. On the other hand, people from these developing countries see sweatshops as beneficial to their lives, because the wages help them meet their basic needs every day. The video on the Apple factory in China presents the same idea. One point of criticism for the factory is that it employs teenagers, and workers live in a dorm as they cannot afford other accommodations (SocProf Jordan). Most workers have never even seen a working iPad, the item they work so hard to create every single day. The factory has also reported several suicides over the years. Despite this, people in the villages that the factory workers come from appreciate the employment opportunities brought by the sweatshops, and they believe that the factories have made their lives better. The conclusion from the two videos is that sweatshops are a good thing for foreign workers. Without these factories, the impoverished workers would have no other source of income.
Works Cited
SocProf Jordan. “Inside Look At Apple’s Chinese Sweatshops!” YouTube. 29 September 2013. https://www.youtube.com/watch?v=unrZw5qZzwsSollars, Gordon G., and Fred Englander. “Sweatshops: Economic analysis and exploitation as unfairness.” Journal of Business Ethics 149.1 (2018): 15-29.
Strong and Affordable Location Privacy in VANETS Identity Diffusion Using Time-Slots and Swapping
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Strong and Affordable Location Privacy in VANETS: Identity Diffusion Using Time-Slots and Swapping
Vehicular Ad Hoc Networks (VANETs) need a way to help authorize messages, remove malevolent vehicles, and find valid vehicles. A public Key Infrastructure (PKI) can offer this operation using fixed public keys and certificates. However, the used of fixed keys allow an adversary to associate a key with a place and a vehicle, thus compromising the privacy of a driver. The use of Temporary Anonymous Certified Keys (TACKS) is a scheme management by VANET to improve diver’s privacy. The approach of this scheme efficiently hinders eavesdropping from associating different keys and gives timely revocation of participants misbehaving while sustaining less or the same overhead for car-to-car communication like the current IEEE 1609.2 standard used in VANET security.
The major concern for deploying VANET in the public is the achievement of effective and simple security mechanisms. Insecurity in VANET translates a broad system open to a number of security attacks such as suppression of real warning messages as well as propagation of false messages of warning, thereby leading to many accidents. The vulnerability of vehicles to security attacks in VANET makes security a major concern when coming up with such systems (Eckhoff).
Privacy is introduced into a VANET network system by using pseudonyms in the form of more block of private of public keys which are provided to the user. The keys are used for a short period and then become changed frequently. The keys are made in a way that they do not bear identity associated information but have the capability of being traced back to the user in the liability linked cases. The follow-up is usually done by Central Authorities (CA). Pseudonyms get used because they make sure that the vehicle a vehicle does not get attacked by an adversary or any other attacker and a message cannot be associated to its sender by other cars.
Instead of equipping vehicle nodes with a lot of pseudonyms, each node bears a time-clotted pool of pseudonyms with slot length t, so that p/t time-slots span the length period p. every single time-slot is assigned exactly one pseudonym, leading to p/t pseudonyms for each vehicle, and a single valid pseudonym for each arbitrary point in time. When a particular slot of time passes, a change of pseudonym gets initiated. This mechanism is usually achieved by use of clocks, which are synchronized with the Global Positioning System (GPS) signal.
The use of non-overlapping pseudonyms, similar to time-slots, implies that nodes in this scenario have the advantage of reusing pseudonyms. When the last time-slot—p/t the time-slot—has passed, time-slot 1 will get activated again, meaning that periodic time will then reload from the beginning.
A good choice of the values of p and t is very important to make sure security is realized. For instance, if t= 20 minutes and p is one week, then the pseudonym generated becomes valid, such as, Monday 7:00 a.m. till 7:20 a.m. it is vital for one to notice that the above pseudonym is then, in fact admissible on every Monday for the said 20 minutes. It is clear from the above scenario that place privacy that comes with time-slotted pool alone depends not only on the time slot-length (t) that determines the frequency of change for a node pseudonym, but also on the reliability of the periodic behavior of the node, such as, beginning the work-commute every Monday 7:00 a.m.
The exchange of pseudonyms can improve the privacy of drivers in VANET by complicating tracking for an attacker. When nodes have the ability to exchange pseudonyms in secrecy by use of encryption and keep third parties at bay from tracking nodes, which have exchanged pseudonyms, then a possible way of mapping authority also becomes admissible. The time-slotted mechanism allows only valid pseudonyms for a particular time-period to be exchanged; otherwise there is usually no guarantee that each car has exactly one pseudonym per time-slot (Chaurisia and Verma).
A node usually scan its surrounding ( such as speed, heading of its neighbors, and vehicle number) and then comes up with a decision on whether change of pseudonym if important or not, so that attackers cannot infer node pseudonyms simply after the swapping by elongating their expected place according to their last known speed and heading.
By a careful choice of limits of similarity, people can increase the possibility of both swap vehicles being unknown in terms of place. An adversary can then never know whether a pseudonym swap took place or not. The efficacy of this approach, of course, is greatly dependent on the positional and frequency accuracy of the beacons emitted by each car. The driver privacy achieved by use of this mechanism can be augmented by using silent time-slots, meaning two vehicles will not send beacons for a while after a possible swap of pseudonyms (Sun et al.).
An advantage that comes with time-slotted mechanism over pseudonym pool is its characteristic of making sure that, ideally, a car always has a pseudonym to take part in the ITS as provided it has received its p/t pseudonyms during the setup period. Whether a CA is not reachable or the vehicle was not used for longer period the car will not exhaust the pseudonyms because it has the chance of reusing old pseudonyms.
The mechanism also comes up with upper bounds of disk space and, importantly, the volume of traffic. This simplifies the make-up of the on-board units and cuts the costs of communication, bring affordability to the deployment of an ITS. The size of the pool of pseudonyms is cut to a value of p/t * s bytes and, importantly, workload of the CA no longer depends on the number vehicular nodes taking part in the network but on the ones entering it.
The use of GPS synchronized clocks and time-slots, by every node will make sure that nodes swap pseudonyms at the same time. Density of traffic and rate of penetration dependency increases traffic driver’s privacy. Further use of pseudonym exchange much improves the security of drivers (chaurasia and verma).
A common problem associated with the time-slot mechanism is that when cars swap currently valid pseudonyms—their current identifier—each vehicle will begin using the same pseudonym every p/t slots, due to the fact that a new slot n + 1 has begun, the pseudonym previously used in the slot will then be reactivated. This way, an adversary, or authority, is able to associate two positions to a single node. The current one (such as, Monday 7:00:00 a.m.) and the one from the earlier time the slot was active (such as, 7:19:59 a.m.). Moreover, each time a new vehicle gets into a time-slot for the first time, which will occur p/t times after being attached with the ITS device, the operator can associate the first place in this time-slot to a vehicle.
A diagram to illustrate the swapping of pseudonyms by two vehicles
References:
Eckhoff, Dacid et al. Strong And Affordable Location Privacy In VANETS: Identity Diffusion Using Time-Slots And Swapping. Gaimersheim: University of Erlangen.
Chaurasia and verma. Optimizing Pseudonym Updation for Anonymity in Vanets. Allahabad, Indian Inst. Technol., 2008.
Sun, Jinyuan et al. An Identity-Based Security System for User Privacy in Vehicular Ad Hoc Networks. Knoxville: Univ. of Tennessee, September, 2010.
Chaurisia and Verma. Maximizing Anonymity of A Vehicle. Allahabad: Indian Inst. Technol., 2008.
Stealing, Theft and Robbery
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Stealing, Theft and Robbery
People in any society experience some form of crime, hence the need for law and order. Some of the most common crimes in the world are stealing, theft and robbery. Although many people use the terms interchangeably, there are some differences between the three. Stealing refers to the act or process of taking something that belongs to someone else. Theft and robbery are the legal terms used to define the crime of stealing, though there is one main difference. Robbery involves violence or coercion in the process of taking something, while theft does not involve force. In fact, one may not realize till much later that they have been the victim of theft, and a perfect example of this is identity theft. Due to the violence involved, robbery is taken as a more serious crime than theft under the law. Stealing, theft and robbery are common occurrences in society. In examining this topic, some relevant areas include statistics, punishment under the law, effects of the crimes and preventive measures.
Statistics from The Pew Research Organization sheds some light on violent crimes such as robbery in the United States. Data shows that violent crimes have been on the decline since the 1990s, with a 51% decrease between 1993 and 2018, according to numbers from the FBI (Gramlich 1). The report also indicates that non-violent crimes such as motor vehicle theft, burglary and theft are far more common than violent crimes. Despite the steady decline in violent crimes, many Americans’ opinions do not reflect this. For example, a 2016 Pew Research poll found that 57% of registered voters at the time believed than rates of crime were higher than the year before, despite the FBI reports showing a double-digit decline. Stealing, theft and robbery fall under the category of property crimes, which have similarly been on the decline. For example, in the year 2017, robbery rates stood at roughly 99 robberies per 100,000 people, and this fell to 87 per 100,000 people in 2018 (Gramlich 2). This is according to data from the Federal Bureau of Investigations.
Despite the promising outlook on cases of theft and robbery, identity theft remains a primary area of focus as instances of identity theft have become more common. Identity theft is a crime where a person obtains another’s personal information such as their social security number, then uses this information to impersonate the person for various reasons such as to obtain a loan, or pay for goods. The number of identity fraud cases is on the rise, mainly due to the digitization of all areas of life. With people working from home, shopping and placing orders online, and filling out various forms over the internet, their information becomes an easy target for hackers and identity fraudsters. Children have especially become an easy target for identity theft. In 2018, the Bureau of Justice Statistics reported 14.4 million cases of identity fraud (BJS). Javelin Strategy & Research focused on cybercrimes and compiled a comprehensive report on identity fraud in the year 2019. Although numbers dropped from 16.7 million in 2017 to 14.4 million in 2019, consumers bore a heavier financial burden. For example, the out of pocket costs on the victims as a result of the crime doubled to $1.7 billion from 2016 to 2019 (Ahmed 21). Additionally, 3.3 million of the consumers who fell victim to identity fraud were found to be liable or partly liable for the crimes against them.
Americans remain the most likely victims of identity theft than people from any other country, with more than 791 million identities stolen in the year 2016 alone. Statistics from a Javelin poll give more insight into why this is the case. 60% of consumers report feeling that their information is safe when using public Wi-Fi networks, which makes them more vulnerable to attack. 43% of adults admitted to shopping online over public networks, and 33% of American adults also reported sharing passwords and account names with others (Zhang 55). A majority of small business, 52%, have no cyber protection investments as they do not believe they could be victims of attacks. One of the verified ways of increasing protection online is the use of a VPN, but 75% of customers still do not use it. Account takeovers are the most prominent form of identity fraud, where fraudsters access a person’s account and change their security information such as passwords. EMV-chip-based credit cards are mostly responsible for the decline in fraud as skimmers cannot copy them.
There are many reasons why people would engage in stealing, theft and robbery, the most prominent of which is material gain. Most thefts and robberies are motivated by financial gain. An excellent example of this is the case of identity theft, where account losses resulted in the loss of $5.1 billion in 2017 alone. Theft is an easy way to make money, especially in cases where the victims do not realize the crime immediately. Identity fraudsters can sell the information they steal in the deep web to criminals who want to use it for different things (Zou et al. 8). Material gain is also the primary motivation for violent robberies. This includes robberies on stores, banks and other commercial businesses. Robbers target cash and other valuable items from these premises. Criminals also engage in theft and robbery just because they can. Some hackers and identity thieves gain access to other people’s information to prove their skill and ability to get away with it.
To avoid falling victim to theft and robberies, there are different things that people can do. The law also protects people by punishing offenders, but the first step to protecting oneself is to be vigilant and proactive. The most critical step in dealing with the issue of theft and robbery is the awareness that anyone can be a victim. With this in mind, people should take care to protect themselves as much as they can. For example, homes and business premises should have alarms installed that one can access in case of any violent attacks. People should learn basic tactics on how to deal with robbers, such as compliance to avoid further injury or harm. On the issue of identity theft, people should improve their safety online by using VPNs to protect their information (Zhang 42). They should also avoid using public networks when sharing sensitive information, such as social security numbers or credit card information. Companies and business should also invest in protecting consumers’ information. The Equifax hack in 2016 led to the stealing of information of millions of Americans, which is a potential avenue for identity theft (Zou et al. 11). Companies should thus take adequate and proactive measures to protect their customers’ data as much as they can.
Under the law, robbery and theft are serious charges depending on the seriousness of the crime. Most states have divided robberies into categories such as simple, aggravated, first-degree or second degree. These categories dictate the punishment that an offender receives. In most cases, robberies are felonies that attract at least a one-year jail term. Punishment depends on the violence of the crime, the value of property stolen, the offender’s criminal record, among other factors. Identity theft carries charges similar to those of robbery, depending on whether the crime is classified as a misdemeanour or felony. Different states have different statutes for identity theft. For instance, Arizona classifies the trafficking in a stolen identity as a Class B felony. Having a record of such crimes of ‘moral turpitude’ can have a significant impact on an offender’s life. For example, a person with such a criminal record will usually have a hard time getting employed as these records show up in a standard background check. Theft and robbery also adversely affect victims of the crimes. They lose their valuable items, some of which may never be recovered. Victims of identity theft experience some financial losses as well as access to their personal information which opens them up to other problems. Being a victim of theft or robbery also comes with psychological effects such as paranoia, fear, and trauma (Golladay & Holtfreter 751).
In conclusion, stealing, theft and robbery are serious crimes ranging from petty offences to more serious ones. Some of the most common kinds of theft and robbery include identity theft, home invasions and motor vehicle theft. Statistics from the FBI and Bureau of Justice Statistics show the trend of crimes over the years, with a general downward trend in violent crimes. Identity theft is one of the biggest concerns for consumers as people shift to online activity such as shopping and banking for convenience. Anyone can be a victim of these crimes, and people should learn some necessary forms of defences. All kinds of crime are punishable by law, but individuals must take proactive measures to keep themselves and their property safe.
Works Cited
Ahmed, Syed R. Preventing Identity Crime: Identity Theft and Identity Fraud: An Identity Crime Model and Legislative Analysis with Recommendations for Preventing Identity Crime. BRILL, 2020.
Golladay, Katelyn, and Kristy Holtfreter. “The consequences of identity theft victimization: An examination of emotional and physical health outcomes.” Victims & Offenders 12.5 (2017): 741-760.
Gramlich, John. “5 Facts About Crime in the US.” Pew Research Organization. 17 October 2019. https://www.pewresearch.org/fact-tank/2019/10/17/facts-about-crime-in-the-u-s/STATISTICS, BUREAU OF JUSTICE. “IDENTITY THEFT.” (2018).
Zhang, Joe. “Holster with protection mechanism facilitating Holstering and unholstering and protecting against theft and robbery.” U.S. Patent No. 10,041,762. 7 Aug. 2018.
Zou, Yixin, et al. “” I’ve Got Nothing to Lose”: Consumers’ Risk Perceptions and Protective Actions after the Equifax Data Breach.” Fourteenth Symposium on Usable Privacy and Security ({SOUPS} 2018). 2018.